A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.

http://absimage.aps.org/image/MAR10/MWS_MAR10-2009-007155.pdf

Limits of predictability in human mobility

Optimal path planning in real time for dynamic building fire rescue operations using wireless sensors and visual guidance

This paper explains market turbulence, such as the recent dotcom boom/bust cycle, as equilibrium industry dynamics triggered by technology innovation. When a major technology innovation arrives, a wave of new firms enter the market implementing the innovation for profits. However, if the innovation complements existing technology, some new entrants will later be forced out as more and more incumbent firms succeed in adopting the innovation. It is shown that the diffusion of Internet technology among traditional brick-and-mortar firms is indeed the driving force behind the rise and fall of dotcoms as well as the sustained growth of e-commerce. Empirical evidence from retail and banking industries supports the theoretical findings. ; Earlier title: Technology innovation and market turbulence: a dot-com example

Technological innovation and market turbulence: the dot-com experience

Socialisation through online social media has changed the pattern in which customers behave. Few studies have examined the implication of social network website in online retailing context by extending the social presence theory and inclusion of attitude (ATT), customer information quality (CIQ) and effectiveness of information content (EIC) in understanding shopping behaviour among social networks users. Thus, this study attempts to examine the influence of ATT, CIQ, EIC and perceived social presence (PSP) on social shopping (SS) intention among social network users. Quantitative techniques, snowball sampling procedure and cross sectional data collection approach used to empirically test the hypotheses within structural equation modelling (SEM) using SmartPLS software for assessment of measurement model (internal consistency, indicator reliability, convergence and discriminant validity) and structural model (structural model for collinearity, the significance of the path coefficients, the level of the R2 values, the f2 effect size and the predictive relevance). A total of 326 valid online questionnaires were analysed. The findings indicate that CIQ, EIC, PSP and ATT are significant predictor toward SS intention. This study contributes to literature by examining social factors of shopping intention and examining Malaysian online social groups. Finally, the study limitations, implication and social contribution are discussed.

Online social shopping: the impact of attitude, customer information quality, effectiveness of information content and perceived social presence

Although purchase pressure cues (PPC) that signal limited time (LT) or limited product availability (LPA) are widely used features on e-commerce websites to boost sales, research on whether and why PPCs affect consumers’ purchase choice in online settings has remained largely unexplored. Drawing on the Stimulus-OrganismResponse (S-O-R) model, consumer decision-making literature, and prospect theory, we conducted a controlled lab experiment with 121 subjects in the context of Deal-ofthe-Day (DoD) platforms. We demonstrate that while LT pressure cues significantly increase deal choice, LPA pressure cues have no distinct influence on it. Furthermore, our results show that perceived stress and perceived product value serve as two serial mediators explaining the theoretical mechanism of why LT pressure cues affect deal choice. Complementary to these results, we provide evidence that higher perceived stress is accompanied by significant changes in consumers’ physiological arousal. Further theoretical and practical implications of our findings are discussed.

Buying under Pressure: Purchase Pressure Cues and their Effects on Online Buying Decisions

Situational awareness is a critical component in a post-disaster recovery operation for assessment of needs and identification of available resources at different parts of a disaster-affected area. This information, in turn, may help the relief agencies to appropriately coordinate, manage and channelize their resources. A major hindrance in developing such global situational awareness is the non-uniform interaction pattern of relief workers. Volunteers in a particular region have much better knowledge of the local situation than those belonging to regions further away. This information asymmetry leads to deviation in perceptions of volunteers working in different regions, thereby affecting the resource distribution process. Thus, a unified global situational view of the entire disaster affected area is essential to bridge the perception gap of volunteers and to help them develop a common understanding of the actual scenario. In this paper, we propose a scheme for developing such a coherent global view of the post-disaster situation using local situational information in a smart-phone based delay tolerant peer-to-peer network environment.We focus on generating a comprehensive view which is consistent for all workers irrespective of their location or mobility. The proposed scheme takes into account the spatial locality and spatial regularity properties of human mobility and uses a concept of “opportunistic knowledge injection” to disseminate local situational knowledge to other remote areas without significant network overhead. The effectiveness of the proposal is evaluated on the ONE simulator.

Developing a coherent global view for post disaster situation awareness using opportunistic network

In this paper, we have developed an agent-based simulation model to study the influence of social media on consumers' inclination towards on-line shopping. Social media includes web-based and mobile based technologies which are used to turn communication into interactive dialogue between organizations, communities, and individuals. Building upon the Transaction Cost Economics theory, the objective of our study is to examine the effect of social media on the "perceived transaction cost" of an individual, which determines his/her inclination to buy online. Transaction cost economics (TCE) theoretically explains why a transaction subject favors a particular form of transaction over others. Since purchasing from online stores can be considered a choice between the internet and traditional stores, it is reasonable to assume that consumers will go with the channel that has the lower transaction cost. Using agent-based models, we have studied the rate of adoption of on-line shopping by consumers and found it to be exponential, not linear.

A simulation model using transaction cost economics to analyze the impact of social media on online shopping

Tracking User-movement in Opportunistic Networks to Support Distributed Query-response During Disaster Management

In existing models of opportunistic networks, nodes are not usually topology-aware. In this paper, we have developed a distributed mechanism in order to make each node in the network topology aware, i.e. aware of the approximate location-related GPS information of other nodes. The mechanism proposed in this paper is primarily developed on mobile agent based framework. It is assumed that each node has a dedicated satellite agent. Task of this agent is to help exchanging GPS information between its host node and its neighboring nodes only. This nearest neighbor interaction rule will eventually enable each node to have approximate location information about other nodes. As a direct consequence of topology-awareness, data forwarding schemes becomes far more efficient. We have introduced a parameter W (degree of disconnectedness) and show that our system is robust against wide variation of W. The performance evaluation results establish the effectiveness of the proposed scheme.

Apratim Mukherjee

Papers

Developing a coherent global view for post disaster situation awareness using opportunistic network

A simulation model using transaction cost economics to analyze the impact of social media on online shopping

Tracking User-movement in Opportunistic Networks to Support Distributed Query-response During Disaster Management

A Decentralized Approach towards Location Tracking of Mobile Users in Opportunistic Networks