With the rapid development of Internet technologies, especially the mobile computing and social networks, the sharing economy (SE) has achieved unprecedented development and received extensive attention from various sectors of the society. The term “sharing economy” describes the phenomenon of peer-to-peer based activity of acquiring, providing, or sharing access to under-utilized goods or services, manpower, and financial resources, which involves demand sources, resource/service suppliers, and community-based on-line platforms (Investopedia, 2018). The sharing economy platforms (e.g., Airbnb, Uber, ofo, Indiegogo, Lending Club, Etsy, Door Dash, Quora, Upwork etc) have revolutionized the way traditional industries operate in the real world, and have started to transform the ways we live. The potential economic and environmental impacts, and benefits of SE are colossal. Meanwhile, SE also poses great challenges to operations management (OM) in practice in terms of fulfilling regulators’ legitimate concerns, matching supply and demand, coping with market competition, addressing security and privacy concerns etc. These problems affect the healthy development of SE and require in-depth research to address.
The purpose of this Special Issue (SI) is to publish high-quality analytical papers addressing emerging operations management and production economics issues arising in the sharing economy, producing significant findings that facilitate the decision-making processes of individual consumers, service providers, regulatory authorities, and other SE stakeholders. We seek research works that employ mainstream OM research methodologies, such as mathematical modelling, optimization, simulation, event studies, questionnaire surveys, and case studies. Original and high-quality research fitting the SI’s theme that is neither published nor currently under review by any other journal is welcome. Potential topics include, but are not limited to, the following:
- Big data analysis for operations management in the sharing economy
- Data-driven operations management in the sharing economy
- Demand forecasting in the sharing economy
- Facility location and layout planning in the sharing economy
- Investment strategy in the sharing economy
- Matching supply and demand in the sharing economy
- Mechanism design in the sharing economy
- Operations management with behavioural concerns in the sharing economy
- Operations planning in the sharing economy
- Operational problems in a competitive sharing economy market
- Pricing in the sharing economy
- Real case studies of operations management in the sharing economy
- Risk control and management in the sharing economy
- Smart logistics/supply chain management in the sharing economy
- Use of information for improving operations in the sharing economy
工学
International Journal of Production Economics
New Technologies in Operations and Supply Chain: Implications for Sustainability
Application of new technologies is gaining strong momentum in production and operations management (POM) of today’s manufacturing. The rapid development of artificial intelligence (AI), machine learning (including data mining), new-generation data-driven information technologies, automatic intelligence, and new energy technologies, for example, has unprecedentedly facilitated the advent of a new industrial revolution. This new era of transformation in industry will undoubtedly bring about game-changing approaches, models, processes and systems in operations management, production planning and control, supply chain and logistics management. In particular, the deep integration of intelligent technologies and communication technologies with manufacturing can trigger the development of smart factories, intelligent manufacturing system architectures, and intelligent manufacturing technology systems.
It is clear that the new technologies in manufacturing can create great opportunities for both new products/services and immense productivity improvements. They also, however, pose substantial challenges, for society as well as commercial firms, such as the dangers and disadvantages in terms of increased unemployment and greater wealth inequalities when intelligent machines outperform human brain power. Yet while there has been much discussion about the impact of new technologies on such matters, there has been less coverage as to whether their applications could improve sustainability performance in the POM literature. This is despite the new technologies raising key questions.
The main objective of this special issue is thus to fill this knowledge gap and provide a forum for scholars and practitioners to critically study, evaluate, explore and explain the new models, new ways, new means and new forms of intelligent manufacturing that create impacts on operations sustainability. The results will further our understanding of the implications of new technologies in manufacturing for sustainability both practically and theoretically.
Recommended Topics:
The particularly suitable topics that are welcomed in this special issue include, but are not limitedto, the following:
• Studies on the impact of new models, new means and new forms of intelligent manufacturing on operations sustainability.
• Studies on intelligent manufacturing ecology, with the characteristics of ubiquitous network technology, cross-border integration, autonomous intelligent, product lifecycle intelligent design technology and mass innovation, etc.
• Comparative studies on different types of new technologies in manufacturing and their impacts on operations sustainability.
• New technologies in manufacturing and their implications for sustainability in different cultural and regional contexts, including developing countries and SMEs.
• Impact of new technologies in manufacturing on various stages of a product lifecycle and its implications for sustainability.
• Applications of new technologies in operations and supply chain management for environmental and social improvement.
• New theory development to explain the implications of new technologies in manufacturing for sustainability at the firm, inter-firm, and supply network levels.