Using AI and ML to predict shipment times of therapeutics, diagnostics and vaccines in e-pharmacy supply chains during COVID-19 pandemic

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahesh Babu Mariappan ◽  
Kanniga Devi ◽  
Yegnanarayanan Venkataraman ◽  
Ming K. Lim ◽  
Panneerselvam Theivendren
Keyword(s):  
Supply Chain ◽  
Real World ◽  
Stochastic Gradient Descent ◽  
Clear Trend ◽  
Logistics Industry ◽  
Content Type ◽  
Time Prediction ◽  
Supply Logistics ◽  
Historic Data ◽  
Fold Cross Validation

PurposeThis paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.Design/methodology/approachThe present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.FindingsThe findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.Research limitations/implicationsThe implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.Originality/valueThe novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

Blockchain technology development and implementation for global logistics operations: a reference model perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rukshanda Kamran ◽  
Nasreen Khan ◽  
Balan Sundarakani
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Reference Model ◽  
Process Efficiency ◽  
Future Research ◽  
Logistics Industry ◽  
Content Type ◽  
Traceability System ◽  
Blockchain Technology ◽  
Global Logistics

Purpose Blockchain technology offers a lot of potential benefits in supply chain management. However, there is a need of a reference model which addresses the gaps in existing frameworks. This paper aims to propose a blockchain technology-based reference model which can be applied to global logistics operations. Design/methodology/approach The researchers have integrated the fit-for-purpose theoretical framework and prototyping methodology to design the reference model, a blockchain-based logistics, tracking and traceability system (BLTTS). The researchers demonstrated the application of the reference model through a health-care supply chain case study. The proposed BLTTS can be implemented across global logistics operations for business performance improvement. Findings The research provides a framework and recommendations for global companies to consider when adopting the blockchain technology for implementation. The researchers found that the Ethereum blockchain technology improves security of the data shared within the block through the secure hashing algorithm 1. The hash algorithm ensures anonymity of the involved parties. The model integrates blockchain with supply chain thus creating transparent process, efficiency and real-time communication. Research limitations/implications The reference model will offer a better solution to global logistics operations challenges. It provides recommendations to key stakeholders involved in logistics operations segment of the logistics industry while adopting blockchain technology. Apart from the methodological limitation of the study, the system compatibility and the layer configuration aspects might be posing potential challenges while upscaling the implementation. Originality/value The proposed reference model overcomes the drawbacks of existing models as it integrates Ethereum technology. In addition, the researchers have applied the model to demonstrate its functioning in real-time environment, which could guide for future research.

Impact of knowledge management capability on supply chain management and organizational practices in logistics industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nurhidayah Bahar ◽  
Siti Norida Wahab ◽  
Mahfuzur Rahman
Keyword(s):  
Knowledge Management ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Organizational Performance ◽  
Logistics Industry ◽  
Chain Management ◽  
Content Type ◽  
Management Capability ◽  
Knowledge Management Capability ◽  
The Impact

Purpose This paper aims to examine the impact of knowledge management capability (KMC) on supply chain management practices (SCMPs), organizational learning (OL) and organizational performance (OP) in the Malaysian logistics industry. Design/methodology/approach The data were gathered using a self-administered questionnaire from the management team in the logistics companies. A total of 412 questionnaires were collected out of which 183 responses were included in the data analysis. This represents a response rate of 44.4%. The respondents were those with managerial and/or supervisory experience where their job title or functions included Managers, Head of the Department, Owners, Chief Executive Officer, Senior Executive Officer and at the very least, Assistant Manager or Supervisors. To investigate the correlations between all the elements (e.g. KMC, OL, SCMPs and OP), this study used different analysis techniques including correlation analysis, reliability and validity test, as well as a structural model. Findings The results indicated that KMC is strongly correlated and has a positive impact on SCMPs in addition to being positively correlated to OL and OP. Also, OL is positively related to OP and SCMPs. Research limitations/implications The findings of this research contribute to the growing body of literature linking KMC with SCMPs, OL and OP. Practical implications The findings provide insight on the importance of knowledge management and OL toward improving SCMPs within organizations. Therefore, the findings are useful for shedding light upon formulating strategies for SCMPs among the decision-makers that will ultimately enhance the overall OP. Originality/value This study meaningfully contributes to enhancing the understanding of the state of affairs of the impact of management capability on SCMPs, OL and OP in the logistics industry. Practitioners may formulate strategies to further improve the study presented here for a better implementation of knowledge management and SCMPs within their organizations.

Intelligent autonomous vehicles in digital supply chains

2019 ◽  
Vol 25 (3) ◽  
pp. 414-437 ◽  
Author(s):  
Naoum Tsolakis ◽  
Dimitrios Bechtsis ◽  
Jagjit Singh Srai
Keyword(s):  
Supply Chain ◽  
Real World ◽  
Autonomous Vehicles ◽  
Simulation Modelling ◽  
Supply Chain Design ◽  
Supply Network ◽  
Methodological Framework ◽  
Test Bed ◽  
Content Type ◽  
Network Operations

Purpose The purpose of this paper is twofold: first, to discuss key challenges associated with the use of either simulation or real-world application of intelligent autonomous vehicles (IAVs) in supply network operations; and second, to provide a theoretical and empirical evidence-based methodological framework that supports the integrated application of conceptualisation, simulation, emulation and physical application of IAVs for the effective design of digital supply networks. Design/methodology/approach First, this study performs a critical review of the extant literature to identify major benefits and shortcomings related to the use of either simulation modelling or real-word application of physical IAVs. Second, commercial and bespoke software applications, along with a three-dimensional validation and verification emulation tool, are developed to evaluate an IAV’s operations in a conceptual warehouse. Third, a commercial depth-sensor is used as a test bed in a physical setting. Findings The results demonstrate that conceptual and simulation modelling should be initially used to explore alternative supply chain operations in terms of ideal performance while emulation tools and real-world IAV test beds are eminent in validating preferred digital supply chain design options. Research limitations/implications The provided analysis framework was developed using literature evidence along with experimental work and research experience, without consulting any industry experts. In addition, this study was developed based on the application of a single physical device application as a test bed and, thus, the authors should further progress with the testing of a physical IAV in an industrial warehouse. Practical implications The study provides bespoke simulation modelling and emulation tools that can be useful for supply chain practitioners in effectively designing network operations. Originality/value This work contributes in the operations management field by providing both a multi-stage methodological framework and a practical “toolbox” for the proactive assessment and incorporation of IAVs in supply network operations.

The integration of automation and artificial intelligence into the logistics sector

2020 ◽  
Vol 12 (1) ◽  
pp. 56-68 ◽  
Author(s):  
Marshalee N. Foster ◽  
Stephen L.N.H. Rhoden
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Logistics Industry ◽  
Content Type ◽  
Mitigation And Adaptation ◽  
Physical Context ◽  
International Trends ◽  
Repetitive Tasks ◽  
The Caribbean ◽  
Using Data

Purpose Artificial intelligence (AI) and automation are technologies that make a global impact by optimizing manual and time-intensive processes using data analytics and robotics, thus making the task more efficient, effective and less time-consuming. This is represented in the cyber-physical context, in which humans and technologies are allowed to coexist and learn from each other. Design/methodology/approach The logistics and supply chain sector consists of numerous partners and stakeholders, and despite the limited inclusion of automation and AI within the sector, there are still many manual and repetitive tasks. Findings Stakeholders in the logistics and supply chain sector are creating awareness and slowly implementing AI and automation within their operations. The majority of shipping and logistics is done through the maritime sector, and this is expected to increase in line with the world’s population. Research limitations/implications Research was limited to Jamaica and a few other countries in the Caribbean. Broadening the scope to include other regional shipping and logistics industry stakeholders would be helpful. Practical implications The removal of sometimes mundane and even more complex manual processes in the logistics supply chain will give rise to more efficiencies and possibly increased revenue. Social implications Creating awareness in the Caribbean of international trends is a challenge. Empowering people to use automation and AI for the mitigation and adaptation of climate change and other disasters is yet to be fully realized. However, those who took part in the study did show a significant inclination toward the use of automation and AI in their every-day lives. Originality/value The purpose of this paper is to examine statistical data on the understanding of automation and AI within education, the port authority and major operators in the shipping and logistics sector throughout the Caribbean.

Energy-constrained and low-carbon scenarios for the transportation and logistics industry

2016 ◽  
Vol 27 (1) ◽  
pp. 142-166 ◽  
Author(s):  
Heiko A. von der Gracht ◽  
Inga-Lena Darkow
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Alternative Fuels ◽  
Research Question ◽  
Low Carbon ◽  
Logistics Industry ◽  
Content Type ◽  
Supply Chain Strategy ◽  
Future Supply ◽  
Energy Constrained

Purpose – There is consensus among experts that the design of future supply chains will have to focus more strongly on environmental concerns. Sustainability will play a major role within the business and has an impact especially on the distant future. Thus, supply chain executives are challenged in designing sustainable supply chains for the future. The paper aims to discuss this issue. Design/methodology/approach – The authors develop expert-based scenarios, which describe how future supply chains could evolve by 2030. The authors focus on the transportation and logistics industry’s perspective to provide an industry-internal view. The data collection is based on an internet-based Delphi survey. Overall, 48 top executives from 20 countries, representing academic, governmental, and industrial perspectives, participated in the survey. Findings – The authors operationalized the research question into five concrete sub-topics relevant for investigation: energy and emissions, consumer behaviour, future transport modes, design of future supply chains, and innovation. The authors derive five Delphi-based scenarios defined by clusters of their impact and expected probability: measurement and control of CO2-emissions; integrated low energy logistics systems; business-as-usual logistics; no-frills logistics and alternative fuels. Each cluster contributes differently to supply chain strategy. Originality/value – The authors address the major issues and challenges experts expect regarding future supply chains in an energy-constrained, low-carbon world. Five scenario clusters evolved for supply chain strategy development. Finally, the authors make recommendations towards strategic planning in the transportation and logistics industry.

The impact of supply chain relationship quality on performance in the maritime logistics industry in light of firm characteristics

2018 ◽  
Vol 29 (3) ◽  
pp. 1077-1097 ◽  
Author(s):  
Youngran Shin ◽  
Vinh Thai ◽  
Kum Fai Yuen
Keyword(s):  
Supply Chain ◽  
Relationship Quality ◽  
Service Providers ◽  
Firm Characteristics ◽  
Maritime Logistics ◽  
Logistics Industry ◽  
Content Type ◽  
Configuration Theory ◽  
Logistics Service ◽  
The Impact

Purpose Anchoring on configuration theory, the purpose of this paper is to evaluate how supply chain relationship quality (SCRQ) differs across firm characteristics (FC) in the maritime logistics industry. In addition, it utilises transactional cost theory to establish the relationship between SCRQ and supply chain performance (SCP). Design/methodology/approach The data were obtained from a survey with 205 maritime logistics service players (shipping firms, shippers and freight forwarders) in Singapore. MANOVA and t-test analyses are used to examine the difference in SCRQ (i.e. trust and commitment) across FC which includes firm types and ownership types. Thereafter, structural equation modelling is employed to examine the influence of SCRQ on SCP. Findings The results indicate that the effects of trust and commitment on SCRQ vary significantly. It was also found that trust as an aspect of SCRQ has a significant impact on SCP, whereas commitment does not. Research limitations/implications As the field data were obtained from only one industry, future replication of the findings to other industries should consider industry-specific factors, if applicable. Practical implications It is suggested that maritime logistics service players should carefully manage trust and commitment to simultaneously enable SCP. By identifying the various aspects of FC that contribute to SCRQ, maritime logistics service providers could devise appropriate strategies for different customer segments more effectively. Originality/value This study expands current supply chain research by linking two dimensions of SCRQ in relationship marketing with SCP in supply chain management. It is also one of the first empirical attempts to explore the role of FC in the linkage between SCRQ and SCP in the maritime logistics industry.

scholarly journals The physical internet as a new supply chain paradigm: a systematic literature review and a comprehensive framework

2020 ◽  
Vol 31 (2) ◽  
pp. 239-287 ◽  
Author(s):  
Horst Treiblmaier ◽  
Kristijan Mirkovski ◽  
Paul Benjamin Lowry ◽  
Zach G. Zacharia
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Disruptive Innovation ◽  
Logistics Industry ◽  
Content Type ◽  
Journal Publications ◽  
Physical Internet ◽  
Comprehensive Framework ◽  
Conference Papers

PurposeThe physical internet (PI) is an emerging logistics and supply chain management (SCM) concept that draws on different technologies and areas of research, such as the Internet of Things (IoT) and key performance indicators, with the purpose of revolutionizing existing logistics and SCM practices. The growing literature on the PI and its noteworthy potential to be a disruptive innovation in the logistics industry call for a systematic literature review (SLR), which we conducted that defines the current state of the literature and outlines future research directions and approaches.Design/methodology/approachThe SLR that was undertaken included journal publications, conference papers and proceedings, book excerpts, industry reports and white papers. We conducted descriptive, citation, thematic and methodological analyses to understand the evolution of PI literature.FindingsBased on the literature review and analyses, we proposed a comprehensive framework that structures the PI domain and outlines future directions for logistics and SCM researchers.Research limitations/implicationsOur research findings are limited by the relatively low number of journal publications, as the PI is a new field of inquiry that is composed primarily of conference papers and proceedings.Originality/valueThe proposed PI-based framework identifies seven PI themes, including the respective facilitators and barriers, which can inform researchers and practitioners on future potentially disruptive SC strategies.

Transforming information into supply chain agility: an agility adaptation typology

2019 ◽  
Vol 30 (1) ◽  
pp. 329-355 ◽  
Author(s):  
Dawn M. Russell ◽  
David Swanson
Keyword(s):  
Supply Chain ◽  
Information Processing ◽  
Real Time ◽  
Real World ◽  
New Technology ◽  
Research Process ◽  
Business Environment ◽  
Time Data ◽  
Content Type ◽  
Supply Chain Agility

Purpose The purpose of this paper is to investigate the mediators that occupy the gap between information processing theory and supply chain agility. In today’s Mach speed business environment, managers often install new technology and expect an agile supply chain when they press<Enter>. This study reveals the naivety of such an approach, which has allowed new technology to be governed by old processes. Design/methodology/approach This work takes a qualitative approach to the dynamic conditions surrounding information processing and its connection to supply chain agility through the assessment of 60 exemplar cases. The situational conditions that have created the divide between information processing and supply chain agility are studied. Findings The agility adaptation typology (AAT) defining three types of adaptations and their mediating constructs is presented. Type 1: information processing, is generally an exercise in synchronization that can be used to support assimilation. Type 2: demand sensing, is where companies are able to incorporate real-time data into everyday processes to better understand demand and move toward a real-time environment. Type 3: supply chain agility, requires fundamentally new thinking in the areas of transformation, mindset and culture. Originality/value This work describes the reality of today’s struggle to achieve supply chain agility, providing guidelines and testable propositions, and at the same time, avoids “ivory tower prescriptions,” which exclude the real world details from the research process (Meredith, 1993). By including the messy real world details, while difficult to understand and explain, the authors are able to make strides in the AAT toward theory that explains and guides the manager’s everyday reality with all of its messy real world details.

Supply chain processes

2016 ◽  
Vol 36 (2) ◽  
pp. 220-238 ◽  
Author(s):  
Daniel Prajogo ◽  
Adegoke Oke ◽  
Jan Olhager
Keyword(s):  
Supply Chain ◽  
Value Chain ◽  
Lean Production ◽  
Black Box ◽  
Operational Performance ◽  
Competitive Performance ◽  
Content Type ◽  
Chain Processes ◽  
Production Processes ◽  
Supply Logistics

Purpose – The purpose of this paper is to examine the value chain processes that represent the “black box” between supply logistics integration and competitive operational performance in firms. To realize this objective, the authors develop a research model which comprises a series of linkages from supply logistics integration to operational outcomes using Porter’s concept of value chain and the relational view of resource-based theory as theoretical lenses. Design/methodology/approach – The data set for testing the hypothesized relationships in this study was drawn from 232 Australian manufacturing firms. Findings – The findings show that there is no significant direct relationship between supply logistics integration and competitive operational performance; rather, the relationship is fully mediated by inbound supply performance and internal lean production processes. Further, lean production processes have a positive effect on inbound supply performance. Research limitations/implications – The study shows the importance of managing both internal (production processes) and external processes (logistics and supply chain) of firms’ operations in an integrated manner in which supply logistics integration act through key internal processes to impact competitive performance which the end customers actually experience. Originality/value – This is the first study which uncovers what happens “in between” the incoming materials and the end outputs delivered by firms into the market. This “in between black box” is important in improving our understanding of how inbound supply activities are translated into outbound competitive performance outcomes.

Blockchain in logistics industry: in fizz customer trust or not

2020 ◽  
Vol 33 (3) ◽  
pp. 541-558
Author(s):  
Geetika Jain ◽  
Harjit Singh ◽  
K. R. Chaturvedi ◽  
Sapna Rakesh
Keyword(s):  
Supply Chain ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Equation Modeling ◽  
Logistics Industry ◽  
Content Type ◽  
Blockchain Technology ◽  
Convenience Sampling ◽  
Acceptance Model ◽  
Customer Trust

PurposeThe study is an attempt to explore much talked but less understood issue of “blockchain in logistics industry” in modern perspective. The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model” by using attitude, perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention and use behavior.Design/methodology/approachData has been collected through online and offline medium, where active 240 responses have been collected finally using convenience sampling. Confirmatory factor analysis with structural equation modeling (SEM) was carried out for data analysis.FindingsThe customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model.” The findings reveal model fit where PEOU, PU and attitude are the major constructs of the model to realize the substantial gains in logistics process efficiency.Research limitations/implicationsConvenience sampling has been considered for the study to collect the data of online users of various technology applications for tracking and shipment detail, whereas a more specified method sampling can be considered for the future research. The study has been conducted in the Indian context, which has been considered as the limitation pertaining to generalization across countries and industries.Practical implicationsThe findings of this study will be helpful for market practitioners to build transparency between customers and industry to overcome the frictions in logistics. Blockchain will help in monitoring the performance history and previous commitments of logistics professionals resulting in selecting a responsible logistics solution provider. Access to critical data by the authorized member of the supply chain will reduce unsubstantiated disputes.Social implicationsBlockchain technology will be available to everyone on the network. This will bring transparency and help logistics professionals such as carriers, shippers and brokers to detect early frauds and prevent thefts. It will increase customer trust toward any financial transaction for tracking the ownership of titles.Originality/valueBlockchain technology is envisioned to be a technology that could be a game-changer for decentralizing infrastructure, introducing transparency and building trust in the supply chain. The current study is a novel addition to the literature where blockchain technology enables the indisputable storage of verified data that was previously kept in safeguarded silos.

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