Calls for Papers (special): Journal of Global Information Management (JGIM)


Special Issue On: Sharing Economy and Cross-border e-Commerce

Submission Due Date
3/15/2020

Guest Editors
Wen-Lung Shiau, PhD, Professor, Department of Business Administration, Zhejiang University of Technology, Zhejiang, People’s Republic of China
Yi-Hung Liu, PhD, Associate Professor, Department of Business Administration, Zhejiang University of Technology, Zhejiang, People’s Republic of China
Felix Ter Chian Tan, PhD, Senior Lecturer, School of Information Systems and Technology Management, UNSW Business School, Australia
Kuanchin Chen, DBA, Professor, Department of Business Information Systems, Western Michigan University, Kalamazoo, Michigan, U.S.A.


Introduction
Cross-border exchanges are a popular way to drive globalization. Goods and services have traditionally been among the top items exchanged with a growing trend of exchanges in other forms, such as human talents and electricity. Factors that drive the demand for cross-border exchanges include supply (e.g., reputation, availability, etc.), delivery (e.g., cost, speed and barriers), service value, and culture (Kim et al., 2017; Chang et al, 2015). Technology plays an increasingly important role as a driver for innovation (Zander & Sölvell, 2000), relationship learning (Jean, Sinkovics & Kim, 2010), exchanges of health data & services (Kim, 2017), knowledge transfer (Makkonen, Williams, Weidenfeld & Kaisto, 2018), collaborative consumption (Hamari, et al., 2016; Greenwood and Wattal, 2017; Tan et al., 2018) and many other emerging areas of cross-border exchanges. For example, digital platforms equipped with data analytics enable high speed, scalable and ubiquitous services, thus offering a substantial advantage over the traditional ways of trade (Sutherland and Jarrahi, 2018; Wu and Lin, 2018). However, new requirements for organizational transformations, increased complexity in business processes, regulatory restrictions, and uneven technology capabilities have contributed to the uncertainties of cross-border exchanges. Nonetheless, the benefits derived from sharing economy and cross-border commerce have put a severe pressure on existing companies that are less flexible to adapt (Kim et al., 2017; Li et al., 2018).

Objective
The special issue is tied to the conference of China Association for Information Systems (CNAIS) to be held on Oct. 11-14th, 2019 in Nanjing University, China. Outstanding papers presented at the conference will be invited for submission to the special issue. The guest editors also welcome submissions that have not been submitted to or presented at the conference. We invite papers addressing leading challenges of sharing economy and cross-border commerce by providing technical, managerial, methodological and other forms of contributions. Interested authors are recommended to review the mission and scope of the journal for the types of articles the journal publishes.

Recommended Topics
Relevant topics for this special issue include but not limited to:
  • Public, corporate and industry experiences with sharing platforms or cross-border e-Commerce.
  • Competition between sharing economy or cross-border e-Commerce companies and traditional forms of economy.
  • Business, legal and public policy issues in sharing economy or cross-border e-Commerce.
  • Data privacy, trust and security in sharing economy or cross-border e-Commerce.
  • The role of technology in sharing economy or cross-border e-Commerce.
  • Technology advances and their associated issues in sharing economy or cross-border e-Commerce.
  • Other emerging issues in sharing economy or cross-border e-Commerce.


Submission Procedure
All submissions must be original, not published or under review elsewhere. Authors should submit their manuscripts through the Journal of Global Information Management (JGIM) online submission system ( https://www.igi-global.com/submission/submit-manuscript/ ), and select "Sharing Economy and Cross-border e-Commerce" from the “Submit to a Special Issue” drop-down box. Manuscripts should follow JGIM 's guidelines for manuscript submission instructions (https://www.igi-global.com/publish/contributor-resources/before-you-write/), and be no more than 32 double-spaced pages in 12-point font, inclusive of all figures, tables, figures, and appendixes. Any inquiries about the special issue can be sent by email to the coordinating guest editor Liu, Y.H. (lyh0315@gmail.com).

All submissions and inquiries should be directed to the attention of:
Yi-Hung Liu
Guest Editor
Journal of Global Information Management (JGIM)
Email: lyh0315@gmail.com

Special Issue On: Management of Information Security, Privacy, and Trust in Global Crowdsourcing, Crowdsensing and Crowdpayment

Submission Due Date
9/15/2020

Guest Editors
Sang-Bing Tsai, University of Electronic Science and Technology of China Zhongshan Institute, China & Wuyi University, China
B. B. Gupta, National Institute of Technology, Kurukshetra, India
Dharma P. Agrawal, University of Cincinnati, Cincinnati, USA
Andrew W. H. Ip, University of Saskatchewan, Department of Mechanical Engineering, Canada




Introduction
Crowdsourcing is a framework through which a task, problem or project is solved and completed through a group of individuals who are willing to contribute. There may be no prior relation between these individuals as they can also be geographically disjointed. It is a joint development process or problem-solving technique that enlists the services of suitable individuals from all over the world, generally through the Internet. The participants can be freelancers, volunteers or paid workers. Generally, the Crowdsourcer publishes a problem or project on a related website and invites experts and the public, also called crowd, to come up with a solution or contribute in finishing the task. The participating members are either paid or given recognition for the completed task. Crowdsensing is a technique similar to crowdsourcing. The contribution is made by gadgets associated with the crowd. Also referred to as mobile crowdsensing, it is a technique where a group of individuals possessing mobile gadgets communicate sensor data to the crowdsenser. The gadgets can be smartphones, tablet computers, wearables or IOT devices equipped with sensors capable of sensing the environment around them. This data is then measured, analyzed and mapped to extract useful information and possibly form conclusions. In short, this means crowdsourcing of sensor data from mobile devices.

This concept has also been translated to the financial world. The usual methods to carry out payments to developers or the individuals of the crowdsourcing community are eWallets, Bank wire transfers and Credit/Debit cards. All these payment methods demand a minimal fee to the service provide at some stage in the transfer. This is the disadvantage of a centralized system. Cryptocurrencies work around this problem by being truly distributed. Crowdpayment is a concept through which all the contributors involved in crowdsourcing are fairly and properly compensated. An example would be to contribute to the core developers of cutting-edge open source technologies like bitcoin. Crowdfunding can be equated as a synonym. It involves sourcing small non-returnable investments from many individuals in order to fund the development of an innovative project, firm or an idea.

Crowdfunding is further effective when carried out using cryptocurrencies. Since crowdsourcing and crowdsensing deal with data from individuals, the issue of privacy naturally arises. These can be privacy threats from data and privacy threats from tasks. Privacy of Sensed Data (PSD), Privacy of Computing Inputs (PCI) and Privacy of Computing Results (PCR) are the risks associated with handling crowdsensed data. The information collected may contain sensitive data about the participant (GPS location data). Even environmental data have the potential to reveal a person’s location. This information if disclosed can lead to a breach of trust and thus have to be handled confidentially. The input (sensed data) and the computed output are also equally sensitive. When sending the data to the computing crowd, it may leak out the private information of data contributors, data owners or other related people. The conclusions from the data may be more sensitive than the actual data itself. Thus, these three risks associated with the sensed and sourced data are of utmost importance. Threats from tasks are Task Privacy of End Users (TPEU) and Task Privacy of Participants (TPP). The participants of a crowdsourcing task have to invariably disclose certain information in order to carry out the task. An example would be a temperature sensing task where the participant has to be at a particular location at a particular time. Such issues have to be mitigated by the service provider. There are also reliability threats which include the extent to which the received data could be trusted. A smartphone sensing temperature can be way off the actual reading due to various unavoidable circumstances. It can be due to the processor emitting extra heat from high processing tasks. The data has to also be reliable and not be tampered with before or during transmission.

Objective
This special issue mainly focuses on the Management of Information Security, Privacy, and Trust in Global Crowdsourcing, Crowdsensing, and Crowdpayment, addressing the information management issues in both original algorithmic development and new applications from a global perspective. We are soliciting original contributions, of leading researchers and practitioners from academia as well as industry, which address a wide range of theoretical and application issues in this domain.

Recommended Topics
The topics relevant to this special issue include but are not limited to:
• Privacy centered framework for crowdsourcing and crowdsensing
• Crowdsourcing cybersecurity
• Data privacy in crowdfunding campaigns
• Legal issues of sourcing ideas to crowds
• R&D outsourcing to the crowd
• Usage of Machine learning to thwart crowdsourcing security threats
• Reduction of Intellectual property rights infringement in crowdsourcing
• Legal and ethical issues of crowdsourcing
• Piggyback crowdsensing
• Efficient task allocation in crowdsourcing
• Programming framework for crowd-sensing applications
• Gamified crowdsourcing


Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Management of Information Security, Privacy, and Trust in Global Crowdsourcing, Crowdsensing and Crowdpayment on or before 15 September 2020 . All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
All submissions and inquiries should be directed to the attention of:
Dr. B.B. Gupta
Guest Editor
Journal of Information Global Management
E-mail: bbgupta@nitkkr.ac.in

Special Issue On: Artificial Intelligence in Global Production Systems and Supply Chain Management

Submission Due Date
3/15/2021

Guest Editors
Prof. Samuel Fosso Wamba, Toulouse Business School, France
Prof. Maciel M. Queiroz, Universidade Paulista, Brazil

Introduction
The digital disruption imposed by information and communication technologies (ICT) (Grant & Yeo, 2019; Wu & Raghupathi, 2015) by recent emerging cutting-edge technologies has become a buzzword and a challenge to scholars and practitioners. An emerging and highly disruptive of these technologies is Artificial intelligence (AI) (Davenport, 2018). In summary, AI refers to machines performing activities that commonly require some human intelligence to perform it (Minsky, 1968). AI has been changing the decision-making process drastically, by employing sophisticated approaches such as machine learning, natural language processing, augmented and virtual reality, voice recognition, cognitive analytics, robotics, smart machines, and vision, among others. AI has been applied in a vast of fields, e.g., medicine (Becker, 2019; Wong, Zhou, & Zhang, 2019), market knowledge in B2B (Paschen, Kietzmann, & Kietzmann, 2019), and production management systems (Burggräf, Wagner, & Koke, 2018; Davies, Thomas, & Shaw, 1994). Nowadays, AI is transforming the global society and organizations’ behavior due to its pervasiveness capacity. From an organization's perspective, AI can help the development and improvement of products and processes to support various business benefits, and consequently, generate competitive advantage (Davenport, 2018). For instance, with AI, organizations can improve the functions related to sales management by the automation of all repetitive tasks (Syam & Sharma, 2018), monitoring infectious disease (Wong et al., 2019), combat card fraud (Ryman-tubb, Krause, & Garn, 2018), among others. In this context, AI can be used in any economic field, notably to support planning, monitoring, and the decision-making process. In addition, AI has been changing profoundly the role of the workers by human-machine interaction to develop operational activities (Faraj, Pachidi, & Sayegh, 2018). Despite the recent advances of AI techniques, there is a great debate between scholars and practitioners, especially about how AI can be implemented and managed, and how it creates value for the stakeholders (Davenport, 2018). In the same spirit, there are uncertainties related to AI issues, for example, ethical and legal issues (Duan, Edwards, & Dwivedi, 2019) related to data exploration and responsibility, the threats associated with AI usage (Clarke, 2019), and the relationship and the role of human-machine interaction (Jarrahi, 2018). At the global operations management and supply chain lens, there are several opportunities and challenges facing AI adoption and management. Besides, new skills are demanded to a new generation of global production systems (Freddi, 2018). However, little is known about how AI can support and bring benefits to the global operations and supply chain management (OSCM) and related-fields.

Objective
The purpose of this Special Issue is to publish the latest and finest advances of AI techniques applied in Global Production Systems and OSCM, as also advance the information systems field. Moreover, we intend to stimulate research and debate between scholars, managers, and practitioners interested in gaining a more in-depth understanding of the role, benefits, and complexities of AI in global production, manufacturing systems, SCM, and information systems. Following the tradition and rigor of high-quality papers published by JGIM in innovative technologies, we expect original contributions from scholars and practitioners that unlocks and shed more light on the comprehension of AI technologies in the global OSCM context, by employing quantitative and qualitative methods.

Recommended Topics
• How can production and supply chain managers improve firm performance, capture benefits, and gain a competitive advantage with AI techniques?
• AI techniques to support the scheduling and demand planning in global logistics and OSCM
• How can AI be managed at different levels of planning, and support operational decisions in global OSCM?
• Ethical issues and societal implications related to AI applied to develop global products
• Global logistics and OSCM capabilities required to implement AI
• AI and the reconfiguration of global production systems business models
• Barriers related to AI implementation in intra-organizational and inter-organizational levels
• What is the role of the interaction between human-machine in global OSCM systems?
• Frameworks to support managers in the decision-making process using AI in planning and control of the global production/OSCM
• Which are the critical factors of AI in global manufacturing, production systems, and supply chain management?
• The impacts of AI in knowledge and innovation in global manufacturing, production systems, and supply chain management
• Governance models to support AI diffusion globally between stakeholders
• How can AI be used to transform traditional global manufacturing and production systems in smart manufacturing?
• The role and consequences of trust, commitment, and power enabled by AI use in global supply chain management
• AI applied to improve quality management
• Workers skills required to work with AI in operational, tactical, and strategic levels?
• How to measure the benefits of AI in global manufacturing, production systems, and supply chain management?
• The threats associated with AI usage

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Artificial Intelligence in Global Production Systems and Supply Chain Management on or before March 15, 2021. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
All inquires should be should be directed to the attention of:
Prof. Samuel FOSSO WAMBA, Ph.D., HDR
Guest Editor
Journal of Information Global Management
E-mail: s.fosso-wamba@tbs-education.fr