Supply Chain Management Technology Research Articles

Integrity and Legitimacy of Halal Products: The Urgency of Halal Supply Chain Management Technology Adoption in Halal Product Authentication Traceability Evidence from Indonesia

"Research Aims: This research aims to determine how technology, integrity, and the environment affect traceability of halal product certification and its relationship with Halal Value Chain (HVSC) Management in micro, small and medium processing industries. Design/Methodology/Approach: The quantitative research utilised survey data from 285 respondents who are processing industry players throughout Indonesia. Structural Equation Modelling-Partial Least Square (SEM-PLS) is applied for data analysis. Research Findings: The study's findings indicate that technology adoption and environmental factors have a significant effect on HVSC traceability. The authentication and legitimacy of halal products are positively impacted by technology adoption, among others, which contributes to the overall product integrity. The research findings also indicate government support as an important factor. Theoretical Contribution/Originality: This research is one of the first studies related to supply chain legitimacy and authentication in the context of micro, small, and medium businesses in Indonesia, a country with a Muslim majority and many micro-businesses where these businesses have direct contact with “from farm to fork or table” end customers. Managerial Implication in the South East Asian Context: This research offers valuable contribution for managers and policymakers in South East Asia in formulating authentic halal product policies in terms of HVSC. Research Limitations & Implications: This research can benefit from a larger sample size, preferably from larger companies, for generalisation. Moreover, expanding the research across borders and employing a mixed-method approach could offer further insights to overcome supply chain challenges in the future."

Assessing the Impact of Healthcare 4.0 Technologies on Healthcare Supply Chain Management: A Multi-Criteria Evaluation Framework

Background: Healthcare 4.0 has transformed supply chain management in the healthcare sector, but there is a lack of comprehensive frameworks to evaluate the impact of Healthcare 4.0 technologies on sector operations, particularly in developing countries. Methods: This study introduces a multi-criteria framework that synergically combines the techno-economic implications of Healthcare 4.0 technologies to improve healthcare supply chain management. The proposed approach innovatively integrates fuzzy VIKOR and Entropy methods to handle data vagueness and uncertainty, using data collected from healthcare supply chain specialists in Lagos, Nigeria. Results: The developed framework identifies the most and least critical technical and economic parameters for Healthcare 4.0 implementation in healthcare supply chain management. It also determines the suitability of different Healthcare 4.0 technologies for supply chain management in the healthcare sector. Conclusions: The main innovation of this study lies in the development of a comprehensive and context-specific framework for evaluating Healthcare 4.0 technologies in healthcare supply chains. The framework offers a new perspective on technology evaluation and provides practical insights for decision-makers. The findings contribute to advancing knowledge and practice in this field, promoting the proper adoption of Healthcare 4.0 technologies in healthcare, particularly in developing countries.

A Bibliometric Literature Review of Digital Supply Chain: Trends, Insights, and Future Directions

This paper presents a comprehensive bibliometric literature review that aims to analyze and synthesize the existing research on the digital supply chain. By employing a bibliometric approach, this study provides insights into the trends, key research themes, influential authors, and relevant journals in the field of DSC. Furthermore, it explores the geographical distribution of publications, collaboration networks among researchers, and the evolution of research topics. The comprehensive bibliometric analysis of literature in DSC is performed through data visualization and content analysis. Data visualization enables the analysis of publication performance and science mapping by examining prolific journals, authors, countries, influential papers, and conducting citation, co-citation, and bibliographic coupling analyses. Content analysis is carried out by examining the occurrence and clustering of textual data. The bibliometric literature review and content analysis were carried out on 114 documents indexed in the Scopus database, which were selected using the Prisma protocol. The data visualization analysis of the literature review through VOSviewer draws the landscape of scholarly research in the digital supply chain. Based on the research landscape, the content analysis demonstrates the significant effects that the incorporation of digital technology into supply chain management has had on several important research topics. The main research trends in digital supply chain according to the content analysis are: intelligent supply chain management, technologies to drive supply chains performance, circular supply chains, information reliability in supply chains, and sustainable supply chains. The findings of this review highlight the transformative potential of digital technologies in supply chain management and its performance optimization.

Integration of robotics and automation in supply chain: a comprehensive review

Robotics and automation have developed as key technologies for supply chain management as a result of the increased demand for quicker and more effective supply chains. Robotics and automation improve supply chain management by lowering long-haul expenses, boosting work and usage strength, reducing errors, declining repetitive stock checks, updating orchestrating, taking care of times, and assembling induction to the problematic and hazardous places. Robotics aids in design, creation, etc. Automation helps to do tasks that are often done by people through the use of self-operating physical machines, computer software, and other technology. Despite being widely accepted as a tool to aid in decision-making, supply chain management (SCM) has very seldom used AI and ML. This article investigates several AI and ML sub-fields that are best suited for resolving real-world SCM-related issues in order to fully realize the potential benefits of AI and Ml for SCM. In doing so, this article examines the track record of successful AI and ML applications to supply chain management and highlights the most fruitful SCM domains to apply AI and ML. And also find out the how robotics and automations helps in warehouse management. The most recent developments in robotics and automation for supply chain management are thoroughly reviewed in this paper. We first give a general overview of the difficulties that supply chain management faces before going over the many ways that robotics and automation are used at various points along the supply chain. Additionally, we go over the advantages of robots and automation in supply chain management, including higher efficiency, accuracy, lower costs, and improved safety. Lastly, we discuss some of the present drawbacks and difficulties associated with robots and automation in supply chain management and suggest some possible directions for further investigation.

Supply chain risks in the age of big data and artificial intelligence: The role of risk alert tools and managerial apprehensions

As supply networks become more complex and international, the task of controlling associated risks becomes more difficult. This article investigates the usefulness of risk alert technologies in supply chain management, with a focus on Big Data Analytics (BDA) and Artificial Intelligence (AI). The study investigates the impact of BDA capabilities, solid IT infrastructure, managerial views, and AI-apprehensions on the effectiveness of risk alert tools using a questionnaire-based survey of 420 managerial personnel and Structural Equation Modeling (SEM) via SMART PLS. The work proposes the concept of AI-Apprehensions as a moderating variable, which is a relatively unexplored field. According to the findings, while BDA capabilities and IT infrastructure considerably improve the effectiveness of risk alert tools, AI-apprehensions can negate these advantages. The study provides useful insights for policymakers and practitioners, emphasizing the importance of balancing technical and human components for effective risk management.

Digital supply chain: literature review of seven related technologies

This paper systematically reviews literature related with digital supply chains (DSC) and investigates the application status and development trend of different digital technologies in supply chain management. The review is conducted from the perspective of seven key digital supply chain technologies, i.e. Internet of Things (IoT) & Radio Frequency Identification (RFID), 5th Generation Mobile Communication Technology (5G), 3D Printing, Big data (BD), Blockchain, Digital Twins (DT), and Intelligent autonomous vehicles (IAVs). It highlights the main limitations and opportunities of the various DSC technologies, provides an overview of prior studies, and identifies knowledge gaps by outlining the advantages, weaknesses and restrictions of individual technology. The paper also aims at providing a development framework as a roadmap for the match of different digital technologies with different strategic goals.

Digital Technology for Supply Chain Management- marketing Integration

Abstract The aim of this document is to present a full description of the innovative efforts that have been made over time to develop digital technologies to manage the interfaces between supply chain management and marketing processes, and beyond that the role they play in maintaining supply chain management and marketing (SCM-M). The methodology used is patent analysis, which collects data from six different offices (USA, China, Taiwan, Japan, South Korea and Germany) and uses real samples to perform this analysis. The research also learned of a number of key security technologies related to the Fourth Industrial Revolution (Industry 4.0) that are considered more relevant for the effective integration of SCM-M (i.e.me. Industrial Internet of Things and Cloud Computing). The results of this study provide detailed information on the digital technologies that support SCM-M integration. Concretely, the authors compose the role dispute related to information, storage and elaboration for the integration of SCM-M by wishing on illustrative realities. In addition, the authors present the organizations most involved in the development of digital technologies for SCM-M integration over time and provide evidence of the impact of these technologies in terms of their impact on resulting technology developments. JEL classification numbers: J43. Keywords: Innovation, Marketing, Supply Chain Management, Internet of Things, Cloud Computing, Patent Analystics, Industry 4.0, Integration marketing-supply chain management.

Key Variables Influencing Artificial Intelligence (AI) Implementation In Supply Chain Management (SCM): An Empirical Analysis On Smes

This study seeks to ascertain the principal elements influencing the application of Artificial intelligence (AI) and how the application of AI affects supply chain management (SCM) performance. During the industrial development period, the use of new technologies in supply chain management is important. A more thorough analysis of the problems with supply chain, AI implementation will offer a more unbiased viewpoint on the difficulties and advantages of integrating AI into SMEs' supply chain management. To achieve the research objectives, representative factors for variables were identified and the acceptability of the study sample was evaluated utilizing the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphere city. Regression Analysis was used to test the proposed hypotheses and to validate the conceptual model.
 The results indicated that the Managerial Support (MS), Competitive Pressure (CP), Government Support (GS), Vendor Partnership (VP), Compatibility (COMPA), and Relative Advantage (RA) factors are essential in AI implementation. The beta values of all the factors, as indicated by the coefficient, are 0.939[1], 0.367, 0.240, 0.249, 0.190, and 0.161 respectively, which is a reasonable representation of their influence on SCM Performance (SCMP) and AI Implementation (AIIM). The study findings show that variables influence the decision to implement AI applications in supply chain management. Examining these variables is anticipated to have a positive impact and assist strategic planners in developing plans to use AI to support the operational requirements of the company both now and in the future. Research findings have aided companies in realizing the value of artificial intelligence, developing strategies and plans to swiftly transition to digital technology, and streamlining workflows to improve supply chain efficiency.

Industry 4.0 in “Major Emerging Markets”: A Systematic Literature Review of Benefits, Use, Challenges, and Mitigation Strategies in Supply Chain Management

The extant literature does not provide consolidated knowledge on the use of Industry 4.0 in supply chains of emerging markets. This systematic literature review investigated the benefits, use, challenges, and mitigation measures related to Industry 4.0 technologies in supply chain management within thirteen “major emerging markets”. Industry 4.0 integrates technologies such as the Internet of Things (IoT), big data analytics, and cloud computing, and it offers tangible benefits for manufacturing and supply chains. However, its adoption faces significant obstacles, particularly in emerging economies. This study used the PSALSAR framework and PRISMA methodology to systematically review 87 peer-reviewed research articles on Industry 4.0 in the supply chain context of thirteen major emerging economies. Findings revealed that while IoT, big data, and artificial intelligence are frequently applied, other technologies such as cloud computing and robotics are underutilized. Key challenges identified include data integration, cyber-security, high upfront investment, weak policy, and business risks. Mitigation strategies proposed include the development of supportive policies, management backing, training, and improved data security. Tangible benefits such as sustainably using resources, reducing power use, enabling collaboration among supply chain partners, incorporating asset traceability, and minimizing meat contamination were evident. This research provides useful insights into the current status of Industry 4.0 adoption in emerging markets, helping stakeholders to navigate towards a more digitized, efficient future.

Research on Improvement of Hotel Supply Chain Resource Management Decision in the Era of Big Data

Hotel supply chain management (SCM) refers to the material service that takes a hotel as the core object. At present, the main method is centralized SCM, which uses integer programming or mixed integer programming to establish and solve the allocation management of various resources among hotels in the supply chain. In this article, based on ant colony algorithm (ACA), the hotel SCM mode is studied and optimized. The research shows that the convergence path is A-S4-M3-L3-D1-R1-T. Therefore, the optimal partner combination meeting the requirements of the supply chain is S4, M3, L3, D1 and R1. The experiment shows that the max-min ACA is effective to solve the problem of partner selection in hotel supply chain. By using enterprise management technology, information technology, network technology and SCM technology under ACA, the effective rules and control of information flow, logistics, capital flow, business flow and value flow in the whole supply chain can be achieved, and the maximum benefit of the whole hotel supply chain can be realized.

Digital technology and its application in supply chain management: new evidence from China's economy.

The purpose of this article is to investigate the influence that practices using information technology (IT) have on the development of a competitive advantage across the supply chain. An organization has a competitive advantage when it has qualities that give the required foundations for it to separate itself from other organizations that are also in its industry. Pressure is applied to the corporate environment as a result of competition and ongoing changes, such as the introduction of new products and technical advancements, the decline of product lifestyles, and the proliferation of products. In order to maintain a competitive edge and achieve financial success in business, organizations are necessary for responding to changes in the market. Through the use of supply chain markets, companies are able to react quickly to unforeseen shifts in the market, and these shifts may be turned into lucrative business possibilities. One of the most significant things that firms can do to assist themselves is make use of information technology to improve their supply chain management agility. From March 2021 through January 2022, the area of China will have a total sample size of 247 persons fill out a questionnaire as part of the data collection process. In each and every questionnaire, the measurements were taken using a Likert scale with five points. The partial least square-structural equation modeling (PLS-SEM) approach is used to the causal model in order to assess the model's reliability and validity. This technique is used to evaluate the causal model. The findings indicate that information technology has a favorable impact on the adaptability of supply chain management systems. In addition, the findings that were collected have shown that there are four factors that influence the SCM systems. These factors are the IT skills and knowledge, the integration of IT-based systems, the IT infrastructure, and the design of global position system and geographic information systems. In addition, this research offers practitioners recommendations for implementing digital technology for supply chain management and building suitable business strategies at various stages of digitalization.

The Impact of Green Supply Chain Management on Long-term Effectiveness of Enterprises

Due to the expansion of the economy and society, higher standards have been proposed for the growth of enterprises. More and more attention has been paid to the sustainable development of enterprises. The shortage of resources and environmental pollution are another challenge for manufacturing enterprises, requiring businesses to give environmental issues more consideration modern management practices such as green supply chain management take the entire supply chain into account when making decisions. It incorporates suppliers, manufactures, sellers and users and is based on the principle of green manufacturing and supply chain management technologies. Its goal is to reduce environmental impact of the entire process of purchasing, processing, packing, storing, moving, using, and discarding products. This article begins with the meaning of supply chain management, examines the fundamental components of a green supply chain, elaborates on the implementation of a green supply chain, discusses the challenges a green supply chain faces in China, and then proposes green supply chain management strategies.

The role of blockchain technology in the sustainability of supply chain management: Grey based dematel implementation

Decentralized, transparent, immutability, irreversible, autonomy, open source, anonymity, ownership and uniqueness, source, contract automation are at the forefront of the features that allow blockchain technology to be accepted within the sectors. Thanks to these features, it has an important potential in terms of applicability, as well as in supply chain management, as in many other fields. In this study, the compatibility and impact level of the features of blockchain technology with the sustainability of supply chain management are investigated. Within the scope of supply chain management, effective information sharing, integration between processes, trustworthy, systematic data management, auditability, transparency, strong relationship between stakeholders, high efficiency, quick answer, ability to increase sustainability, transition to digitization, uncertain legal status, new technology, integration compatibility with other technologies, optimizing time parameters are evaluated. In the results obtained with the Grey Relational Analysis-based DEMATEL method, effective information sharing, integration between processes, systematic data management, quick answer, uncertain legal status, new technology, and integration compatibility with other technologies are included in the group affecting other criteria. Within the scope of the study, the characteristic features of blockchain technology for supply chain management are interpreted with relationship map and graph diagram. The study provides both theoretical and practical contributions by drawing attention to the compatibility of the blockchain in supply chains, and guides the employees in the supply chain line on how they can best guide their companies and on which parameters they can gain by enabling them to adopt blockchain technology. With blockchain technology, it offers the opportunity to achieve higher efficiency with less time, less cost and faster response, which can realize its sustainability mission, which includes each of the economic, social and environmental dimensions.

Mapping the Evolution of the European Union Retail Supply Chain Technology Management: A Bibliometric Analysis

Effective supply chain management (SCM) technology is crucial for the success of retail businesses in the European Union (EU). This research thesis aims to employ bibliometric analysis to provide a comprehensive examination of global contributions and contemporary keyword trends in the field of SCM technology within the EU. Using the Web of Science database, a systematic search was conducted, resulting in a total of 3,173 relevant articles. Bibliometric Analysis and VOSviewer (VOS) were employed to analyze the research landscape. The analysis shows that although this topic is based on the European Union, the scientific productivity and influence on the topic from China, Britain and the United States are higher than that of many EU countries. The European Journal of Operational Research emerged as the most influential journal in terms of both productivity and impact. Affiliations primarily consisted of universities, with a significant contribution from five universities showing consistent growth in research productivity. The results of Network visualization and Thematic Map analysis results of keywords show that technology-based red keyword clustering is very important for the research in this field, including demand response, microgrids, algorithms, price, policies, simulation and so on. This analysis highlights the importance of technology-related topics in the supply chain of EU retailers.

Digital transformation of supply chain management in retail and e-commerce

PurposeThe purpose of studying digitization transformation of the supply chain is to understand how digital technologies and processes are changing the way supply chains operate and to identify the opportunities and challenges associated with this transformation. Studying digitization transformation of the supply chain is important because it can help global businesses in identifying the best practices in supply chain management (SCM) systems and enhance supply chain performance. Hence, this research study is contributing in revealing the outcomes of digital inclusiveness in overall SCM for the growth of retail and e-commerce based platforms.Design/methodology/approachThis research is using both descriptive and explanatory research designs to provide a comprehensive understanding of the problems in SCM. Descriptive research provides a detailed description of the characteristics of the population under study, while explanatory research identifies the causal relationships between the variables. Descriptive research has helped us to develop hypotheses about the relationships between variables that can be tested using explanatory research. Explanatory research has been used to validate the findings of descriptive research. By using both descriptive and explanatory research designs, our research design has increased the generalizability of our findings.FindingsAccording to this study, businesses intend to change their supply chain strategies after the wake of competitive era to make them more robust, sustainable and collaborative with suppliers, customers and stakeholders by investing more in SCM technology like Blockchain, AI, analytics, robotic process automation and data control centers. This study evaluates the impact of digitization on supply chain systems. This includes assessing the benefits of digitization and identifying the factors that contribute to successful implementation. This research is studying the role of data analytics in SCM and how it can be leveraged to improve efficiency, reduce costs and increase transparency.Research limitations/implicationsThe study highlights the importance of adopting digitization in supply chain systems to improve supply chain robustness, sustainability and collaboration with stakeholders. This study's emphasis on data analytics in SCM presents an opportunity for businesses to gain insights into their supply chain systems and make data-driven decisions. This can enhance efficiency, reduce costs and improve overall supply chain performance. The study's focus on SCM technology and data analytics may overlook other factors that contribute to successful SCM, such as organizational culture, human resources and supply chain governance.Originality/valueThis study will complement to the existing body of information, management theory and practice and will benefit all. The research work is original and can be implemented worldwide to promote digitization in SCM for smooth transactions in the entire chain of wholesalers, retail distributors and customers.

Big data ethics and its role in the innovation and technology adoption process

PurposeUpon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making.Design/methodology/approachThis paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment.FindingsFour main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions.Originality/valueThree notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.

Industry 5.0 and Triple Bottom Line Approach in Supply Chain Management: The State-of-the-Art

Digital technologies could be key to solving several open issues in the context of supply chain management (SCM) and sustainable development. The purpose of this article is to investigate the linkage between digital technologies and sustainable practices in SCM. Through a systematic literature review, the article aims to identify which technologies favour sustainable emerging practices considering the triple bottom line (3BL) perspective. In particular, the following 11 technologies were considered: 3D printing, artificial intelligence, blockchain, computing, digital applications, geospatial technologies, Internet of Things, immersive environments, open and crowd-based platforms, proximity technologies and robotics. For the purpose of this research, 5011 peer-reviewed scientific articles were analysed and a comprehensive overview of the use of digital technologies in SCM to favour sustainable emerging practices was proposed. Therefore, four indices that measure the environmental, social, economic and total 3BL sustainability of each technology were used to assess sustainable emerging practices. This study could be useful for both academics and practitioners. For the former, it provides a comprehensive understanding of the application of digital technologies in sustainable emerging practices for SCM. It highlights potential research gaps by proposing scenarios of future research developments. For the latter, the article aims to identify opportunities for the implementation of digital technologies within own company to improve operations management and, at the same time, promote sustainable development.

Critical Success Factors for 5G Technology Adaptation in Supply Chains

The present age is moving through Industry 4.0 with massive technological developments. Supply chains have become digital, keeping sync with consumer demands and preferences. The recent pandemic has reinforced the need of embracing digital technologies in managing supply chains effectively. Therefore, it is necessary that supply chains adopt 5G mobile technologies. In this regard, the present study aims to discern the critical issues for the successful adaptation of 5G technologies for supply chain management (SCM) in developing countries such as India. The success factors for the adaptation of 5G in Indian supply chains are derived from the discussions made in the related past work regarding the challenges of implementing 5G technology. Then, the listed factors are finalised through initial rounds of face-to-face discussions with a focus group of five experts. Then, a q-rung-orthopair-fuzzy (qROFS)-based rating scale is used to rate the success factors. A new qROF-weighted-neutrality-average (q-ROFWNA)-based full-consistency method (FUCOM) approach for multicriteria decision-making (MCDM) problems involving group decision making is utilised to find out the critical success factors. Based on the comparative analysis of 17 success factors (grouped into four main factors), the spectrum availability, awareness of technology and usage, the development of supporting technologies and smart cities, and skill development are found to be the top five critical factors for the successful adaptation and implementation of 5G technologies in SCM. We further carry out a sensitivity analysis and validation test and observe that our model provides a reliable and stable solution.

An Empirical Study on Factors Impacting the Adoption of Digital Technologies in Supply Chain Management and What Blockchain Technology Could Do for the Manufacturing Sector of Bangladesh

ABSTRACT This paper employed an integrated model for examining behavioral intention to adopt blockchain technology in the supply chain management of manufacturing industries in Bangladesh. The proposed conceptual model was empirically tested using data collected from 189 supply chain managers working in manufacturing organizations in Bangladesh. The findings suggest that perceived usefulness, trading partners’ pressure, and competitive pressure are the most important determinant of behavioral intention.

Blockchain technology for supply chain management in the context of AI-based solutions

Purpose: The purpose of the article is to emphasize the growing popularity of using tools based on artificial intelligence and blockchain technology in supply chain management, as well as to show the synergistic potential of using them together. Additionally, the author aims to present and discuss the concept of using both technologies for the purposes of constructing an ordering goods system in the supply chain based on AI tools supported by blockchain technology. Design/methodology/approach: The purposes of the paper were achieved by analyzing literature, industry reports and online publications in the field of blockchain technology and artificial intelligence in supply chain management. The theoretical scope of the article is the description of application areas of both described technologies within the supply chain, their main characteristics and the potential for synergy in their combined use. Findings: The author presented the results of the analysis of literature, industry reports and online publications, demonstrating the growing popularity of the use of blockchain technology and artificial intelligence-based tools in supply chain management, characterized key features of analyzed technologies, comparing them on the basis of opposites, and indicated their resulting synergistic potential. Drawing conclusions from this potential, the author indicated the possibility of using both technologies together as part of the blockchain-AI supported ordering system's concept. The article ended with the author's suggestions regarding the potential of future research aimed at concretizing the proposed concept and looking for opportunities to decentralize AI tools used so far based on their support with blockchain technology. Practical implications: The use of blockchain technology and tools based on artificial intelligence in business shows measurable benefits, as shown by the submitted analysis of industry reports. Observed increasing adoption of both technologies contributes to cost decrease and revenue increase in many industries as shown in the paper. Originality/value: The originality of the paper consists in comparing the opposites and drawing conclusions regarding the potential complementarity of the features of both analyzed technologies, and is also expressed in the proposed concept of Blockchain-AI supported ordering system. Keywords: distributed ledger technology, blockchain, artificial intelligence, supply chain management. Category of the paper: Research paper.