Search results

The purpose of this paper is to analyse how start-ups with a clear sustainability focus collaborate with multiple actors at different levels to pursue business ideas and develop sustainable freight transport solutions.

This paper builds on a theoretical approach that includes three levels of analysis: the actor level (micro), business-network level (meso) and society and government level (macro). An embedded case study is used of a focal start-up aiming to innovate on networked platforms and electric and autonomous vehicles (EAVs).

Activities and resources are developed at the firm (micro), network (meso) and societal levels (macro), and all three levels need to be considered for a start-up, with a clear sustainability focus. Interaction within as well as between levels affects the innovation development, integration and implementation. The many-folded collaborations at the meso level serve as a locus for the integration of EAVs. The start-up’s networking activities with actors at meso and macro levels contribute to it gaining legitimacy in the transport system.

This paper focuses on the importance of collaboration in the context of developing innovative solutions for environmental sustainability and freight transport and provides a unique case of how a start-up company manages collaborations at the micro, meso and macro levels.

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

Despite the increasing use of home delivery (HD) in e-commerce, no studies have explicitly examined consumer perceptions of the convenience of the last-mile delivery of goods by cargo bike (CB). Therefore, this study aims to identify the dimensions of HD convenience and to develop a reliable and valid measurement tool, namely the Home-Delivery Convenience via Cargo Bike (HDCCB) scale.

The methodology of this scale development study is premised on a review of the existing literature, which identifies differences in consumer perceptions of the convenience of services. The authors conducted semi-structured interviews with 10 online consumers and validated the content with 3 experts on marketing in the retail and services sectors in order to develop the items for the scale. Thereafter, the authors identified the main dimensions through an exploratory factor analysis that the authors applied to an online survey with 116 respondents. Finally, the scale was validated through a confirmatory factor analysis of an online survey with 300 respondents.

Following the original work of Brown (1990), the authors define consumer perceptions of HD convenience as a multidimensional construct and measure each facet of its four dimensions, which are time, use, execution and acquisition. E-retailers and last-mile logistics providers could use the authors' proposed measurement tool to assess consumer perceptions of the convenience of HD. That assessment could generate a competitive advantage.

This study is original as the study deepens the existing understanding of consumer perceptions of the convenience of HD by CB in last-mile logistics. This study also develops a multidimensional measure that is based on an empirical study.

The presented research is carried out in reaction to the soaring costs of fuel and tight control over environmental issues such as carbon dioxide emissions and noise. The purpose of this paper is to study the feasibility of applying the environmental-friendly energy source in an unmanned aerial vehicles (UAVs) propulsion system.

Currently, the majority of UAVs are still powered by conventional combustion engines. An electric propulsion system is most commonly found in civilian micro and mini UAVs. The UAV classification is reviewed in this study. This paper focuses mainly on application of electric propulsion systems in UAVs. Investigated hybrid energy systems consist of fuel cells, Li-ion batteries, super-capacitors and photovoltaic (PV) modules. Current applications of fuel cell systems in UAVs are also presented.

The conducted research shows that hybridization allows for better energy management and operation of every energy source onboard the UAV within its limits. The hybrid energy system design should be created to maximize system efficiency without compromising the performance of the aircraft.

The presented study highlights the reduction of the energy consumption, necessary to perform the mission and maximizing of the endurance with simultaneous decrease in emissions and noise level.

The conducted research studies the feasibility of implementing the environmental-friendly hybrid electric propulsion systems in UAVs that offers high efficiency, reliability, controllability, lack of thermal and noise signature, thus, providing quiet and clean drive with low vibration levels. This paper highlights the main challenges and current research on fuel cell in aviation and draws attention to fuel cell – electric system modeling, hybridization and energy management.

This study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.

A systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.

SCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.

The paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.

The purpose of this paper is to present the findings of a bibliometric analysis of the evolution and structure of business model research in industrial marketing scholarship during the period between 2011 and 2020 and to discuss potential directions for future empirical research.

Bibliometric methodologies are deployed to objectively evaluate the business model research that has made the most impact within industrial marketing scholarship as well as the prominent scholars and key topics driving the discipline at points in time.

The findings demonstrate the formative but increasing engagement that industrial marketing scholarship has had with business model literature and the limited but increasing degree that business models have influenced industrial marketing literature. Potential directions for the empirical development of business model literature are argued to lie in the areas of collaboration and coopetition by examining the notion of value within the relationships, interactions and/or networks evidenced in European seaports business models.

Bibliometric analysis is retrospective in nature so developments in the literature appear only after some time has elapsed. Different keyword selection when formulating search strings for sampling may have brought some deviations in the analysis.

Research that investigates the link between business models and industrial marketing is still scarce. This paper is among the few that analyze objectively the evolution and structure of business model literature in industrial marketing scholarship from a longitudinal perspective with a particular emphasis on the period between 2011 and 2020.