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Open Access
Article
Publication date: 13 February 2024

Amer Jazairy, Emil Persson, Mazen Brho, Robin von Haartman and Per Hilletofth

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into…

2012

Abstract

Purpose

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Design/methodology/approach

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

Findings

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

Research limitations/implications

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

Practical implications

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

Originality/value

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 11 January 2024

Yashdeep Singh and P.K. Suri

This study aims to describe the m-learning experience of school students and teachers during the COVID-19 pandemic and explores the factors influencing the continuance intention…

Abstract

Purpose

This study aims to describe the m-learning experience of school students and teachers during the COVID-19 pandemic and explores the factors influencing the continuance intention of m-learning.

Design/methodology/approach

Semistructured interviews of 24 students and 09 teachers of schools in national capital territory (NCT) Delhi, India were conducted over 03 months and transcribed verbatim. A hermeneutic phenomenological design was used to interpret the text and bring out the “lived experiences” of m-learning.

Findings

The following 15 themes or factors influencing continuance intention emerged through the hermeneutic circle: (1) actual usage, (2) attitude, (3) context, (4) extrinsic motivation, (5) facilitating conditions, (6) intrinsic motivation, (7) perceived compatibility, (8) perceived content quality, (9) perceived mobile app quality, (10) perceived teaching quality, (11) perceived usefulness, (12) satisfaction, (13) self-efficacy, (14) self-management of learning and (15) social influence.

Research limitations/implications

The study offers insightful recommendations for school administrators, mobile device developers and app designers. In addition, suggestions for effectively using m-learning during disasters such as COVID-19 have been provided. Several future research directions, including a nuanced understanding of m-assessment and online discussions, are suggested to enhance the literature on m-learning continuance.

Originality/value

The study enriches the literature on m-learning continuance. A qualitative approach has been used to identify relevant factors influencing m-learning continuance intention among secondary and higher secondary level (Grades 9 to 12) school students and teachers in India. In addition, a conceptual framework of the relationships among the factors has been proposed. Further, an analysis of the lived experiences of m-learning during the COVID-19 pandemic indicated several issues and challenges in using m-learning during disasters.

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