The Internet of Things (IoT) has realised the fourth industrial revolution concept; however, its applications in the manufacturing industry are relatively sparse and primarily investigated without contextual peculiarities. Our research undertakes an intricate critical review to investigate significant aspects of IoT applications in the manufacturing Industry 4.0 perspective to address this gap. We adopt a systematic literature review approach by Denyer and Tranfield (2009) to carry out critical analyses that help develop future research domains based on empirical studies. We describe key knowledge gaps in the existing literature and empirical studies by exploring the main contribution categories and finding six critical differences between traditional and manufacturing Industry 4.0 and 10 enablers and 11 challenges of IoT applications. Finally, an agenda for future research is proposed with 11 research domains to focus on the recognised gaps.

The Internet of Things (IoT) and its benefits and challenges are the most emergent research topics among academics and practitioners. With supply chains (SCs) gaining rapid complexity, having high supply chain visibility (SCV) would help companies ease the processes and reduce complexity by improving inaccuracies. Extant literature has given attention to the organisation’s capability to collect and evaluate information to balance between strategy and goals. The majority of studies focus on investigating IoT’s impact on different areas such as sustainability, organisational structure, lean manufacturing, product development, and strategic management. However, research investigating the relationships and impact of IoT on SCV is minimal. This study closes this gap using a structured literature review to critically analyse existing literature to synthesise the use of IoT applications in SCs to gain visibility, and the SC. We found key IoT technologies that help SCs gain visibility, and seven benefits and three key challenges of these technologies. We also found the concept of Supply 4.0 that grasps the element of Industry 4.0 within the SC context. This paper contributes by combining IoT application synthesis, enablers, and challenges in SCV by highlighting key IoT technologies used in the SCs to gain visibility. Finally, the authors propose an empirical research agenda to address the identified gaps.

The present decade has seen an upsurge in the research on the applications of autonomous vehicles and drones to present innovative and sustainable solutions for traditional transportation and logistical challenges. Similarly, in this study, we propose using autonomous cars and drones to resolve conventional logistics and transport challenges faced by international humanitarian organizations (IHOs) during a relief operation. We do so by identifying, shortlisting, and elaborating critical success factors or key transport and logistics challenges from the existing humanitarian literature and present a conceptual model to mitigate these challenges by integrating unmanned ground (UGVs) and aerial vehicles (UAVs) in the humanitarian supply chain. To understand how this novel idea of using UGVs and UAVs could help IHOs, we drafted three research questions, first focusing on the identification of existing challenges, second concentrating on remediation of these challenges, and the third to understand realization timeline for UGVs and UAVs. This lead to the development of a semi-structured, open-ended questionnaire to record the respondents’ perspectives on the existing challenges and their potential solutions. We gathered data form, ten interviewees, with substantial experience in the humanitarian sector from six IHOs stationed in Pakistan and Austria. In light of the feedback for the second research question, we present a conceptual model of integrating UAVs and UGVs in the relief chain. The results of the study indicate that technological advancement in mobility withholds the potential to mitigate the existing challenges faced by IHOs. However, IHOs tend to be reluctant in adapting UGVs compared to UAVs. The results also indicate that the adaptation of these technologies is subject to their technical maturity, and there are no significant differences in opinions found between the IHOs from Pakistan and Austria.

In the era of modern technology, the competitive paradigm among organisations is changing at an unprecedented rate. New success measures are applied to the organisation’s supply chain performance to outperform the competition. However, this lead can only be obtained and sustained if the organisation has an effective and efficient supply chain and an appropriate forecasting technique. Thus, this study presents the demand-forecasting model, i.e., a good fit for the pharmaceutical sector, and shows promising results. Through this study, it is observed that combining forecasting algorithms can result in greater forecasting accuracies. Therefore, a combined forecasting technique ARIMA-HW hybrid¹ i.e. (ARHOW) combines the Autoregressive Integrated Moving Average and Holt’ s-Winter model. The empirical findings confirm that ARHOW performs better than widely used forecasting techniques ARIMA, Holts Winter, ETS and Theta. The results of the study indicate that pharmaceutical companies can adopt this model for improved demand forecasting.

Automotive manufacturers are competing to be the first to introduce customer-ready autonomous vehicles. Some manufacturers are claiming to launch their first self-driving cars as early as 2020. Which all sounds very good and futuristic; however, the question arises, are customers even ready to adopt this new technological advancement? Therefore, this pilot study is aimed at finding out the answer to this question in the Austrian market. This study discovers the standpoint of Austrian consumers concerning the acceptance of self-driving cars for daily usage and gives an overview of the current point of view regarding autonomous vehicles (AVs). The data for this study was collected using an online, user-friendly, Likert scale survey. The collected data were processed and analyzed for empirical significance in SPSS using Spearman’s rank correlation and the Mann–Whitney U test supported by descriptive analysis. The results of the study indicate that Austrian consumers are well aware of autonomous vehicles and their technology. However, they have specific concerns about reliability, cybersecurity, and futuristic car-sharing models. Therefore, these concerns about AVs should be addressed by auto manufactures in order to gain consumers’ trust and sell them a new form of mobility.

Courier, express, and parcel (CEP) services represent one of the most challenging and dynamic sectors of the logistics industry. Companies of this sector must solve several challenges to keep up with the rapid changes in the market. In this context, the introduction of autonomous delivery using self-driving trucks might be an appropriate solution to overcome the problems that the industry is facing today. This paper investigates if the introduction of autonomous trucks would be feasible for deliveries in urban areas from the experts’ point of view. Furthermore, the potential advantages of such autonomous vehicles were highlighted and compared to traditional delivery methods. At the same time, barriers that could slow down or hinder such an implementation were also discovered by conducting semi-structured interviews with experts from the field. The results show that CEP companies are interested in innovative logistics solutions such as autonomous vans, especially when it comes to business-to-consumer (B2C) activities. Most of the experts acknowledge the benefits that self-driving vans could bring once on the market. Despite that, there are still some difficulties that need to be solved before actual implementation. If this type of vehicle will become the sector’s disruptor is yet to be seen.