Diffusion of Electronic Commerce in Australia

2011 ◽  
pp. 102-114
Author(s):  
Mohammed A. Quaddus
Keyword(s):  
Diffusion Process ◽  
Electronic Commerce ◽  
New Technology ◽  
Future Research ◽  
Research Directions ◽  
Simple Diffusion ◽  
Future Research Directions ◽  
Simple Diffusion Model ◽  
High Level ◽  
Flexible Model

Diffusion is the process by which a new technology spreads in its usage among a population. This chapter analyses the diffusion process of one aspect of the consumer-to-business electronic commerce (EC) in Australia, namely Internet shopping. The chapter first reviews three popular logistics diffusion models from the literature and then applies them to the EC diffusion data. Results show that the most flexible model is not significant, while the simple diffusion model (Blackman’s) is. It was also found that the past diffusion process had been mostly influenced by the “internal” interactions between the adopters and the potential adopters of EC. Further analysis of the Blackman’s model revealed some high level policy guidelines to enhance the diffusion process further into the future. Limitations of the study and future research directions were also identified.

Probabilistic Rule Learning Systems

2021 ◽  
Vol 54 (4) ◽  
pp. 1-16
Author(s):  
Abdus Salam ◽  
Rolf Schwitter ◽  
Mehmet A. Orgun
Keyword(s):  
Probability Theory ◽  
Rule Learning ◽  
Background Knowledge ◽  
Learning Systems ◽  
Future Research ◽  
Research Directions ◽  
System Architectures ◽  
Probabilistic Rule ◽  
Future Research Directions ◽  
High Level

This survey provides an overview of rule learning systems that can learn the structure of probabilistic rules for uncertain domains. These systems are very useful in such domains because they can be trained with a small amount of positive and negative examples, use declarative representations of background knowledge, and combine efficient high-level reasoning with the probability theory. The output of these systems are probabilistic rules that are easy to understand by humans, since the conditions for consequences lead to predictions that become transparent and interpretable. This survey focuses on representational approaches and system architectures, and suggests future research directions.

Gamified Self

2016 ◽  
pp. 304-327
Author(s):  
Rachelle DiGregorio ◽  
Harsha Gangadharbatla
Keyword(s):  
Technology Acceptance ◽  
Online Survey ◽  
Personal Information ◽  
New Technology ◽  
Ease Of Use ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
Self Knowledge ◽  
Over Time

Gamified self has many dimensions, one of which is self-tracking. It is an activity in which a person collects and reflects on their personal information over time. Digital tools such as pedometers, GPS-enabled mobile applications, and number-crunching websites increasingly facilitate this practice. The collection of personal information is now a commonplace activity as a result of connected devices and the Internet. Tracking is integrated into so many digital services and devices; it is more or less unavoidable. Self-tracking engages with new technology to put the power of self-improvement and self-knowledge into people's own hands by bringing game dynamics to non-game contexts. The purpose of this chapter's research is to move towards a better understanding of how self-tracking can (and will) grow in the consumer market. An online survey was conducted and results indicate that perceptions of ease of use and enjoyment of tracking tools are less influential to technology acceptance than perceptions of usefulness. Implications and future research directions are presented.

A Generic Guide for Using Membrane Computing in Robot Control

2017 ◽  
pp. 86-96
Keyword(s):  
Operating Systems ◽  
Membrane Computing ◽  
Task Complexity ◽  
Future Research ◽  
Research Directions ◽  
Robot Controller ◽  
Swarm Algorithms ◽  
Future Research Directions ◽  
High Level ◽  
Generic Algorithms

As various theoretical and practical details of using membrane computing models have been presented throughout the book, certain details might be hard to find at a later time. For this reason, this chapter provides the reader with a set of checkmark topics that a developer should address in order to implement a robot controller using a membrane computing model. The topics discussed address areas such as: (1) robot complexity, (2) number of robots, (3) task complexity, (4) simulation versus real world execution, (5) sequential versus parallel implementations. This chapter concludes with an overview of future research directions. These directions offer possible solutions for several important concerns: the development of complex generic algorithms that use a high level of abstraction, the design of swarm algorithms using a top-down (swarm-level) approach and ensuring the predictability of a controller by using concepts such as those used in real-time operating systems.

scholarly journals How Job Tenure Weakens the Positive Influence of Education on Creative Performance through Task Performance

2022 ◽  
Vol 14 (1) ◽  
pp. 537
Author(s):  
Lu Yang ◽  
Jun Wei ◽  
Jinyi Zhou
Keyword(s):  
Task Performance ◽  
Positive Influence ◽  
Future Research ◽  
Job Tenure ◽  
Creative Performance ◽  
Research Directions ◽  
Future Research Directions ◽  
Indirect Relationship ◽  
High Level ◽  
Practical Implications

Researchers indicate that employees with a high level of education tend to have better creative performance. However, few studies have investigated the boundary conditions of this association. The componential model of creativity demonstrates that both task-relevant skills and creativity-relevant skills are indispensable factors of creative performance. Job tenure, which generally hinders employees from acquiring creativity-relevant skills, is regarded as a potential boundary condition. In this study, we investigate how job tenure weakens positive influence of education on creative performance through task performance. Using a sample of 368 employees and 43 leaders in a provincial bank in China, we indeed find that job tenure negatively moderates the indirect relationship between education and creative performance via task performance. Specifically, the positive relationship is weakened when job tenure is high than when it is low. We also discuss the theoretical and practical implications of our study and highlight future research directions.

scholarly journals Leveraging Human Guidance for Deep Reinforcement Learning Tasks

2019 ◽  
Author(s):  
Ruohan Zhang ◽  
Faraz Torabi ◽  
Lin Guan ◽  
Dana H. Ballard ◽  
Peter Stone
Keyword(s):  
Reinforcement Learning ◽  
Future Research ◽  
Sequential Decision ◽  
Research Directions ◽  
Learning Agents ◽  
Learning Tasks ◽  
Future Research Directions ◽  
Human Effort ◽  
High Level ◽  
Learning Frameworks

Reinforcement learning agents can learn to solve sequential decision tasks by interacting with the environment. Human knowledge of how to solve these tasks can be incorporated using imitation learning, where the agent learns to imitate human demonstrated decisions. However, human guidance is not limited to the demonstrations. Other types of guidance could be more suitable for certain tasks and require less human effort. This survey provides a high-level overview of five recent learning frameworks that primarily rely on human guidance other than conventional, step-by-step action demonstrations. We review the motivation, assumption, and implementation of each framework. We then discuss possible future research directions.

Social Presence

2015 ◽  
pp. 1897-1914
Author(s):  
Libi Shen ◽  
Irene Linlin Chen
Keyword(s):  
Higher Education ◽  
Distance Education ◽  
Social Presence ◽  
New Technology ◽  
Future Research ◽  
Research Directions ◽  
Online Instructors ◽  
Future Research Directions ◽  
Innovative Pedagogy ◽  
Technology Trends

Over the years, the advance of technology has changed the ways of instructions in higher education, and new communication trends as well as innovative pedagogy evolved to be reconciled with new technology trends in distance education. What are the major challenges of communication in distance education? This chapter explores how dissertation chairs perceive social presence in online dissertation courses, and what challenges these online instructors have in distance dissertation mentorship. In this study, the authors interviewed eight experienced dissertation chairs to explore their insights and opinions on the effectiveness of social presence in distance dissertation mentorship as well as to examine the controversies hidden in online instructions. Major issues and problems in applying social presence theories in dissertation mentorship emerged from the interview results. Solutions and recommendations are provided to tackle the problems. Future research directions are indicated as well.

Data Tagging In Medical Images: A Survey of the State-of-art

2020 ◽  
Vol 16 ◽  
Author(s):  
Jyotismita Chaki ◽  
Nilanjan Dey
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Medical Data ◽  
Future Research ◽  
Research Directions ◽  
Data Intensive ◽  
Different Types ◽  
Future Research Directions ◽  
High Level ◽  
State Of Art

: A huge amount of medical data is generated every second, and a significant percentage of them are images that need to be analyzed and processed. One of the key challenges in this regard is the recovery of medical images. The medical image recovery procedure should be done automatically by the computers that are the method of identifying object concepts and assigning homologous tags to them. To discover the hidden concepts in the medical images, the low-level characteristics should be used to achieve high-level concepts and that is a challenging task. In any specific case, it requires human involvement to determine the significance of the image. To allow machine-based reasoning on the medical evidence collected, the data must be accompanied by additional interpretive semantics; a change from a pure data-intensive methodology to a model of evidence rich in semantics. In this state-of-art, data tagging methods related to medical images are surveyed which is an important aspect for the recognition of a huge number of medical images. Different types of tags related to the medical image, prerequisites of medical data tagging, different techniques to develop medical image tags, different medical image tagging algorithms and different tools that are used to create the tags are discussed in this paper. The aim of this state-of-art paper is to produce a summary and a set of guidelines for using the tags for the identification of medical images and to identify the challenges and future research directions of tagging medical images.

Modular Reconfigurable Robotics

2019 ◽  
Vol 2 (1) ◽  
pp. 63-88 ◽  
Author(s):  
Jungwon Seo ◽  
Jamie Paik ◽  
Mark Yim
Keyword(s):  
State Of The Art ◽  
Low Cost ◽  
Future Research ◽  
Research Directions ◽  
Current State ◽  
Robot Systems ◽  
Technical Issues ◽  
Future Research Directions ◽  
Reconfigurable Robot ◽  
High Level

This article reviews the current state of the art in the development of modular reconfigurable robot (MRR) systems and suggests promising future research directions. A wide variety of MRR systems have been presented to date, and these robots promise to be versatile, robust, and low cost compared with other conventional robot systems. MRR systems thus have the potential to outperform traditional systems with a fixed morphology when carrying out tasks that require a high level of flexibility. We begin by introducing the taxonomy of MRRs based on their hardware architecture. We then examine recent progress in the hardware and the software technologies for MRRs, along with remaining technical issues. We conclude with a discussion of open challenges and future research directions.

scholarly journals Generative Design in Building Information Modelling (BIM): Approaches and Requirements

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5439
Author(s):  
Wei Ma ◽  
Xiangyu Wang ◽  
Jun Wang ◽  
Xiaolei Xiang ◽  
Junbo Sun
Keyword(s):  
New Technology ◽  
Future Research ◽  
Generative Design ◽  
Building Information Modelling ◽  
Research Directions ◽  
Information Modelling ◽  
Building Information ◽  
Skill Requirement ◽  
Future Research Directions ◽  
Development Objectives

The integration of generative design (GD) and building information modelling (BIM), as a new technology consolidation, can facilitate the constructability of GD’s automatic design solutions, while improving BIM’s capability in the early design phase. Thus, there has been an increasing interest to study GD-BIM, with current focuses mainly on exploring applications and investigating tools. However, there are a lack of studies regarding methodological relationships and skill requirement based on different development objectives or GD properties; thus, the threshold of developing GD-BIM still seems high. This study conducts a critical review of current approaches for developing GD in BIM, and analyses methodological relationships, skill requirements, and improvement of GD-BIM development. Accordingly, novel perspectives of objective-oriented, GD component-based, and skill-driven GD-BIM development as well as reference guides are proposed. Finally, future research directions, challenges, and potential solutions are discussed. This research aims to guide designers in the building industry to properly determine approaches for developing GD-BIM and inspire researchers’ future studies.

scholarly journals Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions

2021 ◽  
Vol 1 (4) ◽  
pp. 580-596
Author(s):  
Cecelia Horan ◽  
Hossein Saiedian
Keyword(s):  
Open Source ◽  
Language Processing ◽  
Digital Forensics ◽  
New Technology ◽  
Future Research ◽  
Cyber Crime ◽  
Research Directions ◽  
Digital Forensic ◽  
Open Source Intelligence ◽  
Future Research Directions

As technology has become pivotal a part of life, it has also become a part of criminal life. Criminals use new technology developments to commit crimes, and investigators must adapt to these changes. Many people have, and will become, victims of cybercrime, making it even more important for investigators to understand current methods used in cyber investigations. The two general categories of cyber investigations are digital forensics and open-source intelligence. Cyber investigations are affecting more than just the investigators. They must determine what tools they need to use based on the information that the tools provide and how effectively the tools and methods work. Tools are any application or device used by investigators, while methods are the process or technique of using a tool. This survey compares the most common methods available to investigators to determine what kind of evidence the methods provide, and which of them are the most effective. To accomplish this, the survey establishes criteria for comparison and conducts an analysis of the tools in both mobile digital forensic and open-source intelligence investigations. We found that there is no single tool or method that can gather all the evidence that investigators require. Many of the tools must be combined to be most effective. However, there are some tools that are more useful than others. Out of all the methods used in mobile digital forensics, logical extraction and hex dumps are the most effective and least likely to cause damage to the data. Among those tools used in open-source intelligence, natural language processing has more applications and uses than any of the other options.

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