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.

Tourism and logistics in an age of unprecedented crime

2017 ◽  
Vol 9 (1) ◽  
pp. 86-94 ◽  
Author(s):  
Richard Bennett
Keyword(s):  
Structured Interviews ◽  
Social Implication ◽  
Logistics Industry ◽  
Content Type ◽  
International Trends ◽  
The Caribbean ◽  
The Government ◽  
Global Arena ◽  
The Impact

Purpose This paper aims to examine the positioning of tourism and logistics and the related impact of crime. Design/methodology/approach The study is exploratory in nature and draws extensively on related literature. Data were obtained through primary sources (semi-structured interviews, observation) and additionally draw on the researcher’s own professional experience. Findings The findings suggest that both tourism and logistics need a more rigorous security infrastructure and support to keep pace in the current global arena where the range and scale of crime is unprecedented. Research limitations/implications The limitation of this study is that the focus is specifically on the Caribbean – though the situation in the Caribbean is no different from international trends. Practical implications Jamaican society has been impacted by different forms of crime (drugs, domestic and political) over the past three decades. While tourism has been the major source of foreign exchange for the island, little attention has been given to the impact of crime on tourism. Logistics, like tourism, has been premised as the next agenda for economic growth for the island. Similar to tourism, security has not been emphasized in the promotion of the logistics hub. Therefore, the role of security should be a priority agenda for the country as it works towards establishing a global logistic hub. Social implications The social implication of this study is to sensitize both the government and local people on the importance of the tourism and logistics industry and the role that security will play in their sustainability. The proposed logistics hub and the special economic zones will probably double the employment opportunity provided by tourism. Finally, the paper will help inform government policy both at the national and local levels on attitudes to national and private security. Originality/value Little has been written on the role of security in tourism and logistics in the Caribbean. As a result, this paper is timely and makes a fresh contribution to what is known on the subject matter.

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

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.

Empirical analysis of integration practices among agribusiness firms

2019 ◽  
Vol 25 (7) ◽  
pp. 1696-1715
Author(s):  
Michael Kwamega ◽  
Dongmei Li ◽  
Eugene Abrokwah
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Direct Interaction ◽  
Mediating Effect ◽  
Data Set ◽  
Content Type ◽  
Internal Customer ◽  
Using Data ◽  
The Relationship ◽  
Positive Effect

Purpose The purpose of this paper is to investigate the mediating effect of information sharing (IS) on the link between supply chain integration (SCI) practices (internal, customer and supplier) and internal process performance (IPP) by using selected agribusiness firms from an emerging economy, Ghana. Design/methodology/approach To determine the effect of IS on the nexus between SCI practices and IPP, a research framework was developed and tested using data amassed from 156 agribusiness firms for the study. The data set was assessed and hypotheses were tested using structural equation modelling. Findings The outcomes revealed that both INI and CI positively and significantly influenced IS. However, the results disclosed that SI has no significant positive effect on IS among the Ghanaian agribusiness firms. The findings of the study further discovered that IS fully mediates the relationship between INI, CI and IPP, whereas SI has a direct interaction with IPP. Originality/value This study contributes to the existing supply chain management research by empirically authenticating IS as the mediator between SCI practices and IPP. From the viewpoint of a developing economy, this paper identifies the significant connection that exists between SCI practices, IS and IPP. The outcomes recommend that IS is a core driving facilitator to reinforce the correlation between SCI practices and IPP.

IoT ecosystem faces fragmented future

2019 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Internet Of Things ◽  
Data Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Content Type ◽  
Iot Devices ◽  
The Internet Of Things

Subject IoT ecosystem. Significance The market for the Internet of Things (IoT) or connected devices is expanding rapidly, with no manufacturer currently forecast to dominate the supply chain. This has fragmented the emerging IoT ecosystem, triggering questions about interoperability and cybersecurity of IoT devices. Impacts Firms in manufacturing, transportation and logistics and utilities are expected to see the highest IoT spending in coming years. The pace of IoT adoption is inextricably linked to that of related technologies such as 5G, artificial intelligence and cloud computing. Data privacy and security will be the greatest constraint to IoT adoption.

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.

Supply chain collaboration in performance-based contracting: an empirical study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hasan Uvet ◽  
Hasan Celik ◽  
Sedat Cevikparmak ◽  
Saban Adana
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Convincing Evidence ◽  
The Body ◽  
Amazon Mechanical Turk ◽  
Equation Modeling ◽  
Supply Chain Collaboration ◽  
Content Type ◽  
Using Data ◽  
The Impact

PurposeDespite the significant increase in the adoption of performance-based contracting (PBC) in various industries, the primary value drivers of it are still not clear. Considering a lack of empirical evidence for PBC, this study investigates the effects of collaboration between the suppliers to understand the value offerings created in PBC by empirical findings. The purpose of this paper is to examine how supply chain collaboration (SCC) affects PBC benefits.Design/methodology/approachUsing data from 381 survey participants who hold the title of manager or above, hypotheses are tested using structural equation modeling (SEM).FindingsThe results reveal that a strong and positive relationship between SCC and PBC benefits.Research limitations/implicationsOne of the limitations of this research is the collection of data through the Amazon Mechanical Turk online service. The experience level of participants in PBC and the absence of validation of these scale items by industrial experts are other limitations of this study. Nonetheless, the authors found convincing evidence that SCC has a positive effect on PBC benefits.Practical implicationsThe findings highlight the importance of SCC to increase financial, operational and non-financial benefits of PBC for practitioners. The findings offer guidance for managers aiming to increase PBC benefits through SCC.Originality/valueThis is the first study to empirically examine the impact of SCC for better PBC and contributes to the body of knowledge by providing empirical findings in a PBC context. This research also develops valid and reliable instruments to measure PBC benefits through rigorous empirical and statistical analysis that can be used in future studies.

Managing firm risk through supply chain dependence: an SME perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Feng Liu ◽  
Kwangtae Park
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
Credit Rating ◽  
Emerging Market ◽  
Firm Risk ◽  
Content Type ◽  
Industrial Marketing ◽  
Customer Dependence ◽  
Using Data ◽  
The Impact

Purpose The purpose of this study is to conduct an empirical investigation into the impact of supply chain dependence (including customer dependence and supplier dependence) on credit risk through the lens of social network theory (SNT) by focusing on how to manage firm risk using supply chain relationships in the context of Chinese small and medium-sized enterprises (SMEs). Design/methodology/approach Using data from public databases, this study selects a unique sample from a Chinese SME board and uses an ordered logistic regression model to investigate the relationship between the dependence on major customers or suppliers and both credit risk and credit rating. It is found that the results are robust to the use of different empirical methods. Findings The main findings of this study are that a firm’s dependence on major customers is positively related to its credit risk but negatively related to its credit rating, while a firm’s dependence on major suppliers is positively related to its credit risk but negatively related to its credit rating. Originality/value To broaden the understanding of industrial marketing and purchasing, this study contributes to research on supply chain relationship management and risk management by focusing on SMEs’ dependence on major customers and suppliers and empirically examining the influence of this dependence on both credit risk and credit rating in an emerging market.

A new approach for estimating leagile decoupling point using data envelopment analysis

2016 ◽  
Vol 36 (3) ◽  
pp. 233-245 ◽  
Author(s):  
Arash Shahin ◽  
Angappa Gunasekaran ◽  
Azam Khalili ◽  
Hadi Shirouyehzad
Keyword(s):  
Supply Chain ◽  
Dynamic Performance ◽  
Data Envelopment ◽  
New Approach ◽  
Content Type ◽  
Agile Processes ◽  
Efficiency And Effectiveness ◽  
Public Responsibility ◽  
Using Data

Purpose This paper aims to propose a new approach for determining a decoupling point in leagile chain, based on Lean and agile criteria regarding market and customer demands and internal capabilities of the chain with the ultimate goal of fulfilling customer needs and increasing chain profit. Design/methodology/approach In the new approach, Lean and agile criteria have been defined for assessing the effectiveness and efficiency of supply chain. The efficiency and effectiveness ratios have been calculated for Lean and agile processes using input- and output-oriented Banker, Charnes and Cooper (BCC) methods, respectively. Based on the results, inefficient and ineffective units have been addressed and the decoupling point has been determined. Findings Findings indicate that the decoupling point can be regarded as a borderline between two strategies of Lean and agile production, and fuzzy decoupling point and lean–agile distance can provide the basis for distinguishing the two strategies. Practical implications Determining the decoupling point has an important role in dynamic performance of a supply chain. By the proposed approach, managers can estimate the most probable area for the decoupling point. Moreover, by appropriate determination of decoupling point, an organization can increase its public responsibility by appropriate usage of its resources and responding faster to customers’ requirements. Originality/value In this study, in addition to determining a decoupling point in a supply chain with the aim of increasing productivity, the subject of leagile strategy of supply chains has been developed.

The contemporary state of big data analytics and artificial intelligence towards intelligent supply chain risk management: a comprehensive review

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Harsh M. Shah ◽  
Bhaskar B. Gardas ◽  
Vaibhav S. Narwane ◽  
Hitansh S. Mehta
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Research Directions ◽  
Content Type ◽  
Future Research Directions

PurposeThis paper aims to conduct a systematic literature review of the research in the field of Artificial Intelligence (AI) and Big Data Analytics (BDA) in Supply Chain Risk Management (SCRM). Finally, future research directions in this field have been suggested.Design/methodology/approachThe papers were searched using a set of keywords in the SCOPUS database. These papers were filtered using the Title abstract keywords principle. Further, more papers were found using the forward-backward referencing method. The finalized papers were then classified into eight categories.FindingsThe previous papers in AI and BDA in SCRM were studied. These papers emphasized various modelling and application techniques for AI and BDA in making the supply chain (SC) more resilient. It was found that more research has been done into conceptual modelling rather than real-life applications. It was seen that the use of AI-based techniques and structural equation modelling was prominent.Practical implicationsAI and BDA help build the risk profile, which will guide the decision-makers and risk managers make their decisions quickly and more effectively, reducing the risks on the SC and making it resilient. Other than this, they can predict the risks in disasters, epidemics and any further disruption. They also help select the suppliers and location of the various elements of the SC to reduce the lead times.Originality/valueThe paper suggests various future research directions that fellow researchers can explore. None of the previous research examined the role of BDA and AI in SCRM.

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