Macquarie University - Introduction · Web viewthe supplier and the country of origin. For example,...

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MacquarieBusiness School

RESEARCH PROPOSAL1

Evaluation of BlockChain: Meat Protection Trials Case Study

Yvette Blount

Amy Tung

Yuniarti Hidayah Suyoso Putra

Macquarie Business School

Macquarie University

19 April 2020

Table of Contents

Introduction4Background and Context4Problem Statement4Literature Review5Blockchain5Supply Chain6Cold Chain Monitoring6Benefits7Barriers and risks7Traceability8Transparency9Chinese Market9Vietnamese Market9United States of America Market10Theory10Relevance and Importance of the Research10Research design and methods10Research design10Methods11Practical Considerations13Implications and contributions to knowledge13Practical Implications13Theoretical Implications13Preliminary Research schedule and budget13References14Appendix 1: Process Mapping17Appendix 2: Meat Protection Air Trail18Appendix 3: Participants and App Details19Appendix 4. Interview Guidelines20

List of Figure

Figure 1: Barriers of blockchain (Saberi, Kouhizadeh et al. 2019)8

Figure 2: Framework of Blockchain Technology Evaluation11

List of Table

Table 1: Research Participants11

Introduction

Background and Context

Aglive (https://aglive.com/about-aglive/) developed the world’s first electronic National Vendor Declaration (eNVD) app in consultation with the MLA (Meat and Livestock Association https://www.mla.com.au/). In 2015, Aglive was licenced by the MLA as the first provider of an electronic National Vendor Declaration for use by producers and processors in Australia. Aglive’s eNVD underpins the LPA Quality Assurance program and provides complete traceability of livestock, from farm to stockyard, feedlot, abattoir and exporter. By creating a simple to use, electronic version of the National Vendor Declaration.

TBSx3 is a technology platform designed around three concepts (https://tbsx3.com/): Cryptographic Certainty, Logistics Tracking and Blockchain Technology.

Aglive and TBSx3 merged in January 2020 under the name Aglive (supported by the Blockchain technology Sx3 and IoT solution AusTracker) to develop an industry-first end-to-end paddock-to-plate solution that will strengthen trust in beef industries around the world. The mergers gives Aglive the expertise and technology to be able to digitize their food supply chain process, making it more transparent, traceable, and immutable (https://www.cryptoninjas.net/2019/10/15/aglive-to-merge-with-tbsx3-bringing-blockchain-trust-to-beef-supply-chain/).

See Appendix 1 for the process map.

Aglive is running numerous trials over the coming months. One trial has already occurred. The next two trials will be:

Trial 2 – 29-30 Jan ‘20

· Supply Chain Traceability with Cold Chain Monitoring (frozen) through the use of IoT and Block Chain

· Route will involve: Macka’s Farm – livestock transport – abattoir/ meat processor – finished product transport – DB Schenker – Sea Freight Australia (Brisbane) to China (Shanghai) – Chinese Customs – Macka’s China Distribution Centre – Chinese Supermarket (On-line)

Trial 3 – end Feb/ early Mar ‘20

· Supply Chain Traceability with Cold Chain Monitoring (fresh) through the use of IoT and Block Chain

· Route will involve: Macka’s Farm – livestock transport – abattoir/ meat processor – finished fresh product transport – DB Schenker – Air Freight – Cathay Pacific Australia (Brisbane) to Hong Kong to China (Beijing or Shanghai) – Chinese Customs – Macka’s China Distribution Centre – Chinese Supermarket (On-line)

See Appendices 2 and 3 for details about the trials.

Macquarie University Business School has been approached to ascertain if there is a potential research project to evaluate the trials. The outputs would include an academic paper and a report for Aglive.

Problem Statement

There are significant problems in the food supply chain involving counterfeit goods and food. Fake or counterfeit food not only has significant issues for health but also the reputation of the supplier and the country of origin. For example, in 2018, more than a quarter of commercial honey brands were found to have potentially been watered down with sugar cane, corn syrup or other products. This is problematic because Australia is the fourth largest exporter of honey in the world so authenticity about how pure honey products are is important for the market and reputation of suppliers and the country (Zhou, Taylor et al. 2018).

The export red meat market is a significant Australian export. According to MLA’s data Australia was the third largest beef exporter in 2018, behind Brazil and India. The export industry was worth over $13 billion and employed over 430,000 people in 2016/2017. Australia is consistently one of the top beef, sheepmeat and goatmeat exporters globally, however, competition in the international marketplace is intensifying. The increased competition means that Australia’s need to be even more focused on meeting consumer needs while increasing productivity and efficiencies through the supply chain (Meat & Livestock Australia 2019). Very importantly this includes the ability to trace the product (meat) from paddock to plate.

An ABC investigation in November, 2019 claimed that every second kilo of beef exported to China from Australia is possibly fake (Adams 3 November 2019). Therefore, how can we ensure that the product is authentic?

The generic supply chain consists of production, processing, distribution, retailing and consumption. Blockchain in the food supply chain holds great promise but there are significant challenges and barriers that need to be overcome. Examples include regulation, technology infrastructure, technology skills, scalability, cost and privacy (Kamilaris, Fonts et al. 2019).

The research aim is to evaluate the Aglive solution for achieving the objectives of traceability from paddock to plate. This will include the opportunities and potential benefits as well as the challenges, barriers and risks.

Research Questions

The overarching research questions are:

1. What are the opportunities and benefits for the stakeholders of the supply chain to adopt the Aglive solution?

2. What are the challenges, barriers and risks for the stakeholders of the supply chain to adopt the Aglive solution?

Literature Review

Blockchain

Blockchain underpinned the first cryptocurrency, Bitcoin (Nakamoto 2008). A blockchain is a digital ledger where transactions are maintained by a network of computers. Each transaction is a block and each block are managed through a software platform that allows the data to be transmitted, processed, stored, and represented in human readable form. Each block contains a header with a timestamp, transaction data and a link to the previous block. A hash gets generated for every block, based on its contents, and then becomes referred in the heading of the subsequent block. Any manipulation of any block in the chain would result in a mismatch of hashes in all subsequent blocks (Kamilaris, Fonts et al. 2019).

Although blockchain was originally used for financial transactions and records, in more recent times, there have been other applications that have experimented with the technology. For example, administrative records, smart contracts, digital authentication and signature systems, verifying and tracking ownership of intellectual property rights and patent systems, electronic voting and tracking of goods through the supply chain (Kamilaris, Fonts et al. 2019).

The literature on Blockchain and the supply chain show that there is great potential to resolve issues such as traceability, however issues remain including technical aspects, education, policies and regulatory frameworks (Kamilaris, Fonts et al. 2019).

Supply Chain

The food supply chain is complex and involves many stakeholders with different maturity levels such as farmers, shipping companies/ airlines, wholesalers and retailers, transport, distributors, and consumers. The generic agri-food supply chain phases are:

· Production/ Farming

· Processing

· Distribution

· Retailing

· Consumption (Caro, Ali et al. 2018, Kamilaris, Fonts et al. 2019)

Supply chains are cumbersome and inefficient, transactions are vulnerable to fraud, there is little transparency, consumers are unaware of the origin of products and risks as well as costs are high (Kamilaris, Fonts et al. 2019). Walmart was an early adopter and piloted using blockchain in the supply chain of pork and mangoes in the Chinese market (Kamath 2018).

Kamilaris, Fonts et al. (2019) investigated existing blockchain projects in the agricultural supply chain including soybeans, grains, olive oil, turkeys, mangoes, tinned pumpkin, pork, sugar cane, beer, beef, chicken, cannabis, wood, seafood, table grapes, organic food, food waste, water and rice. The objective for using blockchain included traceability, supervision and management, waste reduction and environmental impact. The Blockchain technology solutions were varied, however it was unclear if the projects were ongoing to had ceased.

Cold Chain Monitoring

The cold chain is responsible for ensuring that perishable food is preserved and transported at the optimal temperature to slow biological decay to ensure the quality and safety to the consumer (Mercier, Villeneuve et al. 2017). According to Tesson, Federighi et al. (2020), in Europe each year, meat is associated with 2.3 million foodborne illnesses, with many of those from beef. The Quantitative Microbiological Risk Assessment (QMRA) model, first used to measure water safety, is used as a risk assessment tool for food including beef (Tesson, Federighi et al. 2020). Contamination by a pathogen may occur at any stage of the supply chain, therefore knowledge of the whole paddock to plate cold chain is important for the quality and safety of meat (Tesson, Federighi et al. 2020).

Therefore, optimal temperature monitoring is a prerequisite for cold chain management and thus for the production and supply of high quality and safe products as well as for the reduction of waste and economic losses. A special focus is placed on the identification and specification of challenges by the implementation of temperature monitoring systems which allow an optimal control of the temperature conditions in meat supply chains, as required by the European food law (Mercier, Villeneuve et al. 2017).

Benefits

Blockchain will improve traceability because each individual item can be tracked leading to transparency, significantly reducing the costs of monitoring processes. This may lead to a reduction in operational, financial and insurance costs and the ability to deal with fake products (Queiroz, Telles et al. 2019). For example, the blockchain technology enables Walmart to successfully trace and validate the pork products transported from a

farm owned by the Chinese meat producer Jinluo to Walmart’s distribution centre in Beijing and help to ensure that the food products consumed by the consumers is right and authentic (Kshetri and Loukoianova, 2019).

Blockchain can increase transparency, traceability and sustainability as well as the potential for smart contracts. Smart contracts could automate payments as well as validate transactions and help eliminate food fraud (Astill, Dara et al. 2019; Hancock, 2019).

Barriers and risks

The disruption to the supply chain as a result of Industry 4.0 and emerging technologies such as blockchain and IoT will result in disintermediation resulting from smart-contract adoption (Queiroz, Telles et al. 2019).

A framework by Saberi, Kouhizadeh et al. (2019) shows the potential barriers for Blockchain adoption in the Supply Chain.

Figure 1: Barriers of blockchain (Saberi, Kouhizadeh et al. 2019)

Olsen, Borit, and Syed (2019) showed that in the red meat supply chain, the barriers include fraud by replicating the product and packaging without proper food safety assurances (such as fraudulent health certificate or documentation, product produced without inspection, illegal slaughter) and fraud in finished products (e.g. the presence of illegal veterinary medicine, undeclared substance to improve appearance or shelf life product such as colourants). Other challenges relate to infrastructure in supporting the blockchain technology in such as the accessibility to mobile devices and internet, reluctance by some industries to share access to their data, data entry issues and the regulatory environment (Hancock, 2019; Kamilaris et al, 2019).

The literature refers to the potential of Blockchain in the agricultural supply chain for traceability and transparency.

Traceability

There are laws, regulations and standards relating to traceability in supply chains including food. For example, ISO 22005:2007 Traceability in the feed and food chain and ISO/DIS 22095 Chain of custody — General terminology and models that is currently under development (https://www.iso.org/standard/72532.html) (Olsen and Borit 2018).

The definition of traceability is problematic because there are different definitions that apply in legislation and standards. For the purposes of this study, the definition of traceability will use the Olsen and Borit (2018) definition: “the ability to access any or all information relating to that which is under consideration, throughout its entire life cycle, by means of recorded identifications”. A traceable resource unit (TRU) is well established term that refers to any traceable unit including a trade unit such as a bottle or bag, a logistic unit such as a pallet or container or a production unit such as a lot or batch (Olsen and Borit 2018)

Transparency

Bouzembrak, Steen et al. (2018) developed text mining tool to collect food fraud articles. The authors found that the three biggest fraudulent items were meat, seafood and milk. The use of blockchain technology provide the transparency in information sharing such as improving the distribution of the products and price transparency (Hancock, 2019). The technology could provide the efficient solution the urgent need to improve the traceability of food related to its safety and transparency (Kamilaris et al, 2019), and enables the company to record every event or transaction within the supply chain distribution (Kshetri and Loukoianova, 2019)

Chinese Market

In big agricultural markets such as China, traceability is a preventive strategy for the quality, safety and authenticity of food items (Tse, Zhang et al. 2017). Chinese consumers tend to distrust locally produced food and consider it inferior to imported food from countries that have strict regulations around food safety, for example, Europe. The identification and authenticity of products is key to building trust with Chinese consumers (Kendall, Naughton et al. 2018).

There is complexity around the regulatory environment in China, because the quality and safety of food is managed by different government departments that are not integrated (Tse, Zhang et al. 2017). Kendall, Kuznesof et al. (2019) found that food fraud (authenticity, safety, quality and reliability of food) is a primary barrier to the attainment of safe food and is prevalent in the minds of consumers. That is, brand reputation and trust influence the purchasing decisions of consumers in China.

Blockchain may be a solution for the government to better track, monitor and audit the food supply chain support manufacturers in authenticating transactions (Tse, Zhang et al. 2017).

Vietnamese Market

The issue with counterfeit goods is not just a Chinese phenomenon. Other countries such as Vietnam have experienced similar issue around the authenticity of food (Veitnam Investment Review 2018). Some food safety issues in Vietnam are related to lacks of ethics of certain food value chain stakeholders and the difficulty in managing food in wet markets and from smallholder production (Nguyen-Viet, Tuyet-Hanh, Unger, Dang-Xuan and Grace, 2017).

Food fraud also has been reported widely in some developing countries, for example, Pakistan, Brazil, and India has reported milk adulteration usually for financial gain or due to poor hygiene conditions of processing, storage, transportation, and marketing (Handford, Campbell, and Elliott, 2016).

United States of America Market

United States of America (USA) market also suffers from food fraud problems. The Washington Post reported that fraudulent activities have been found in food products such as fruit juice, olive oil, spices, vinegar, wine, spirits and maple syrup, and appears to pose a significant problem in the food industry. Victims range from the shopper at the local supermarket to multimillion companies, including E&J Gallo and Heinz USA. For example, the expensive "sheep's milk" cheese in a Manhattan market was made from cow's milk and a jar of "Sturgeon caviar" was Mississippi paddlefish. Some honey makers dilute their honey with sugar beets or corn syrup but still sell it as 100 percent pure at a premium price (Layton, 2010). Food fraud is also in seafood supply chain industries which involve importers, to fraudulent activities at individual restaurants or grocery stores (Fox, Mitchell, Dean, Elliott, and Campbell, 2018).

Some food distribution areas such as cattle, egg, and poultry production industries have become the focus of attention related the use of blockchain technology to prove provenance, compliance, authenticity, and quality. The governments in states such as Colorado and Wyoming encourage the use of blockchain technology for the beef supply chain (Bumblauskas, Mann, Dugan, Rittmer, 2020). Retail giants such as Walmart are working on the utilization of blockchain technology to solve food safety problems and build more transparency in food production including their beef products (Kamath, 2018; Polasek, 2019)

Theory

Stakeholder theory argues that every person or group involved in the activities or an organisation do so to obtain benefits. Stakeholder theory overlays the conceptual framework of benefits and challenges in the research design section.

Relevance and Importance of the Research

Studies relating to blockchain and supply chain management (SCM) integration are limited because many applications are either in pilot or just beginning (Queiroz, Telles et al. 2019). There are behavioural, organisational, technological, or policy-oriented aspects that are yet to be resolved (Saberi, Kouhizadeh et al. 2019).

This is a new area of research that is integral to the MQBS research and teaching capabilities.

Research design and methods

Research design

The research will use a conceptual framework developed from the literature to evaluate the Aglive trials. The conceptual framework will evaluate the strengths and limitations of using blockchain in the supply chain for achieving the objectives of traceability and transparency using stakeholder theory. Figure 2 presents the conceptual framework blockchain evaluation adapted from Saberi, Kouhizadeh et al. (2019) and Kamilaris et al (2019).

Figure 2: Framework of Blockchain Technology Evaluation

Methods

The evaluation will combine both qualitative and quantitative approaches following Creswell (2014) and consist of two main phases. The first phase is a qualitative study using interviews and the second phase is a quantitative study using survey.

The first phase is a pilot study. The evaluation will use qualitative methods. The data will include:

· Semi-structured interviews from stakeholders

· Documents and articles on the supply chain and blockchain technology

The interviews will last between 30 and 45 minutes. The interview questions will design to identify the opportunities and benefits, and the challenges, barriers and risks for the stakeholders of the supply chain to adopt the Aglive solution. The interviews will be recorded, and additional notes will be taken. The guideline for interview questions is presented in Appendix 4. The following are the list of participants to include in this research.

Table 1: Research Participants

Code

Description

Company

Participant

Responsibility

Interviewee 1

Production

Macka Beef

Robert Mackenzie – Brand Owner for Macka’s

T: +61 2 4982 6227

M: 0408 490 911

E: [email protected]

Meat production / farming

Interviewee 2

Logistic Provider

Macka shipping

Trevor Heinrich - General Manager for Martins Stock Haulage

T: 07 4691 2888

M: 0488 078 000


Livestock transport to abattoir, and meat products from abattoir to company’s warehouse

Interviewee 3

Meat processing plant

Abattoir

Plant manager or representativeComment by Author: Need to discuss

Meat processing

Interviewee 4

Warehousing

Company’s warehouse

Warehouse manager of representative

Storing, products’ handling including packaging, labelling, and distributing

Interviewee 5

Logistic provider

Sea freight

DB Schenker

Chris Pienaar - Vertical Market Manager Perishables for DB Schenker

P: +61 2 9333 0330

M: +61 409 070 837


Finished product transport

Interviewee 6

Warehousing

Macka’s China Distribution Centre

Warehouse manager or representative

Storing, products’ handling including repackaging and labelling, and distributing

Interviewee 7

Retailing

China’s supermarket (on-line)

Monica – Chinese contact for Macka’s

P/ M: Use of WeChat


Retailer of products

Interviewee 8

Consumption

Customer

Customer Comment by Author: Through Monica (Macka’s China)

Product’s consumer

Interviewee 9

Blockchain Provider

Aglive Pty Ltd

Micha Veen

Supply Chain Innovation Specialist

Data from semi-structured interviews from stakeholders will be analysed using NVivo and will triangulate with other sources such as documents and articles on the supply chain and blockchain technology

Initial themes, data coding, and keywords were generated from a framework developed based on the stakeholder theory and potential barriers draws from blockchain studies (Saberi et al, 2019; Kamilaris et al, 2019; Wang, Singgih, Wang, and Rit, 2019). The findings from first phase will be used to build a second, quantitative phase by conducting the survey).

Practical Considerations

The trials will initially be evaluated after they have taken place due to time constraints. In the future we envisage that once the conceptual framework is validated, we will be able to assess live trials.

Implications and contributions to knowledge

Practical Implications

The study will provide guidance to policy makers (regulators), supply chain stakeholders, blockchain developers and consumers on the benefits and limitations of using blockchain in the supply chain.

Theoretical Implications

The study will contribute to the literature by developing a conceptual framework to critically evaluate supply chain block chain solutions.

Preliminary Research schedule and budget

Item

Description

Completion Dates

Resource

Budget

Draft Research Proposal

The first draft of the research proposal

9 February 2020

YB

Appoint Research Assistant (Yuni)

8 May 2020

YB

Level 6

Literature Review

Ongoing January 2020 – Finalisation of project

YB and Yuni

Draft budget

20 March 2020

YB and MV

Project plan

20 March 2020

YB and MV

Finalisation of Research Proposal

24 April 2020

YB and Research Assistant

Contract (Research Collaboration Agreement)

Agreement between Aglive and MQBS

8 May 2020

YB, Aglive (MV), Research Office, Legal

Ethics Approval

Ethics application deadline

Ethics approval

4 May 2020

22-29 May 2020

YB and Yuni

Data Collection

Interview and documents collection

May-June 2020

YB and Yuni

Data Analysis

NVivo analysis

June – July 2020

YB and Yuni

First draft of report

17 July 2020

YB and Yuni

Finalisation of report

20 July-21 August 2020

YB, Yuni, MV

Development of Phase 2 of project (project plan/budget)

30 August 2020

YB

Journal paper

Send to journal

31 August 2020

YB, Yuni, MV

References

Adams, P. (3 November 2019). "China is hungry for Australian beef, but every second kilo shoppers buy could be fake." Retrieved Accessed 28 January 2020, 2020, from https://www.abc.net.au/news/2019-11-03/blockchain-detecting-beef-fraud-in-australian-exports-to-china/11662950.

Astill, J., R. A. Dara, M. Campbell, J. M. Farber, E. D. Fraser, S. Sharif and R. Y. Yada (2019). "Transparency in food supply chains: A review of enabling technology solutions." Trends in Food Science & Technology.

Bouzembrak, Y., B. Steen, R. Neslo, J. Linge, V. Mojtahed and H. Marvin (2018). "Development of food fraud media monitoring system based on text mining." Food Control 93: 283-296.

Bumblauskas, D., Mann, A., Dugan, B., Rittmer, J. (2020). " A blockchain use case in food distribution: Do you know where your food has been?" International Journal of Information Management 52: 1-10.

Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (4th ed.). Los Angeles: Sage Publications.

Caro, M. P., M. S. Ali, M. Vecchio and R. Giaffreda (2018). Blockchain-based traceability in Agri-Food supply chain management: A practical implementation. 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), IEEE.

Fox, M., Mitchell, M., Dean, M., Elliott, C., and Campbell, K. (2018). " The seafood supply chain from a fraudulent perspective". Food Security 10:939–963.

Handford, C.E., Campbell, K., and Elliott, C.T. (2016). Impacts of Milk Fraud on Food Safety and Nutrition with Special Emphasis on Developing Countries. Comprehensive Reviews in Food Science and Food Safety 15: 130-142.

Hancock, C. N. (2019). "The Integration of Blockchain Technology to the Beef Industry – A Comparative Analysis". Social Impact Research Experience (SIRE). 71. https://repository.upenn.edu/sire/71

Kamath, R. (2018). "Food traceability on blockchain: Walmart’s pork and mango pilots with IBM." The Journal of the British Blockchain Association 1(1): 3712.

Kamilaris, A., A. Fonts and F. X. Prenafeta-Boldύ (2019). "The rise of blockchain technology in agriculture and food supply chains." Trends in Food Science & Technology 91: 640-652.

Kendall, H., S. Kuznesof, M. Dean, M.-Y. Chan, B. Clark, R. Home, H. Stolz, Q. Zhong, C. Liu and P. Brereton (2019). "Chinese consumer's attitudes, perceptions and behavioural responses towards food fraud." Food Control 95: 339-351.

Kendall, H., P. Naughton, S. Kuznesof, M. Raley, M. Dean, B. Clark, H. Stolz, R. Home, M. Chan and Q. Zhong (2018). "Food fraud and the perceived integrity of European food imports into China." PloS one 13(5).

Layton, L. (2010). " FDA pressured to combat rising 'food fraud'. The Washington Post. Retrieved from http://www.washingtonpost.com/wp-dyn/content/article/2010/03/29/AR2010032903824_pf.html

Meat & Livestock Australia (2019). 2019 State of the Industry Report The Australian Red Meat and Livestock Industry

Mercier, S., S. Villeneuve, M. Mondor and I. Uysal (2017). "Time–temperature management along the food cold chain: A review of recent developments." Comprehensive Reviews in Food Science and Food Safety 16(4): 647-667.

Nakamoto, S. (2008). "A peer-to-peer electronic cash system." Bitcoin.–URL: https://bitcoin. org/bitcoin. pdf.

Kamath, R. (2018). "Food traceability on blockchain: Walmart’s pork and mango pilots with IBM". The JBBA, 1(1): 47-53.

Kshetri, N. and Loukoianova, E. (2019)."Blockchain adoption in supply chain networks in Asia” IEEE IT Professional, 21(2), 11-15.

Nguyen-Viet, H., Tuyet-Hanh, T.T., Unger, F., Dang-Xuan, S., and Grace, D. (2017). Food safety in Vietnam: where we are at and what we can learn from international experiences. Infectious Diseases of Poverty 6 (39): 1-6.

Olsen, P. and M. Borit (2018). "The components of a food traceability system." Trends in Food Science & Technology 77: 143-149.

Olsen, P., Borit, M. and Syed, S. (2019). Applications, limitations, costs, and benefits related to the use of blockchain technology in the food industry. Report 4/2019, Norway: Nofima.

Polansek, T. (2019). Walmart creates Angus Beef Supply Chain, Cutting Out Meat Processors. Reuters. Accessed 20 May 2019 https://www.reuters.com/article/us-walmart-beef/ walmart-creates-angus-beef-supply-chain-cutting-out-meat-processors

Queiroz, M. M., R. Telles and S. H. Bonilla (2019). "Blockchain and supply chain management integration: a systematic review of the literature." Supply Chain Management: An International Journal.

Saberi, S., M. Kouhizadeh, J. Sarkis and L. Shen (2019). "Blockchain technology and its relationships to sustainable supply chain management." International Journal of Production Research 57(7): 2117-2135.

Tesson, V., M. Federighi, E. Cummins, J. de Oliveira Mota, S. Guillou and G. Boué (2020). "A Systematic Review of Beef Meat Quantitative Microbial Risk Assessment Models." International Journal of Environmental Research and Public Health 17(3): 688.

Tse, D., B. Zhang, Y. Yang, C. Cheng and H. Mu (2017). Blockchain application in food supply information security. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

Veitnam Investment Review. (2018). "Counterfeit goods growing into serious social issue." Retrieved 9 February 2020, from https://www.vir.com.vn/counterfeit-goods-growing-into-serious-social-issue-63802.html.

Zhou, X., M. P. Taylor, H. Salouros and S. Prasad (2018). "Authenticity and geographic origin of global honeys determined using carbon isotope ratios and trace elements." Scientific Reports 8(1): 14639.

Wang, Y., Singgih, M., Wang, J., and Rit, M. (2019). Making sense of blockchain technology: How will it transform supply chains? International Journal of Production Economics, 211, 221–236.

Appendix 1: Process Mapping

Appendix 2: Meat Protection Air Trail

Appendix 3: Participants and App Details

Appendix 4. Interview Guidelines

General Information

1. What’s your name?

2. What’s your title?

3. How long have you worked in the company?

4. Tell us about your role at the company?

5. What is your organisation’s role in the supply chain (which part)?

Supply Chain

1. What technology or paper process was used in the supply chain before blockchain?

2. What does your supply chain look like today?

a. How much is manually handled?

b. How much is digitally handled?

3. How does your information flow look like?

a. How much data is shared in the red meat supply chain?

b. How is the data you collect, stored and shared?

c. What databases, inhouse solution or system do you use? Is it centralized or provided by an external party?

Traceability

1. How do you value traceability within your company?

a. Is it something you prioritize in your business operations?

b. Do you believe that blockchain is able to improve traceability in and outside your company?

c. How could blockchain improve traceability?

d. Is your technology infrastructure sufficient for using blockchain? For example, do you need to improve, update or replace technology?

2. What actions are made in case of a product recall?

a. is there any documentation over what routines there are in this case?

b. What trends can you see for the food sector to improve traceability?

c. Is there any technology that you think you could adopt in the future?

3. What did your company do to before blockchain was introduced to increase the traceability of red meat?

4. How do you collaborate with the other members of the supply chain to increase the traceability of red meat?

Blockchain

1. How is blockchain is being used in your organization?

2. Intra-organisational barriers:

a. Is there any problem with technological skill and expertise to operate blockchain technology?

b. Is there enough support and management commitment within your organization including the policies related to the use of this technology?

c. Is there any hesitation or resistant to use this technology? What are the reasons or problems?

3. Inter-organisational barriers:

a. Is there any problem in the collaboration, communication, and coordination in the supply chain?

b. Is there any challenge in disclosing the information policy between partners in the supply chain?

c. Problem with cultural differences of supply chain partners?

4. System related barriers:

a. Is there any problem with the access to technology?

b. Is there any security challenge during the use of blockchain that need to improve?

5. External barriers:

a. Is there any support or government regulation related to the use of blockchain in red meat industry?

b. Is there any industry involvement in ethical and safety practices?

c. Is there any problem with market competition and uncertainty in using blockchain?

6. Do you believe that your business model has to change with the implementation of blockchain?

7. In what way?

8. What do you believe are the benefits in implementing a blockchain technology?

9. What do you believe are the restrictions in implementing a blockchain technology?

10. Do you believe that the use of blockchain enable to reduce the transaction costs?

Draft 1.5 19 April 2020 Yvette Blount

Meat Protection Air Trail

1

TBSX3 BUSINESS AREA DEFINITION

Purpose of this document To identify any business processes, scripts or scenarios for the use of such processes that will

need to be established as part of the solution To identify much of the business data to be used (created/ manipulated) and through use of the

proposed solution To assess the impact of the project outcome on the various supply chain partners that need to be

managed. Considering new or changed: o Operational business process and organisational elements o Culture or behaviour o Resource activities

To describe the strategy for deploying the 3 trails and the final solution and/or any increments of it, from a business perspective

To describe the strategy for training those impacted by this solution

Document Admin

Approved/Accepted by

Robert Mackenzie Macka’s

date Chris Pienaar DB Schenker

date

Nigel Chynoweth Cathay Pacific

date Paul Allen Macka’s/ Casino

date

Paul Ryan/ Mark Toohey Business Visionary

25-Nov-19 Andrew Dong CTO/ Solution Architect

25-Nov-19

Micha Veen Supply Chain Innovation Specialist

25-Nov-19

Revision History

Name Version Reason for change Status

BPS - Draft v0.1 Create Document Complete


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TABLE OF CONTENTS TBSx3 Business Area Definition ....................................................................................... 1

Purpose of this document ............................................................................................................................ 1 Document Admin ......................................................................................................................................... 1

Table of Contents .......................................................................................................................................... 2

Business Impact Assessment ........................................................................................... 3 Business Process Impacts ........................................................................................................................... 3

Business Process Context .......................................................................................................................... 3 Processes to be validated through Blockchain Technology ........................................................................ 5 Process Operation ....................................................................................................................................... 6 Process Scripts/ Scenarios ......................................................................................................................... 8

External Solution Impacts ............................................................................................................................ 8 Business Organisation and Resourcing Impacts ...................................................................................... 8 Principles, Assumptions and Constraints .................................................................................................. 8

Business Implementation Strategy ................................................................................. 10 Impact on the Business Organisations ..................................................................................................... 10 Changing External Business Interfaces .................................................................................................... 10 User Training ............................................................................................................................................... 10


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BUSINESS IMPACT ASSESSMENT The Business Impact Assessment section of this document provides key input for the Solution Architecture/ Technical Architecture Document (covered separately) and for the Business Implementation Strategy in the second part of this document.

BUSINESS PROCESS IMPACTS Business Process Context The diagram below provides the high-level process from “Paddock to Plate”. This trail is set-up in three parts, being:

Trail 1 – Track and Trace of frozen meat, location based on TBSX3 app and/ or partner data availability

Trail 2 – Track and Trace of frozen meat, location based on a combination of TBSX3 app, partner data availability and IoT devices. This trail included location and cold chain monitoring

Trail 3 – Track and Trace of fresh/ chilled meat, location based on a combination of TBSX3 app, partner data availability and IoT devices. This trail included location and cold chain monitoring

The following supply chain process participants will be actively involved to capture:

Participant(s) Role Process Description Data

Macka’s/ Aglive Farm Livestock tracking from birth to Mature

Digital Livestock Consignment (incl. Aglive eNVD/ Waybill) Commercial Brand Claims & Integrity Declarations Tracking Data

Macka’s/ Aglive/ AusTrack

Transport Livestock tracking from Mature to Abattoir GPS tracking in Macka’s Livestock transport

Digital Livestock Consignment (incl. Aglive eNVD/ Waybill) (GPS) Tracking Data


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Casino (Macka’s) Abattoir Livestock Tracking from Transport to Kill Plan to Meat Processor (finished/ retail product)

Digital Livestock Consignment (incl. Aglive eNVD/ Waybill) Abattoir Lot/ Batch receipt Meat Processing solution GPS Tracking (Location) Temperature Tracking (Cold Chain)

DB Schenker Transport Retail product tracking GS1/ SSCC/ QR Code tracking

GS1 Data SSCC Data Product / GPS/ Cold Chain Transport Documentation (ASN/ Export-Import/ Customs)

Cathay Pacific Transport Retail product tracking GS1/ SSCC/ QR Code tracking

GS1 Data SSCC Data Product / GPS/ Cold Chain Transport Documentation (ASN/ Export-Import/ Customs)

Macka’s - China (Warehouse)

Warehouse Retail product tracking within warehouse – location tracking GS1/ SSCC/ QR Code tracking

GS1 Data SSCC Data Product / GPS/ Cold Chain Transport Documentation (ASN/ Export-Import/ Customs) Warehouse Storage location

Macka’s - China (Logistics)

Transport Retail product tracking between warehouse and point-of-sale (location tracking) GS1/ QR Code tracking

GS1 Data Product / GPS/ Cold Chain Transport Documentation (ASN/ Delivery/ Proof of Delivery) Point-of-Sale Storage location Transport tracking

Supermarket/ Sales & Distribution China (Consumer sales)

Point of Sales

Retail product tracking within – location tracking GS1/ QR Code tracking

GS1 Data Product / GPS/ Cold Chain Transport Documentation (Chinese Transport documentation) Point-of-Sale Storage location

The full end-to-end project will use a combination of:


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IoT devices – automated tracking Supply Chain solutions – scanning (good receipt/ goods issue), ERP, warehouse, distribution and

transport solutions. Blockchain – data integrity between the supply chain partner to ensure that full track and trace,

GPS and cold chain verification is in place The diagram, describing the end-to-end process and data captures is identified below. Further context and described in more detail in the following section.

Processes to be validated through Blockchain Technology As further described in the Solution Architect Documentation, these trails use a proven blockchain solution to ensure integrity of the data is maintained. This will be ensured through multiple data verification points (independent data comparisons) ensuring that the product authenticity is not being compromised. The aim of this trail is to use existing data standards, e.g. GS1, SSCC and other standards to verify and track the physical with the digital supply chain. The high-level technology model which is capturing these digital data points is shown below:

Cold Chain

The Temperature and location of products being transported in Cold Chain needs to be monitored. It would be stored in Blockchain periodically. Business partners can access the Blockchain to trace and analyze the data, making a better business decision.

Blockchain Location


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At every stage in the physical supply chain, data points will be registered to ensure that the products are being digitally tracked from Paddock to Plate (Point of Sale) and are at their “expected” location. The aim of these trails is to proof and further validate the provenance of the products when it arrives at its end-location. The provided technology (further explained in the Solution Architecture) will ensure that all relevant validations take place to continuously verify the product history.

Process Operation The Process operation is captured through the following main process descriptions;

User Class (Business Role)

Geographic Location(s) or Mobile

User Req. Use of the Solution

Farmer Farm (Australia) Capture farm-data, documentation (incl. food/ nutritional data)

Aglive Solution


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Transport Farm – Abattoir (Australia)

Capture farm data and transport data (GPS tracking)

Aglive Solution Austracker

Abattoir Abattoir/ Meat Processor (Australia)

Capture feed lot/ batch data Capture meat processing data (from abattoir to retail product) Capture GS1/ QR code data/ SSCC Label GPS Tracking (on product/ batch/ pallet/ container) Capture Cold Chain data (required and actual)

Aglive Solution Austracker Meat Processor Product Information

Transport Meat Processor (Australia) to Warehouse (China)

Capture GS1/ QR code data/ SSCC Label Capture transport information (documentation) GPS Tracking (on product/ batch/ pallet/ container) Capture Cold Chain exception reporting (when cold chain is broken)

Aglive/ TBSX3 Solution DB Schenker Cathay Pacific Austracker

Warehouse Macka’s Warehouse (China)

Capture GS1/ QR code data/ SSCC Label Capture transport documentation (export-import/ customs/ etc>) Capture warehouse location/ GPS Tracking (on product/ batch/ pallet/ container) Capture Cold Chain exception reporting (when cold chain is broken)

Aglive/ TBSX3 Solution Austracker

Point of Sale Supermarket/ On-line distribution

Capture GS1/ QR code data/ SSCC Label Capture supermarket (isle) location/ GPS Tracking (on product/ batch/ pallet) Capture Cold Chain exception reporting (when cold chain is broken)

Aglive/ TBSX3 Solution Austracker Supermarket POS solution


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Process Scripts/ Scenarios To ensure that all the requirements are met, a detailed scenario list (with associated test scripts) has been developed to validate the individual supply chain participant process elements and expected outcomes. (This is captured in a separate document - Meat Protection Air Trails - Scenarios and Test Scripts)

EXTERNAL SOLUTION IMPACTS There is a clear focus on using existing third-party data elements, to reduce the need to develop all functionality from scratch. This will allow us to ensure that we minimise the capturing of data through “TBSX3 hardware/ software solutions”, but transition towards validating existing data. Therefore, there is a preferred reliance on the data that is provided through our partner’s software solutions in this Trail. However, if the supply chain partner is unable to provide fit-for-purpose data and information as part of these trails, there is a solid back-up solution to capture the data requirements through the TBSX3 app.

BUSINESS ORGANISATION AND RESOURCING IMPACTS Due to the nature of this project, there is a strong reliance on the resource capability, capacity and skill set of the partners in these trails. Therefore, this project has provided the following details to these partners (as part of this initiative)

Data requirements per partner Hardware/ software solutions (or insight in these) to allow capturing of the relevant data Training requirements (when no sufficient software solution is in place) IoT device requirements to allow the team to capture data using non-human technologies to

provide accurate and independent data The main challenge is to guide the physical supply chain effectively and capture the digital footprint at every stage of this physical supply chain. Therefore, a clear end-to-end script and scenarios have been established to fully understand, capture and validate the various steps in the supply chain process.

PRINCIPLES, ASSUMPTIONS AND CONSTRAINTS There is a key requirement to deliver this end-to-end solution across the digital and physical supply chain model. Therefore, it’s imperative that the technology solutions have the following key: PRINCIPALS

No-intrusive, easy-to-use and intuitive solution for the various key roles, e.g.; o Warehouse manager


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o Dispatch & Logistics manager o Transport manager/ driver o Operational manager o Dashboard manager

Ability to collect data from various existing or new hardware and software solutions, incl; o Organisational ERP, manufacturing solutions o Scanners, IoT devices, etc. o Apps, Websites, Mobile devices (text messages, etc.)

Hardware/ software solutions which work within different (geographic) locations, incl.; o Areas with no access to internet (Wi-Fi), 3G/ 4G/ 5G, etc. o Different temperatures, e.g. cold stores, warm/ heat (dessert) o Transport environments – air travel, ship, train, truck, etc.

Use existing data to “create” new data requirements to validate relevant key blockchain elements

ASSUMPTIONS

The solution will be fit-for-purpose and developed to increase adoption by all supply chain participants

The supply chain model is a repetitive model with different participants, the solution should/ requires to be built with this repetitive/ enhancing / evolving solution in place

The solution should easily be able to “replace” supply chain participants, but ensure that the end-to-end physical and digital supply chain stays secure and effective

It’s imperative that there is a full end-to-end data model with access and process controls that ensures that there is no data being shared (through the digital supply chain), that is not intended for certain supply chain participants

CONSTRAINTS

The supply chain partner’s solutions will have a different level of maturity (different technology levels). During the early investigation an assessment will be made to either create an interface (to capture the relevant data) or to use the TBSX3/ Aglive app to capture the required data

There is an intention to reduce the number of duplicate actions/ activities by the user in the process, however, the “lack of technology” might require the user to duplicate the actions


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BUSINESS IMPLEMENTATION STRATEGY The solution will be implemented/ tested in stages through various trails, which have a clear scope, intention and expected outcomes. An Agile-product development and deployment methodology is being used to ensure that every trail is effectively delivering additional value. The implementation will run through the following high-level approach:

Development of the requirements Technical validation/ testing of the requirements – based on test scripts/ scenarios

User testing of the test scripts/ requirements Client testing/ validation of the test scripts/ scenario requirements

End-to-end testing of the solution with; o Sign-off of the test/ scenarios o Capture improvements/ enhancements/ findings for the “next” trail o Lessons learned/ review

IMPACT ON THE BUSINESS ORGANISATIONS The focus is on capturing relevant and effective data to conduct a full end-to-end validation (independent validation) of the physical supply chain, ensuring the authenticity of the products and the ability to forecast the physical product flow through the end-to-end supply chain process

CHANGING EXTERNAL BUSINESS INTERFACES To ensure that we use existing data (available from our supply chain partners), instead of creating duplicate or additional processes, there is a desire/ requirement to use standard API’s or data transfer files to capture the data in the TBSX3 database. Additional insights in how this is developed and managed is described in the Solution Architecture documentation

USER TRAINING To ensure that the adoption is effective through our user community, the data capturing makes use of the following models:

Use of existing hardware devices that the user is already familiar with (our solution is capturing the data from the existing devices)

Introduce a role-based, intuitive user-app to capture the required information (available through the TBSX3/ Aglive solution)


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Introduce a fit-for-purpose solution which can be easily deployed and “trained” to the user to capture the relevant data

The focus of the User Interface is to minimise training through using a “Facebook” mindset, meaning “nobody should be trained on using Facebook”..

Meat Protection Air Trial Aglive and Macka’s will work together to conduct a series of air shipment trials. Each trial will expand the scope of the protection and will start to include new features and new trial participants.

1. Brand owners can have confidence their products will safely land at their destination

2. Logistics / Brand protection partners can assure brand owners that their products are safe with them

3. Consumers can trust that the brand they buy is true and genuine

Helping Build a Sustainable Future

Brand Enhancement Trials Join us in our journey in providing brand-consumer transparency with our true

Paddock-to-Plate Technology

The Aim The end result of this trial aims to prove

The Trial

The initial participants in the trials with be:

• Mackas Australian Black Angus Beef;• DB Schenker;• Cathay Pacific; and• Aglive.

Other entities will be invited to join the blockchain over time with the eventual aim that a large number of trusted companies will be involved in this private blockchain.

Your Role

As Macka’s main contact in China, you will play the important role of scanning and receiving the delivered items using the Supplier App to mark the end of its journey to China and to make sure that the items have indeed arrived in good quality shape.

The First Trial Process

Supplier App: An easy, simple, and efficient app built specially for brand owners and their brand protection partners. All actions below will be done using the Supplier App

1. A small number of meat packs in a small number of cartons in Macka’s warehouse will each be labeled with a unique QR code

2. Using the Supplier App, items will be scanned by warehouse personnel and wait for DB Schenker driver to receive and complete the second scan to transfer custody of items to DB Schenker

3. At the next drop point, DB Schenker will once again scan the items and wait for Cathay Pacific crew to receive and complete the second scan. All custody will then be transferred to Cathay Pacific who will take the items to China

4. Once in China, Cathay Pacific will again scan the items and wait for Macka’s Personnel to receive and complete the second scan. This will mark the end of the package journey.

See attached videos for Supplier App demo:

1. English Version2. Chinese Version3. Bilingual Version

The Participants

https://drive.google.com/open?id=1bGz3ajungsoeSzEAyZ9O_GK-DWu_vu_W

https://drive.google.com/a/tbsx3.com/file/d/1xUm2f4MdQe_IUm_HhQjHNbJV6lx-E3ZY/view?usp=sharing

https://drive.google.com/a/tbsx3.com/file/d/1hn7xRD5jMjpGhvR782F4GYDmULZ_WFxc/view?usp=sharing

Login Scan Positive Result Negative Result

Product Info Delivery History View Map Scan History

Consumer App A free and user friendly app customers can use to scan the QR code on the item to check its authenticity, its origin, and its journey along the supply chain. Simple results will notify the customer if the item truly is genuine, or not what it claims to be.

Below are samples of how a Macka’s Consumer App looks like

Macquarie University - Introduction · Web viewthe supplier and the country of origin. For example,...

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