Koppiahraj Karuppiah, Jayakrishna Kandasamy, Luis Rocha-Lona, Christian Muñoz Sánchez and Rohit Joshi
Humanitarian supply chain management (HSCM), operating in a complex environment, needs to be agile and robust. The advent of digital technologies has revolutionized HSCM…
Abstract
Purpose
Humanitarian supply chain management (HSCM), operating in a complex environment, needs to be agile and robust. The advent of digital technologies has revolutionized HSCM operations, and thus, this study identifies and evaluates key drivers of artificial intelligence (AI) incorporation in HSCM.
Design/methodology/approach
In total, 20 key drivers were identified through a review of the relevant extant literature and finalized with experts’ inputs using a Likert scale survey. With a Kappa analysis, these drivers were classified into four groups: technical (T), organization (O), human (H) and institution (I). An integrated multi-criteria decision-making (MCDM) method of the Fermatean fuzzy set (FFS) analytic hierarchy process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) was used to rank the key drivers and explore their causal interrelationships.
Findings
Improved performance output, organizational preparedness, user acceptance and continued support, guarantee of job security for technologically semi-skilled workers and government support are the five key drivers of AI incorporation in HSCM.
Originality/value
This study evaluates the key drivers of AI integration in HSCM with FFS-AHP-DEMATEL.
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Keywords
This study aims to understand the role of technology adoption (TA) in improving the efficiency and environmental sustainability (ENS) of humanitarian supply chains through…
Abstract
Purpose
This study aims to understand the role of technology adoption (TA) in improving the efficiency and environmental sustainability (ENS) of humanitarian supply chains through collaboration and supply chain agility. This study made an attempt to explore how technological resources can be used strategically to achieve operational efficiency and contribute to sustainable humanitarian logistics.
Design/methodology/approach
The data collected from 274 respondents involved in humanitarian logistics is analyzed using the confirmatory factor analysis and the Partial Least Squares Structural Equation Modeling. These respondents include logistics managers, coordinators as well as other relevant personnel from different non-governmental organizations, international aid agencies and relief operations.
Findings
The results of this study show that TA plays a critical role in improving both collaboration and supply chain agility in humanitarian operations. It is evidenced that both collaboration and agility significantly moderate the relationship between TA and supply chain outcomes, respectively, improving the effectiveness and ENS of aid delivery. In particular, technology-facilitated collaboration and agility cut down operational costs, reduce the response time and minimize the environmental impact.
Originality/value
This study extends the application of dynamic capabilities view in humanitarian operations and supply chain and elaborates on how technological capability improves humanitarian supply chain performance. This study also highlights the mediation role of agility and collaboration to achieve aid delivery efficiency and ENS.
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Keywords
Bhawana Rathore, Rohit Gupta, Baidyanath Biswas, Abhishek Srivastava and Shubhi Gupta
Recently, disruptive technologies (DTs) have proposed several innovative applications in managing logistics and promise to transform the entire logistics sector drastically…
Abstract
Purpose
Recently, disruptive technologies (DTs) have proposed several innovative applications in managing logistics and promise to transform the entire logistics sector drastically. Often, this transformation is not successful due to the existence of adoption barriers to DTs. This study aims to identify the significant barriers that impede the successful adoption of DTs in the logistics sector and examine the interrelationships amongst them.
Design/methodology/approach
Initially, 12 critical barriers were identified through an extensive literature review on disruptive logistics management, and the barriers were screened to ten relevant barriers with the help of Fuzzy Delphi Method (FDM). Further, an Interpretive Structural Modelling (ISM) approach was built with the inputs from logistics experts working in the various departments of warehouses, inventory control, transportation, freight management and customer service management. ISM approach was then used to generate and examine the interrelationships amongst the critical barriers. Matrics d’Impacts Croises-Multiplication Applique a Classement (MICMAC) analysed the barriers based on the barriers' driving and dependence power.
Findings
Results from the ISM-based technique reveal that the lack of top management support (B6) was a critical barrier that can influence the adoption of DTs. Other significant barriers, such as legal and regulatory frameworks (B1), infrastructure (B3) and resistance to change (B2), were identified as the driving barriers, and industries need to pay more attention to them for the successful adoption of DTs in logistics. The MICMAC analysis shows that the legal and regulatory framework and lack of top management support have the highest driving powers. In contrast, lack of trust, reliability and privacy/security emerge as barriers with high dependence powers.
Research limitations/implications
The authors' study has several implications in the light of DT substitution. First, this study successfully analyses the seven DTs using Adner and Kapoor's framework (2016a, b) and the Theory of Disruptive Innovation (Christensen, 1997; Christensen et al., 2011) based on the two parameters as follows: emergence challenge of new technology and extension opportunity of old technology. Second, this study categorises these seven DTs into four quadrants from the framework. Third, this study proposes the recommended paths that DTs might want to follow to be adopted quickly.
Practical implications
The authors' study has several managerial implications in light of the adoption of DTs. First, the authors' study identified no autonomous barriers to adopting DTs. Second, other barriers belonging to any lower level of the ISM model can influence the dependent barriers. Third, the linkage barriers are unstable, and any preventive action involving linkage barriers would subsequently affect linkage barriers and other barriers. Fourth, the independent barriers have high influencing powers over other barriers.
Originality/value
The contributions of this study are four-fold. First, the study identifies the different DTs in the logistics sector. Second, the study applies the theory of disruptive innovations and the ecosystems framework to rationalise the choice of these seven DTs. Third, the study identifies and critically assesses the barriers to the successful adoption of these DTs through a strategic evaluation procedure with the help of a framework built with inputs from logistics experts. Fourth, the study recognises DTs adoption barriers in logistics management and provides a foundation for future research to eliminate those barriers.