The Physical Internet: a new grand challenge for customs authorities?

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The Physical Internet: a new grand

challenge for customs authorities?

An exploratory study into the impact of the

Physical Internet on the Dutch Customs Administration

Master’s dissertation

Presented for:

MSc Technology & Operations Management (University of Groningen)

MSc Operations & Supply Chain Management (Newcastle University Business School)

Written by:

Niek Florian Hacquebord

n.f.hacquebord@gmail.com

S2980614 B9059558

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If you want to go fast, go alone. If you want to go far, go together

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ABSTRACT

Purpose: current performance of logistics networks is unsustainable in terms of its economic,

environmental, and societal impacts. The future vision of the Physical Internet (PI) is proposed as the solution to overcome this sustainability grand challenge. In the development of the vision, customs authorities and other regulatory agencies have consistently been omitted. This study aims to explore how the PI might impact the operations of customs authorities and to identify requirements to the PI from the perspective of the Dutch Tax and Customs Administration. Based on the requirements, this study proposes a first conceptual system design for Dutch Customs to deal with the expected impacts of the PI. The study thereby takes a first step in filling the gap in the academic literature.

Methodology: a design science project was performed to design a first conceptual system for customs

authorities in the PI. Empirical data was collected in a single case study at the Dutch Tax and Customs Administration. The (academic) literature on data pipelines and smart containers was used as the basis for the design of the proposed system. Two validation workshops were then held with various stakeholders to evaluate the proposed conceptual system.

Findings: the findings indicate that customs authorities have a very limited set of information available

to base their risk assessment on, even though the risk assessment is crucial for the enforcement of the security and safety of border-crossing flows of goods. This can mainly be attributed to the fragmented information landscape that exists in current business environments. Dutch Customs needs more data and information that is of higher quality and received at an earlier stage in the logistics chain. The data pipeline concept was identified as being able to fulfil Dutch Customs’ needs, to increase the quality of risks assessments and thereby eliminate the number of unnecessary interventions that disrupt logistical flows.

Contribution: this study is the first to explicitly recognise and address the important role of customs

authorities in the future vision of the PI. Being exploratory in nature, it presents a first conceptual system design, based on the data pipeline concept. It further proposes avenues for future research for the further development of the conceptual system presented in this study.

Keywords: Physical Internet (PI), data pipeline, data sharing, information infrastructure, customs

authorities, design science research (DSR), case study.

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PREFACE

This study was conducted as the dissertation project for the MSc Technology Operations Management at University of Groningen (Faculty of Economics and Business) and the MSc Operations & Supply Chain Management at Newcastle University (Business School). First and foremost, I would like to thank my university supervisors Dr. Nick Szirbik and Dr. Rebecca Casey for their enthusiasm and continuous guidance, support and feedback over the course of this project. In addition to that, this project would not have been possible without the guidance of Winfred Kooij and Stef Pastoor, who have supported me from day one in finding my way in the world of the Dutch Tax and Customs Administration, even though it was mostly online as a result of COVID-19. With their knowledge they guided me in the right direction and with their network they have been able to provide me with very valuable sources of information both within Dutch Customs as well as outside of it. Furthermore, I want to express my sincere gratitude to Jaco Voorspuij for his enthusiasm about my research, for proof-reading the draft version of this work and for sharing his knowledge and insights with me. Next to that, I would like to thank Patrick Fahim for his valuable inputs with regard to the organisation of the validation sessions. Finally, many thanks to all others that have been involved in some other way in this project: colleagues at Dutch Customs, workshop participants, academics, fellow students, friends, and family. Without your support, writing this paper would not have been possible.

Niek Hacquebord

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LIST OF FIGURES

FIGURE 2.1:US FREIGHT TRANSPORTATION BY TRANSPORT MODE (DATA FROM USDEPARTMENT OF TRANSPORTATION,2019) ...5

FIGURE 2.2:PILLARS OF THE PI...7

FIGURE 2.3:ENFORCEMENT VISION DUTCH CUSTOMS (DNL,2014) ... 13

FIGURE 4.1:DESIGN SCIENCE RESEARCH CYCLES (HEVNER,2007, P.2) ... 16

FIGURE 4.2:THE REGULATIVE CYCLE (WIERINGA,2009) ... 17

FIGURE 5.1:KEY ACTORS/ROLES ASSOCIATED WITH THE FOUR MAIN BUSINESS AREAS (UN/CEFACT,2018) ... 23

FIGURE 5.2:HIGH LEVEL CONCEPT OF THE NATIONAL SINGLE WINDOW (NICULESCU AND MINEA,2016) ... 24

FIGURE 5.3:SEAMLESS INTEGRATED DATA PIPELINE (ADAPTED FROM TASK 360TEAM,2013) ... 26

FIGURE 6.1:BENEFITS OF SMART CONTAINER SOLUTIONS (UN/CEFACT,2019B) ... 31

FIGURE 6.2:PHASE ONE OF THE EXIT PROCESS UNDER STAGE 1 ... 33

FIGURE 6.3:PHASE TWO OF THE EXIT PROCESS UNDER STAGE 1 ... 34

FIGURE 6.4:PHASE ONE OF THE EXIT PROCESS UNDER STAGE 2 ... 36

FIGURE 6.5:PHASE TWO OF THE EXIT PROCESS UNDER STAGE 2 ... 37

FIGURE 6.6:EXIT PROCESS UNDER STAGE 3 ... 40

FIGURE 7.1:EXAMPLES OF TRADE DATA (BASED ON HU ET AL.,2016) ... 45

FIGURE A.1:PILLARS OF THE PI ... 58

FIGURE A.2:POTENTIAL DIMENSIONS FOR THE MODULAR Π-CONTAINERS (MONTREUIL ET AL.,2010) ... 60

FIGURE A.3:MODULARITY OF Π-CONTAINERS (MONTREUIL ET AL.,2010) ... 60

FIGURE E.1:PHASE ONE OF THE EXIT PROCESS IN THE CURRENT STATE... 71

FIGURE E.2:PHASE TWO OF THE EXIT PROCESS IN THE CURRENT STATE ... 74

FIGURE F.1:PHASE ONE OF THE EXIT PROCESS UNDER STAGE 1 ... 75

FIGURE F.2:PHASE TWO OF THE EXIT PROCESS UNDER STAGE 1 ... 76

FIGURE F.3:PHASE ONE OF THE EXIT PROCESS UNDER STAGE 2 ... 77

FIGURE F.4:PHASE TWO OF THE EXIT PROCESS UNDER STAGE 2 ... 78

FIGURE F.5:THE EXIT PROCESS UNDER STAGE 3 ... 79

FIGURE F.6:EXAMPLE OF HOW THE PIPELINE IS FILLED IN THE EXIT PROCESS ... 80

FIGURE G.1:PHASE ONE OF THE ENTRY PROCESS IN THE CURRENT STATE ... 83

FIGURE G.2:PHASE TWO OF THE ENTRY PROCESS IN THE CURRENT STATE ... 86

FIGURE H.1:PHASE ONE OF THE ENTRY PROCESS UNDER STAGE 1 ... 87

FIGURE H.2:PHASE TWO OF THE ENTRY PROCESS UNDER STAGE 1 ... 88

FIGURE H.3:PHASE ONE OF THE ENTRY PROCESS UNDER STAGE 2 ... 89

FIGURE H.4:PHASE TWO OF THE ENTRY PROCESS UNDER STAGE 2 ... 90

FIGURE H.5:THE ENTRY PROCESS UNDER STAGE 3 ... 91

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LIST OF TABLES

TABLE 4.1:SUMMARY OF PROPOSED APPROACH... 17

TABLE B.1:OVERVIEW OF THE KEY BENEFITS OF PRIOR (EMPIRICAL)PI RESEARCH... 61

TABLE C.1:OVERVIEW PARTICIPANTS VALIDATION WORKSHOP 1 ... 62

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LIST OF ABBREVIATIONS AND ACRONYMS

ACN Air Cargo Netherlands

ACXIS Automated Comparison of X-ray Images for cargo Scanning

AEO Authorised Economic Operator

ALICE Alliance for Logistics Innovation Through Collaboration in Europe

APEC Asia-Pacific Economic Cooperation

API Application Programming Interface

ATA Actual Time of Arrival

BCO Beneficial Cargo Owner

B2B Business-To-Business

B2G Business-To-Government

C-BORD Effective Container Inspection at BORDer Control Points

CCP Consignment Completion Point

CIRRELT Interuniversity Research Center on Enterprise Networks, Logistics and Transportation

CRIS Customs Real-time Information system

DNL Dutch Tax and Customs Administration

DS Design Science

DSR Design Science Research

DTLF Digital Transport Logistics Forum

EC European Commission

EEA European Environment Agency

ENS Entry Summary Declaration

EO Economic Operator

ESC European Shippers’ Council

ETA Estimated Time of Arrival

EU European Union

EU27 27 member countries of the EU1

GDP Gross Domestic Product

GHG Greenhouse Gas

IATA International Air Transport Association

ICT Information and Communication Technology

IGO Intergovernmental Organisation

II Information Infrastructure

ILT Inspectie Leefomgeving en Transport. English: Dutch Human Environment and Transport Inspectorate

IMO International Maritime Organization

IoT Internet of Things

IPIC International Physical Internet Conference

IS Information System

ISO International Organisation for Standardization

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ITF International Transport Forum

LCL Less than Container Load

LSP Logistics Services Provider

Modulushca Modular Logistics Units in Shared Co-modal Networks

NAFTA North American Free Trade Agreement

NFC Near-Field Communication

NVWA Nederlandse Voedsel- en Warenautoriteit. English: Netherlands Food and

Consumer Product Safety Authority

OECD Organization for Economic Co-operation and Development

PCS Port Community System

PI Physical Internet

π PI, Physical Internet

RTA Regional Trade Agreement

SBR Standard Business Reporting

SC Supply Chain

SCM Supply Chain Management

SOA Service Oriented Architecture

TAE Trader At Exit

UCC Union Customs Code

UN/CEFACT United Nations Centre for Trade Facilitation and Electronic Business

UNCTAD United Nations Conference on Trade and Development

WCO World Customs Organization

WEF World Economic Forum

WTO World Trade Organization

XBRL Extensible Business Reporting Language

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GLOSSARY OF TERMS

Term Definition

Buyer The party to whom goods or services are sold as stipulated in a Sales Order Contract (UN/CEFACT, 2018).

Cargo/Freight A collection of physical materials and/or transport units stipulated in a Transport Service Contract (UN/CEFACT, 2018).

Consignee The party receiving a consignment of goods as stipulated in a Transport Service Contract (UN/CEFACT, 2018).

Consignment

A Transport Service Contract between a Transport service buyer and a Transport service provider to transport cargo/freight (packaged or unpackaged) from a specified node in the logistics network to another specified node in the network (UN/CEFACT, 2018).

Consignor The party consigning goods as stipulated in a Transport Service Contract (UN/CEFACT, 2018).

Consolidation Consolidation is the act of combining two or more shipments in a truck or container (Flexport, 2020).

Deconsolidation Deconsolidation is the act of separating out LCL2 shipments to prepare them for final delivery (Flexport, 2020).

Goods A collection of physical materials and/or items stipulated in a Sales _{Order Contract (UN/CEFACT, 2018).}

Intermodal transport

Movement of goods (in one and the same loading unit or a vehicle) by successive modes of transport without handling of the goods themselves when changing modes (OECD, 2020a).

Seller The party selling goods or services as stipulated in a Sales Order Contract (UN/CEFACT, 2018).

Shipment

A collection of Goods Bought/Sold between a Buyer/Seller in a single transaction and despatched together with the intent of being delivered together (UN/CEFACT, 2018).

Supplier The party who produces the goods or delivers the services as stipulated in the Sales Order Contract (UN/CEFACT, 2018).

Synchromodality

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1. INTRODUCTION

International trade is the driver of economies all over the globe. As an indicator of the volume of international trade, the value of global exports has more than tripled over the last two decades, from US$ 6.45 trillion in 2000 to US$ 19.45 trillion in 2018 (UNCTAD, 2019). This can, to a large extent, be attributed to the significant reduction in transportation costs over the last decades. Nowadays, it is often cheaper to produce products on one side of the globe and ship them to the market where they will be sold, than to produce them in the same market as where they will be sold. Reductions in global transportation costs are mainly the result of the introduction of the world-standard twenty feet intermodal shipping container that led to vast increases in efficiency of logistics systems (Montreuil, 2011).

The main problem with current logistics systems relates to their fragmentation, leading to a situation in which goods flow through disconnected networks (Sarraj et al., 2014). In Europe alone, €160 billion is lost every year due to such inefficiencies (ALICE, 2020). The ground-breaking concept of the Physical Internet (PI) is aimed at tackling this “global sustainability grand challenge” by strongly increasing the efficiency of freight transport (Pan et al., 2014). It intends to do this by intensifying collaborative and connected business models, in which the PI acts as an “open global logistics system” (Montreuil et al., 2013, p. 152). Combined with the substantial growth of e-commerce, the PI is expected to further increase levels of international trade. An in-depth description and definition of the PI concept is presented in Section 2.2 and Appendix A.

Another driver of international trade is the proliferation of regional trade agreements (RTAs) such as NAFTA, APEC or the EU. It is estimated that more than 50 percent of global international trade volumes are covered by RTAs (OECD, 2020b). The EU can be seen as a special kind of RTA; it is a so-called customs union, which means that no customs duties are paid at the borders between EU countries. Duties on goods from outside the EU are paid when they first enter the territory of the Union, after which they can freely move within the EU Customs Union (under customs supervision) (EC, 2020b). It is not just intra-EU trade, however, that is an important source of international flows of goods. The Netherlands, for example, obtained over half of its total imports from outside the EU27 in 2018 (based on WCO data).

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e-commerce flows further complicate this challenging role, especially given the static or decreasing resources of customs authorities globally (Holloway, 2009). As argued, the PI is expected to contribute to a further increase of the complexity and volumes of international trade and is therefore expected to have a significant impact on the operations of customs authorities.

The academic development of the PI vision has so far not taken the interests of government agencies into account, thereby showing a lack of multidisciplinary collaboration that is perceived to be crucial to “really shape the vision” and “give it flesh” (Montreuil, 2011, p. 86). The current state of development of the PI concept would have severe consequences for international logistics if it were to be implemented tomorrow. These consequences relate to the resources of customs authorities, but more importantly to disruptions in logistics processes (Kooij, 2020, personal communication, February 27), which would thereby negate the efficiency increases the concept aims to achieve.

As the PI is expected to open up global shipping to virtually anyone3_{, it will make it more complicated}

for customs authorities to assess the reliability of new (unknown) shippers. In addition to that, administrative deconsolidation of shipments4_{will increase the number of shipments that needs to be}

supervised by customs authorities. In combination with Brexit, the growth of e-commerce and economic growth in general, this will lead to a significant increase in the number of declarations (i.e. shipments) to be processed by customs authorities. IBM Netherlands (2020) estimates that above developments will lead to a growth in import and export declarations from 160 million in 2019 to 850 million in 2025. In addition to that, new EU to e-commerce legislation, taking effect on July 1st_{2021 is}

expected to increase the number of declarations by a factor of 15-205_{(Voorspuij, 2020a, personal}

communication, November 27). The current systems of the Dutch Customs Administration (DNL) are improperly designed to handle such volumes and will likely continuously trigger alarms for physical inspections (Kooij and Pastoor, 2020, personal communication, June 11), which would in turn severely disrupt logistics chains. In addition to the above, a crucial data element (i.e. the route of a shipment) is expected to become more clouded in the PI. The route is not known and fixed in advance in the PI, as it can change over the course of the journey from origin to destination as a result of the autonomy of the concept (see Section 2.2.1).

3_{Scale economies are no longer needed.}

4_{The PI is expected to lead to administrative deconsolidation of shipments through the introduction of modular π-containers.}

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In response to these continuously growing volumes of trade, further automation seems an essential component of the solution, which is also recognised by Rukanova et al. (in press). In this context, DNL

recognises the need for employees with different backgrounds. Further automation will require e.g. data analysts/scientists that are currently only scarcely present in the organisation.

This research aims to explore how the PI will impact the operations of DNL and identify requirements to the PI from the perspective of DNL. Based on that, it proposes a first conceptual system design for DNL to deal with the challenges of the PI. It will be a first step in filling the gap in the academic literature, by being the first work recognising and addressing the importance of customs authorities in the PI.

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2. THEORETICAL FRAMEWORK

Although being a novel concept, attention for the PI has increased in academia and industry. The number of publications on the PI has increased considerably after the first edition of the “International Physical Internet Conference” (IPIC), organised by CIRRELT6_{in Quebec City, Canada in 2014}

(Treiblmaier et al., 2016). Despite the increase, the literature base is still relatively limited compared with other concepts in the realm of logistics, supply chain management, and operations management. Nevertheless, this chapter explores the state-of-the-art of PI research by addressing six questions.

2.1 Why are major changes in logistics systems necessary?

In 2018, transportation functions represented almost 10 percent of the US GDP at US$ 1.850 billion (US Department of Commerce, 2019). Similar figures are found for Europe, where over 3,600 billion tonne-kilometres of freight was transported in 2019 (EEA, 2019). These numbers will increase in the future, as global transport volumes are expected to triple by 2050 (ITF, 2019). Although being an important part of the economy, the industry suffers from inefficiencies resulting from low capacity utilisation of trucks and containers.

Above numbers indicate the importance of the freight transportation industry. The size of the industry also makes it a significant contributor to climate change, however. The industry represents a vast source of both greenhouse gas (GHG) emissions and pollution. This can be attributed to the fact that the large majority of continental freight is transported via truck, as displayed in Figure 2.1below. The preference for trucks mainly relates to its benefits in terms of flexibility. Trucks emit significantly more GHGs per container than e.g. trains or barges, however. Overall, freight transportation already accounts for nearly 15 percent of GHG emissions in developed countries and this level is increasing (Montreuil et al., 2010).

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Figure 2.1: US freight transportation by transport mode (data from US Department of Transportation, 2019)

2.2 What is the Physical Internet?

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To respond to the “worldwide grand challenge” of current logistics systems, the PI vision was introduced in 2010, which can be defined as an “open global logistics system founded on physical, digital, and operational interconnectivity through encapsulation, interfaces and protocols” (Montreuil

et al., 2013, p. 152). It is aimed at addressing “the way in which physical objects are currently

transported, handled, stored, realised, supplied and used throughout the world” (Montreuil, 2011, p. 71). According to Montreuil, the current state is not sustainable from economic, environmental and societal perspectives.

The main economic goal of the PI is to significantly increase the efficiency and productivity in global logistics, production and transportation networks. Environmentally, the aim is to reduce energy consumption globally and with that, reduce direct and indirect pollution. From a societal perspective, the goal is to increase the quality of life of workers in the logistics, production and transportation industries (Montreuil, 2011).

7_{This section solely discusses the essentials of the PI concept, as a basic understanding of the concept is assumed. An}

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As aforementioned, the key objective of the PI is to improve efficiency of freight transport (Pan et al., 2014). In the current state, average truck loads are low, and the frequency of empty trips is high, among others due to the focus on lean production and -management. In the EU, 25 percent of trips is empty, while non-empty trucks, on average, only use 56 percent of their weight capacity (Montreuil

et al., 2012). Global transport efficacy has been estimated to be lower than 10 percent (Ballot and

Fontane, 2008). Low performance in these areas means that more resources are required to move the same amount of freight (Franklin and Spinler, 2011). One solution to this is an intensification of collaborative and connected business models, which will be enabled by the PI. The European CO3 project8_{has shown how increased collaboration can lead to a reduction of GHG emissions and costs}

(ALICE, 2020). Consolidating, balancing and synchronising loads of Nestlé and PepsiCo led to cost savings of 10-15 percent and similar reductions in CO2 emissions. A different case showed a

collaboration between P&G and Tupperware, resulting in 150,000 truck kilometres saved, improved cube and weight fill from 55 to 85 percent and the attainment of 17 percent cost savings (ALICE, 2020). Other benefits found in prior studies are presented in Section 2.3 and Appendix B.

2.2.1 Pillars of the PI

The PI vision can be said to have four key pillars (Szirbik, 2020a, personal communication, September 28), as depicted in Figure 2.2 below:

- A characteristic of the PI is to have full automation in place by the year 2050, meaning all physical operations are carried out by robots while the informational flow is handled by means of software agents.

- Modularity: in practice, this means that the goods of a shipment will be encapsulated in a

“π-container” of an appropriate size so as to minimise the amount of ‘air’ that is shipped. The topic of π-containers will be discussed below.

- All shipments will flow through the PI autonomously, making its own decisions in terms of routing using real-time information on e.g. the availability or price of the different arcs and nodes of the network.

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2.2.2 Key components of the PI

Two key components of the PI are “π-hubs” and “π-containers”. The PI is aimed at enabling a collaborative, highly distributed and leveraged logistics and distribution system (Montreuil et al., 2010). In this open system, shipments travel to their destinations via intermediate hubs in the network. In each of these hubs, shipments have the possibility to be reallocated to new carriers, e.g. in the case of disruption on the initially planned route, or in the case of cheaper alternatives (Pan et

al., 2014). A criticism on the PI vision is that transit through several of these hubs may require more

handling operations, compared with direct shipments (Sarraj et al., 2014). This perceived drawback, however, will be overcome by the introduction of new, standardised and modular π-containers.

These smart “π-containers” have standardised interfaces for handling and communication and their preliminary designs focus on ease of loading, unloading, handling, storing, transporting, sealing, snapping and interlocking with each other (Montreuil et al., 2013). The containers are termed “smart” because they are not only protecting the goods encapsulated within them, but are also intelligent objects with a logistics purpose9_{(i.e. having communication and decision capabilities) (Sallez et al.,}

2016). To allow for efficient routing across the open logistics system, a link needs to be established between the physical flow of π-containers and the informational flow about them. To that end, each

9_{The UN/CEFACT Smart Container project has delivered a set of standards that may be used for smart PI containers.}

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smart π-container has a unique worldwide identifier and a smart tag to act as its representing agent. This smart tag will help ensuring identification, integrity, routing, conditioning, monitoring, traceability, and security of each π-container (Montreuil, 2011). The “Modulushca”10 _{project was set}

up by logistics stakeholders from industry and academia across Europe and Canada to specify characteristics and potential sizes of these new containers.

2.3 What are the potential benefits of the PI?

Even though the PI is a novel concept and the majority of its research projects is of an exploratory and conceptual nature, there have also been several projects with a more empirical focus. Important to note is that there exists a misconception that there is a “binary state in which the PI either exists or not” (Treiblmaier et al., 2016, p. 3). Development and implementation are likely to follow a more gradual process. Prior projects and simulations have shown that significant gains can be achieved through applications of (particular principles of) the PI in all three targeted areas (a comprehensive overview of the findings by paper can be found in Appendix B):

- Economic: the general finding is that applications of the PI result in significant cost reductions,

coming from a range of different factors including reductions in total transport time (Sarraj et

al., 2014) and distance (Hakimi et al., 2012).

- Environment: prior research has found significant reductions in GHG emissions as a result of

PI applications, which can largely be attributed to reductions in fuel use (Naccache et al., 2014) as a result of lower travelled distances (Hakimi et al., 2012).

- Society: examples of benefits in this area are improvements to the precarious working

conditions of truck drivers, leading to reductions in driver turnover (Faure et al., 2014). Furthermore, society in general is less impacted by freight transportation through less congestion, reduced noise pollution and increased road safety (Franklin and Spinler, 2011).

2.4 What is lacking in current PI research?

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In terms of research directions, one major stakeholder has not been recognised so far. Although “legislators” are mentioned in a general sense in Crainic and Montreuil (2016), a group of “legal” stakeholders that is of particular importance in the PI are customs authorities. This stakeholder group is crucial in the current world of global trade and has been ignored in PI research so far. At IPIC 2019, customs representatives were shocked by the lack of interest in the potential impacts of the PI for customs authorities (Szirbik, 2020b, personal communication, May 15th). Nearly all presentations at IPIC 2019 omitted customs authorities as a stakeholder in the flows of goods of the future (Pastoor and Kooij, 2020). In response to this, the Dutch Tax and Customs Administration aired serious concerns, as the PI would deal a devastating blow to the organisation’s resources if it were to be introduced “tomorrow”. This would in turn lead to disruptions in logistics chains. A further in-depth discussion of the importance of customs authorities in relation to the PI is presented in Section 2.6.

2.5 Who are important stakeholders in relation to the PI?

A vast set of stakeholders can be identified for logistics networks in general, and for a PI setting in particular. This section discusses the most important stakeholders, in addition to customs authorities, in the context of a PI-enabled logistics future.

2.5.1 Customers and suppliers

Whereas little change is expected in terms of the roles of customers (i.e. eventual consumers/users of the products) and suppliers (i.e. parties providing the products that are shipped), they are both arguably the biggest winners of the evolution and gradual implementation of the PI. Customers will have easier access to better and cheaper products, contributing to a better health and quality of life. At the same time, the PI allows suppliers to extend their market reach, as scale economies are no longer required for global shipping. The main benefit for suppliers relates to attaining cost savings, both in the short and long term. In addition to that, the environmental and societal benefits that result from the PI can boost the supplier’s image.

2.5.2 π-hub owners and operators

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transhipment processes (ALICE, 2020), which will need to be provided by the PI and especially by the implementation of π-containers. In the current state, hubs (i.e. transit nodes) already play an important role in logistics networks. Their importance is expected to further increase with the increase in international trade and the expected increase in intermodal transport11_{as a result of the PI.}

2.5.3 π-container owners

Currently, most intermodal shipping containers are owned by a few large ocean carriers (e.g. Maersk, MSC, Cosco, Hapag-Lloyd), with the rest being accounted for by container leasing companies (Song and Dong, 2015). In the current state of development, it is still debatable which parties should own the smart containers in the PI (Sarraj et al., 2014). The PI is expected to have a larger number of container owners, mainly due to the fact that π-containers will likely exist in smaller sizes, making them easier to own and operate. Regardless of who will be responsible for the π-containers, their owners will be responsible for maintenance to safeguard good container condition and thereby ensure availability. Availability is crucial in the PI as the containers will autonomously find their shipments. A high availability significantly increases the time in which the containers are actively used (and thereby generate revenues for their owners).

2.5.4 π-transporters

Transportation companies are the owners of so-called transporters” that are part of the “π-movers”. According to Montreuil et al. (2010), these movers will carry out operations such as transporting, conveying, handling, lifting and manipulating the π-containers. π-transporters consist of “π-vehicles” and “π-carriers”, which are vehicles and carriers that are “specifically designed for enabling easy, secure and efficient moving of π-containers” (Montreuil et al., 2010, p. 312). Today, transportation companies are responsible for performing transport and for the loading and offloading of shipments. Just as in the current state, transportation companies in the PI will aim to maximise their profits by minimising costs through the maximisation of asset utilisation.

2.5.5 Other stakeholders

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2.6 Why are customs authorities important in the PI?

Whereas for the functioning of the PI, contents of shipments are to a large extent irrelevant (Montreuil

et al., 2010), customs authorities are arguably only interested in the contents of PI shipments to

perform their function of collecting duties and taxes. Generally speaking, customs authorities are responsible for “the enforcement of the fiscal integrity, security and safety of cross-border movements of goods” (Heijmann et al., 2020, p. 4). An ongoing challenge for customs authorities is balancing trade facilitation with border security and control, while at the same time facing increased trade volumes and static or even decreasing resources (Holloway, 2009).

2.6.1 The Dutch Tax and Customs Administration

In this research, the focus will be on the Dutch Tax and Customs Administration (from now referred to as “DNL”). DNL supervises the fiscal integrity and safety of the flows of goods that originate from or go outside the EU via the Netherlands. It plays a crucial role in the EU-context, as nowadays approximately one-third of all goods entering and leaving the EU flows through the Netherlands (DNL, 2019). This can mainly be attributed to the global importance of the port of Rotterdam as the 10th

-largest port in the world in terms of container shipping (Hong Kong Marine Department, 2020). While DNL’s main goal is to supervise the fiscal integrity and safety of goods, it is also expected to contribute to the competitive power of the Netherlands and the EU, by supporting and stimulating measures that facilitate trade (DNL, 2014). In that sense, Dutch Customs thus performs a dual role.

2.6.2 The importance of ICT in customs supervision

To tackle the ongoing challenge of the dual role of customs authorities, ICT is recognised as being a “critical strategic measure for modern customs organisations to manage the complexities implicit in today’s global trading environment” (Lewis, 2009, p. 5). The importance of automation of customs procedures has been emphasised by several global intergovernmental organisations (IGOs) like the WCO12_{, the WTO}13_{, the World Bank, the OECD}14_{, and the UNCTAD}15_{(Holloway, 2009, p. 15). These}

IGOs argue that automation can increase the speed of customs clearance, improve the transparency and predictability of customs procedures, and significantly reduce the number of physical examinations of goods (Holloway, 2009), to thereby intervene in logistical flows less and in a less disruptive way.

12_{World Customs Organization} 13_{World Trade Organization}

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DNL has also recognised the potential of innovative solutions and is implementing these in conjunction with its ambition of having 100 percent supervision over all vehicles passing the borders and its ground-breaking concept of “layered supervision and enforcement” (DNL, 2019). In this respect, several initiatives have been set up to increase the efficiency and effectiveness of their supervision. For example, nuclear scanning and detection gates have been moved toward container terminals at ports, and a scanner has been installed at the Port of Rotterdam that can perform scans of trains while they are in transit. In addition, “virtual nets” have been developed that allow Dutch Customs to see which ships and planes are in Dutch territory at any given moment (DNL, 2014). DNL is also collaborating with the EU business community to develop a large range of modern scanning and sensor techniques that can be combined into one “checkpoint”. A similar concept called the “Joint Inspection Centre” already exists at Schiphol Airport and allows for a one-stop shop for all inspection authorities, including DNL, NVWA16_{, and ILT}17_.

2.6.3 Vision “Pushing Boundaries”

The layered concept that forms the core of the “Pushing Boundaries”-vision of DNL, aims at making the operations of trusted companies subject to less (and less disruptive) interventions, while inspections are becoming more likely with unknown parties. Its goal is thereby to reduce the blue area in Figure 2.3 (on page 13) representing unknown and/or unreliable traders. In this blue area, frequent inspections are carried out, both physically and in documentation. These processes are highly resource intensive. It is often difficult for customs authorities to track who the true sender of a shipment is, making it complex to assess the trustworthiness of shipments. As the PI is expected to open up global shipping to virtually every individual and organisation, there is a risk of the blue area growing. This, in turn, poses a risk for customs authorities, especially given their limited resources.

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3. RESEARCH QUESTIONS

As customs authorities have so far not been recognised as a stakeholder in the PI, this research aims to take a first step in filling the gap in the literature. This is done by exploring how the PI will impact the operations of customs authorities. Furthermore, the research will look at what the emerging requirements to the PI are from the perspective of customs authorities. The focus area of the research is the Dutch Tax and Customs Administration (DNL), which has been one of the first customs authorities to identify a potential impact of the PI on their operations; it strongly believes that future PI research should take their interests into account. This research aims to answer to that call for action and will explore the ways in which the PI is expected to have an impact on their operations. Based on that, a conceptual system design is proposed that allows Dutch Customs to deal with the impacts of the PI. To that end, the following research question is formulated:

“How will the PI impact the operations of the Dutch Tax and Customs Administration and how can the Administration operate in the context of a global, open logistics network like the PI?”

To answer this question, different areas will be explored by means of several sub-questions:

1. What are the relevant terms that are used to describe (different concepts of) the PI in the context of customs processes and organisation?

2. What is the state-of-the-art of PI research in terms of the acknowledgement of customs authorities as a crucial stakeholder?

3. What are the emerging requirements to the PI from the perspective of the Dutch Tax and Customs Administration?

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4. METHODOLOGY

This chapter presents the methods that were applied in this study. It firstly broadly describes the context of the research and the approach taken by the researcher. After that, by means of “three phases of research” (Wieringa, 2009), a further elaboration on the instruments, tools, and methods is given. The study was deliberately designed as relatively unstructured, since it involves an exploratory case study at the Dutch Customs and Tax Administration (DNL). This in line with Stake’s (1995) reasoning that the design of case studies is flexible and allows researchers to make changes, even after proceeding from the design of the research towards conducting the research. The research emerged and unfolded into more detail after the start of the project and can therefore be classified as an “unfolding case study” (Punch, 2000, p. 15).

As aforementioned, this paper uses a case study to explore the potential impacts of the PI in the context of customs authorities. The use of an exploratory case study is suitable for this type of research as the current PI literature base has never considered customs authorities or other regulatory inspection agencies. Furthermore, this type of research is particularly relevant in dealing with ‘how’ questions (Yin, 2003). To that extent, the case study firstly analyses how the PI might impact the operations of customs authorities, after which potential mitigations to these impacts are explored by means of a proposal for a future design (i.e. how can customs authorities operate in the context of a global and open logistics network like the PI?).

4.1 Research context and approach

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DSR originates from the fields of engineering and IS and is rather new as an approach in social sciences. The “formal” acceptance in the field of operations management is as recent as 2016 but is still subject to opposing opinions. To that end, Hevner (2007) proposed three “cycles” (see Figure 4.1 below) as a guideline for conducting high-quality DSR:

- Good DSR projects start by identifying problems in an application environment. This relevance cycle initiates the design exercise by providing the context of the problem to be addressed. - The rigor cycle provides existing theories and methods that are relevant for the design

exercise.

- The ‘heart’ of the DS exercise is carried out in the design cycle, in which design alternatives are generated and evaluated, based on inputs provided by the other two cycles.

Figure 4.1: Design Science Research Cycles(Hevner, 2007, p. 2)

Wieringa (2009), on the other hand, takes the “regulative cycle”18_{as a starting point for conducting}

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Figure 4.2: The regulative cycle (Wieringa, 2009)

Table 4.1: Summary of proposed approach

Phase Sub-question

addressed Main instruments employed

Problem investigation 1

Literature review, multiple instruments resulting from “insider research” (e.g. interviews, regular conversations, reports/memos)

2 Literature review

System design 4

Literature review, multiple instruments resulting from “insider research” (e.g. interviews, regular conversations, reports/memos)

Design validation 4 Expert validation

4.2 Problem investigation

The aim of the problem investigation-phase is describing the problem, explaining it and, potentially, predicting what happens if no actions are taken. According to a classification by Wieringa (2009), the problem investigation in the context of this study is best described as a “goal-driven” or “solution-driven” investigation. The first considers a situation in which no problem is (yet) experienced, but there are nevertheless reasons to change the world in agreement with particular “goals”. The latter considers the “search for new technology that can solve problems not yet experienced” (Wieringa, 2009, p. 3). As the study does not aim at searching new technology per se, it cannot unambiguously be termed a solution-driven investigation. However, as the researcher carries out the study in a proactive manner (“before it will be too late”), it can be argued that the investigation seeks to find solutions to problems that are not yet experienced but are likely to be experienced in the future.

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primary (e.g. interviews, observations) and secondary data (e.g. review of literature and documents/data).

The theoretical framework introduced in Chapter 2 was the starting point for the problem investigation. Sub-questions 1 and 2 explore the current state of the PI in terms of both academic research and contributions originating from industry and are mainly addressed by means of a thorough review of the literature. The system design, related to the third sub-question, was also partly based on a review of existing literature. This is in line with Hevner’s (2007) proposed “rigor cycle” (see Figure 4.1 above).

The ‘practical’ exploration is conducted by means of a single case study at DNL. A single case study is considered appropriate as it is an emergent method that draws from multiple data types and sources over time. Although investigating a single case may be seen as a limitation (Klievink et al., 2012), DNL is considered to be a leading customs authority in terms of innovative enforcement solutions. Therefore, the results can serve as the basis for further research. The researcher has operated as an intern at DNL for the duration of the study to tap into the knowledge that exists within and about DNL. For that reason, the researcher can be said to have taken an “actor-observer”-role in the study (Gioia

et al., 1994). This role has allowed the researcher to get as close to reality as possible and by that

provide information, meanings and perspectives that are unobtainable otherwise (Evered and Louis, 1981).

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All interviews and other forms of empirical data collection were held in Dutch, as both the researcher and the informants at DNL were native Dutch speakers. To assure the quality of the collected data, interviews were recorded if permission was given. To assure data quality resulting from the less explicit forms of data collection, the researcher took “field notes”. Combined with notes taken during interviews and other conversations, these field notes were the main sources of primary data in this study. Secondary data (e.g. internal memos, reports) have been used to further cross-check interpretations that resulted from the primary data sources, thereby acting as a form of triangulation.

4.3 System design

Based on the researcher’s role as “actor-observer”, an assessment was made as to which processes are crucial in the current state, and which of these will be impacted by the PI and how. This formed the basis of the identification of requirements that are placed on the PI from the perspective of DNL. These requirements are critical for DNL to be able to fulfil their role in the context of the PI. The requirements formed the basis of the design exercise of this study and were used to conduct a second review of the literature to design the proposed system.

4.4 Design validation

The design exercise and its validation go hand in hand and should be seen as a process of continuous interactions and feedback loops (Buede and Miller, 2016). Formally, Wieringa specifies design validation as “a knowledge task in which we ask whether the specified design, if implemented correctly, would indeed bring stakeholders closer to their goals” (2009, p. 4). Within design validation, three concepts are important (Wieringa, 2009):

1. Internal validity deals with the content of the solution design: will it, if implemented, satisfy the requirements identified in the problem investigation phase?

2. Trade-offs: how can slightly different designs satisfy the requirements in the same context? 3. External validity takes the designed solution and checks whether it would also satisfy criteria

in different contexts (e.g. other customs authorities). It could thus also be perceived as a first check for generalisability.

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5. CURRENT STATE

This chapter describes the current state of supply chains, which is characterised by poor data and information exchange, leading to problems for customs authorities. It starts by presenting the causes of poor SC visibility and transparency, after which the need for improvement is laid out. Subsequently, the dependency of customs authorities on reliable trade data is explained, stressing the importance of the seller in information provision. Then, current initiatives to improve upon the current state are briefly touched upon. Finally, a recap is given with regard to the expected impact of the PI on customs supervision.

5.1 Current state of information exchange

Modern developments in the realm of physical infrastructures have significantly improved the efficiency of international trade and shipping. The PI is another, new initiative aimed at further optimising flows of goods at a global level. Efficient movements of goods are not only dependent on physical infrastructures, however. Jensen et al. (2014) argue that efficient information infrastructures (IIs) are lacking in current international trade SCs. “Middle parties in the supply chain have created an industry so complex that the buyers and sellers often have no other reasonable choice but to place the transport and logistics part of their transaction in the hands of ‘experts’” (Hesketh, 2010, p. 4). These middle parties deal with a lot of data and information, and frequently choose to shelter them from others, except from those actors that are directly involved in their commercial operations (Rukanova et al., 2020). All have their own arguments to mask particular information (see e.g. van Stijn et al. (2011) and Klievink et al. (2012)). Jensen and Tan report that that several studies have confirmed that “the quality of data provided to authorities is poor, misleading, and sometimes even fraudulent” (2015, p. 493).

The actors that do share information with other parties, generally do this in a way that involves manual retyping and copying of information, as each actor tends to have its own IS (Jensen et al., 2014; Jensen and Tan, 2015). As a consequence, data inaccuracy is estimated to be as high as 50 percent in business-to-government (B2G) interactions (Jensen and Tan, 2015). Regardless of the major financial, safety, and planning risks this creates, some organisations see visibility and transparency as a threat to their business operations. The business model of a large group of LSPs is in fact based on the inefficiency in the international trade (Klievink et al., 2012; Jensen et al., 2014). As a result, a fragmented information landscape exists in which nobody has the complete picture of the process (Jensen et al., 2014; Hu et

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5.1.1 Poor information exchange in supply chain practice

In essence only the seller, the actor “who packed the box”, knows the true contents. Subsequent handlers of the goods can solely provide statements such as “said to contain” and “said to weigh”. They do this for the sole purpose of protecting themselves against liability in the case of theft of or damage to the goods (Hu et al., 2016). In the current state, however, those (i.e. carriers and importers) are the actors required to make legal declarations about goods they have never seen themselves (van Stijn et al., 2011). Such parties do not always have a business interest to hold all required data, nor can they be held responsible for them (Heijmann et al., 2020). The administrative burden thus seems to be placed on the wrong actors. This can partly be attributed to current legal frameworks in place (Hesketh, 2010; van Stijn et al., 2011; Rukanova et al., 2020). The Hague-Visby Rules19_{, for example,}

concentrate on the provision of a very limited information set by the seller, leading to a “dance” around the description, value, and liability of goods (Hesketh, 2010, p. 8). As a consequence, the seller is shielded from taking full responsibility for sending goods in the SC. The legal frameworks in the air freight sector are radically different. After 9/11, more emphasis has been placed on the security of international air freight SCs. This has, in turn, raised questions about why these security and data management standards do not apply to maritime cargo (Hesketh, 2010).

5.2 Commercial need for accurate data and information

The WCO’s Revised Kyoto Convention20_{recognised that to make (operational) decisions, both customs}

authorities and commercial parties need information, and that this information originates from the commercial sector itself (Hesketh, 2009). It is in all the involved parties’ interests to have access to accurate information. For example, financial institutions require accurate data to issue letters of credit, sea carriers require it to prepare balanced stowage plans, and consignees require it for planning purposes. “Data deficiencies and gaps, together with an outdated paper trail are creating financial, safety and planning risks” (van Stijn et al., 2011, p. 7).

Error-prone information, missing communication, and a lack of coordination due to a lack of accurate logistic information leads to delays, because actors cannot proceed with the next steps in the logistics process (Jensen et al., 2014). This can have serious consequences for the trade in time-sensitive goods such as fresh fruits and vegetables, as their quality is directly dependent on the transport lead time. Overbeek et al. (2011) recognise that businesses are actively investing in dealing with complexity and improving visibility in SCs, to realise reliable and secure trade environments. For all of these

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investments to generate value, reliable trade data is required. “Without timely and accurate data about the goods, the people involved, the payments and the integrity of the logistics, the risk of something going wrong increases, effective planning is inhibited and confidence decreases (Christopher and Lee, 2004)” (van Stijn et al., 2011, p. 6).

5.3 Customs’ need for accurate data and information

International trade is a key example of a sector in which business- and government data sharing are tightly intertwined. As customs authorities are, in the capacity of governments, responsible for supervising and controlling the flows of goods, “any delay due to customs processes can lead to a direct disruption of the supply chain operations with related costs for the businesses involved” (Rukanova et al., 2020, p. 3). Customs and other cross-border inspection agencies analyse information that businesses are required to submit, to assess the risks related to flows of goods. This requires “accurate and timely data about the goods, about the parties involved, and about the location and security of the consignment” (Klievink et al., 2012, p. 12). In the current state, the authorities must rely on data originating from import and export declarations. As argued above, these declarations frequently contain inaccurate information, thereby making them unreliable for customs supervision purposes.

Outsourcing, cargo consolidation and multi-modal transport chains “have allowed the identity of the true seller/sender to be clouded and contractual terms to be complicated” (Klievink et al., 2012, p. 1). Due to the vast number of intermediaries involved in a typical international trade SC, approximately 60 percent of vessel manifest information is classified as ‘agent-to-agent’ (Hesketh, 2010), making it unfit for risk assessment purposes by authorities. This is caused by the fact that data elements key to risk assessment (e.g. the ‘true’ seller/producer and buyer) cannot be derived from these documents. In practice, customs authorities do not have access to all SC information, so they must manage their activities based on second-hand information that is filtered, altered, and thus likely to be inaccurate (Hesketh, 2010). In other words, data that is currently available in global logistics networks does not fit the SC visibility requirements of both commercial and government actors (Klievink et al., 2012). As argued by Hesketh, it is crucial for authorities to have “accurate upstream information received as

early as possible along the international trade logistics chain” (2009, p. 31) for their decisions with

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5.4 The crucial role of the seller

As argued above, the information requirements of the many actors involved in logistics chains are very different. However, a key source of information is centred on the seller. It is generally agreed that the consignor is the primary source of the data that is required to meet regulatory requirements (e.g. Hesketh, 2010; Overbeek et al., 2011; Klievink et al., 2012). The definitions of the terms “seller” and “consignor” are crucial here, however, as they may wrongfully be regarded as synonyms (see glossary of terms on page X and Figure 5.1 below). Whereas the (multiple) consignors involved in the physical movements of the goods do ‘see’ the transport units (i.e. containers, pallets, boxes), they do not necessarily know which goods are encapsulated in those transport units.

Figure 5.1: Key Actors/Roles associated with the four main Business Areas (UN/CEFACT, 2018)

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5.5 Initiatives for improvement

Whereas from a legal perspective, authorities currently may have “no other choice”, there are several initiatives aimed at improving the poor B2B and B2G information exchange. The initiatives are all centred around improving SC visibility and transparency. This section explores a couple of these.

5.5.1 Single Window

The national Single Window (see Figure 5.2 below) is a concept that facilitates business processes and data exchange for national export and import (van Stijn et al., 2011). Single Windows allow commercial parties to lodge standardised information into a single point, in order to fulfil all regulatory requirements. Various border enforcement authorities then send one reply message and reuse the information as they require (Heijmann et al., 2020). The EC recently proposed an EU-wide Single Window initiative, which will “enhance cooperation and coordination between different authorities, and will support the automatic verification of non-customs formalities for goods entering or leaving the EU” (EC, 2020c).

Figure 5.2: High Level Concept of the National Single Window (Niculescu and Minea, 2016)

5.5.2 The data pipeline and piggybacking

A concept that is frequently mentioned in the context of improving SC visibility is the data pipeline. Core of the concept is that data is obtained from the source, starting at the consignment completion point21_{(CCP) or even before that. As the goods physically flow through the logistics chain, data is}

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entails the re-use of available business data in international SCs for purposes different than those for which they were originally intended (Baida et al., 2008; Rukanova et al., 2011; Tan et al., 2011). Within the data pipeline concept, piggybacking means a fundamental shift from a document perspective towards a data perspective. The focus is no longer on the documents, but rather on the data that is contained within them. This will also lead to a change from a situation in which companies ‘push’ their data to the authorities, towards a situation in which authorities can ‘pull’ the data from the existing ISs of companies that are interlinked via the data pipeline (Tan et al., 2011).

5.5.3 Standards

Key to all initiatives are standards in the areas of data and information exchange. An example of a set of standards that is widely used for data sharing in international SCs is “EPC Global” by GS122_{. These}

standards are open and vendor-neutral (Overbeek et al., 2011), meaning they work anywhere in the world, on heterogeneous hardware and software platforms. Closely related to these standards is the Dutch SBR Program23_{, the national standard for the digital exchange of business reports (SBR NL,}

2020). It is aimed at reducing the administrative and regulatory burden for commercial parties and public authorities, respectively. The program is “based on the Extensible Business Reporting Language (XBRL), which is an XML24_{-based language for formatting business information in such a way that it}

can be read across different software applications.” (Overbeek et al., 2011, p. 12).

5.6 The expected impact of the PI on customs supervision

The case study analysis has identified several ways in which the PI is expected to impact customs supervision:

1. The PI is expected to open up global shipping to virtually anyone, which will make it more complicated for DNL to assess the reliability of shippers (see Chapter 1).

2. The introduction of new and modular π-containers is expected to lead to administrative deconsolidation25_{of shipments, thereby leading to a spike in the number of separate}

shipments and declarations to be supervised by customs authorities (see Chapter 1 and Section 2.2.1).

3. As a result of the autonomy of the PI vision, the route of a shipment will not be known and fixed in advance, as it can change during the journey from origin to destination (see Section

22_{GS1 is an independent, not-for-profit organisation that develops international standards for identification, collection and}

sharing of data.

23_{Abbreviation of: Standard Business Reporting} 24_{Extensible Markup Language}

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2.2.1). The route of a shipment is currently an important variable in the risk assessment process of DNL26_.

4. The overall response time of customs authorities is expected to decrease, as in the PI, decisions are postponed as much as possible to be able to incorporate real-time data and information. This will not only lead to challenges in terms of risk assessment, but also in terms of efficiently organising the physical inspection that may result from the risk assessment.

It can be argued that all four of the above-mentioned impacts revolve around increased uncertainty of a growing volume of shipments. This will make the dual role of customs authorities even more challenging than it currently is. To prevent customs from becoming a bottleneck in the future reality of the PI, change is necessary. What appeared from the case study analysis is that DNL needs more information that is of higher quality, received at an earlier stage in the logistics chain to increase the quality of the risk assessment process and to further automate it. Strongly simplified, the data (from the source) should travel faster than the flow of goods (Physical Layer) to enable a high-quality, efficient and timely risk assessment (see Figure 5.3 below).

Figure 5.3: Seamless integrated data pipeline (adapted from Task 360 Team, 2013)

26_{Unusually long stops, or deviation from the declared/most efficient route could result in the flagging of a container for}

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5.6.1 Tackling the challenges of the PI

Further automation seems key for DNL to deal with the increased volume of shipments (Lewis, 2009) that is expected as a result of the PI. Receiving more information at an earlier stage will enable DNL to conduct the risk assessment process more efficiently. In the current state (see Appendix E and G), the limited set of poor-quality data received by means of declarations is frequently insufficient for an unambiguous risk assessment. To that end, DNL frequently requests additional documents to e.g. cross-validate the data provided in the declaration. This process can lead to delays at several stages:

- After the request, DNL needs to wait for the declarant to submit the requested documents before being able to finalise the risk assessment process.

- Declarants may not have direct access to the required documents themselves, meaning they will need to request them with their SC partners, in turn leading to more delays.

If this occurs when goods have already arrived in the port of offloading, these delays will mean severe disruptions to the physical movement of the goods, which could in turn affect the quality of the goods. A more efficient risk assessment process, characterised by data that is received early in the logistics chain, will thus aid in preventing disruptions to the physical flow of goods. When a physical inspection is deemed necessary and decided upon at an early stage in the chain, there will be more time available to efficiently organise the inspection, thereby keeping the disruption of the logistics process to a minimum. At the same time, the opportunity of using a more elaborate dataset for risk assessment is expected to increase the quality of the risk assessment and thereby reduce the number of false

positives (i.e. unnecessary inspections).

The Physical Internet: a new grand challenge for customs authorities?