Influential Factors In Consumer\u27s Adoption Of Innovative Products

This dissertation addresses the challenges involved with the process of diffusion of innovations in the contexts of innovative educational materials and technological innovations. Chapters 2 and 3 discuss building and using Online Brand Communities (OBCs) to disseminate innovative math educational materials. OBCs are known to be important platforms where consumers can communicate with the brand as well as other consumers. Through the effective use of these platforms, brands could accelerate the process of diffusion of their innovations. However, OBCs will not survive if consumers do not get engaged and participate in these communities. The purpose of this section of the dissertation is to investigate how customer engagement can be increased in social media based Online Brand Communities (OBCs) so that these communities could be effectively used as platforms for disseminating innovations. Different hypotheses are suggested based on the consumer engagement literature and well-known organizational and psychological theories. These hypotheses are then tested in different studies in order to better understand the drivers of customer engagement behavior. Since one of the important factors that can impact the success of OBCs is the size of the communities, chapter 3 discusses Referral Reward Programs (RRPs) as a means for growing the OBC size. In this chapter, different hypotheses are proposed based on well-known psychological theories. These hypotheses are then tested in 3 different research studies to understand the impact of different rewards on customers’ likelihood to participate in the referral programs. The next section of this dissertation which is presented in chapter 5 uses the context of technological innovations, particularly Augmented Reality Smart Glasses (ARSGs). The purpose of this chapter is to understand the factors that would impact consumer’s decision to adopt a particular type of ARSGs: Microsoft HoloLens. The results of the studies in this dissertation have important theoretical and managerial implications in the areas of customer engagement in OBCs, Word-of-Mouth marketing, and consumer’s adoption of innovations

Minds Online: The Interface between Web Science, Cognitive Science, and the Philosophy of Mind

Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis they place on forces and factors that reside at the level of agent–world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind

The Internet of Things Will Thrive by 2025

This report is the latest research report in a sustained effort throughout 2014 by the Pew Research Center Internet Project to mark the 25th anniversary of the creation of the World Wide Web by Sir Tim Berners-LeeThis current report is an analysis of opinions about the likely expansion of the Internet of Things (sometimes called the Cloud of Things), a catchall phrase for the array of devices, appliances, vehicles, wearable material, and sensor-laden parts of the environment that connect to each other and feed data back and forth. It covers the over 1,600 responses that were offered specifically about our question about where the Internet of Things would stand by the year 2025. The report is the next in a series of eight Pew Research and Elon University analyses to be issued this year in which experts will share their expectations about the future of such things as privacy, cybersecurity, and net neutrality. It includes some of the best and most provocative of the predictions survey respondents made when specifically asked to share their views about the evolution of embedded and wearable computing and the Internet of Things

Outdoor Education and Mobile Learning: an Autobiographical Narrative Using Application-Based Information and Resources

Although mobile learning using smartphones and applications or apps have the potential to inform and educate individuals in an outdoor environment, users may find that connectivity issues and basic knowledge of outdoor environments, including both physical and emotional, could be limited by what this technology provided. This study provided my perspective as both participant and researcher on a journey over 150 miles on the Colorado Trail, using my iPhone as my primary tool for navigation and information for learning how to survive in an outdoor environment. From the beginning, the physical effects were difficult to overcome, but it was the psychological toll that became my greatest obstacle and the one element where mobile learning in the outdoor environment proved to have the greatest value. While this was one perspective, in a single study, by one participant, in which mobile learning in an outdoor environment took place, there were several themes that developed in regards to data connection, the use of fluid apps, the usefulness of static apps, and the restrictions of power in rural mountainous environments. These themes were emphasized to help future researchers further develop this information to help in the continued development of outdoor education using mobile learning

What explains continuance intention in smartwatches?

Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157-169. DOI: 10.1016/j.jretconser.2018.03.017Smartwatch is a recent and significant development in the domain of wearable technology. We study continuance intention and its determinants, using a combination of the expectation-confirmation model (ECM) with habit, perceived usability, and perceived enjoyment, to explain the continuance intention of smartwatches. Based on a sample of 574 individuals collected from the USA, we show that relationships of ECM enhance the continuance intention, such as confirmation, perceived usefulness, and satisfaction, and also the role of habit and perceived usability. Additionally, we find that habit was the most important feature to explain the continuance intention of smartwatches. The paper ends with a discussion of the study's limitations and implications.authorsversionpublishe

Determinants of continuance intention in wearables : the case of smartwatches

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceSmartwatch sales have been growing for the past few years, but their regular use is still sub-par. Understanding the primary determinants of smartwatch continuance intention is thus important for brands, researchers, and users alike. Therefore, a conceptual model was developed that combines the expectation-confirmation model (ECM) with habit, perceived usability, and perceived enjoyment, to explain the continuance intention of smartwatches. To test the conceptual model, we collected data from the U.S.A. (574 valid cases). Our results support the relationships of ECM, such as confirmation, perceived usefulness, and satisfaction, and also the role of habit and perceived usability. Habit was the most important factor to explain the continuance intention of smartwatches

Investigating how educational technologies can enhance learning experiences by assisting different learning activities

Current educational technology implementations are done independently and not necessarily linked, neither with key elements of the pedagogic model, nor accommodating different learning styles. This work focuses on developing a framework that would standardise the use of assistive technologies in education. In particular, the focus of this work is on how social media, computer-assisted assessment, augmented and mixed reality can be used to improve the learning experience in certain educational contexts. This research study is based on a combination of grounded theory that included a literature review on the following relevant areas, covering key topics that correspond to the dimensions of the proposed framework: i) communication in education; ii) assessment; iii) and feedback. This stage provided a review of the learning activity spectrum that can be affected by educational technologies. The deliverable of this stage was a detailed literature review with distinct links to the action research in the form of specific pilot studies. The following stage provides a discussion on the impact of educational technologies on learning activities. The main deliverable is a review of current technologies with emphasis on how they affect specific learning activities The research also included an element of action research in the form of six pilot studies: i) Google Glass: Student Experience; ii) Google Glass: Presentation Feedback; iii) Google Glass: Feedback on Feedback; iv) Google Glass: Voting System; v) Social Media: Facebook/Twitter/LinkedIn; vi) Student Observable Behaviour. The pilots were conducted and analysed in order to provide sufficient evidence supporting the proposed framework guidelines. The framework proposed consists of four dimensions: i) content; ii) communication; iii) assessment; iv) feedback. This framework is a framework of good practice. It can be used to support academics who wishes to deploy educational technologies in support of a range of learning activities. Furthermore, the framework has the flexibility of applying different educational technologies for different scenarios without missing a standardised evaluation criteria

Three Essays on Friend Recommendation Systems for Online Social Networks

Social networking sites (SNSs) first appeared in the mid-90s. In recent years, however, Web 2.0 technologies have made modern SNSs increasingly popular and easier to use, and social networking has expanded explosively across the web. This brought a massive number of new users. Two of the most popular SNSs, Facebook and Twitter, have reached one billion users and exceeded half billion users, respectively. Too many new users may cause the cold start problem. Users sign up on a SNS and discover they do not have any friends. Normally, SNSs solve this problem by recommending potential friends. The current major methods for friend recommendations are profile matching and “friends-of-friends.” The profile matching method compares two users’ profiles. This is relatively inflexible because it ignores the changing nature of users. It also requires complete profiles. The friends-of-friends method can only find people who are likely to be previously known to each other and neglects many users who share the same interests. To the best of my knowledge, existing research has not proposed guidelines for building a better recommendation system based on context information (location information) and user-generated content (UGC). This dissertation consists of three essays. The first essay focuses on location information and then develops a framework for using location to recommend friends--a framework that is not limited to making only known people recommendations but that also adds stranger recommendations. The second essay employs UGC by developing a text analytic framework that discovers users’ interests and personalities and uses this information to recommend friends. The third essay discusses friend recommendations in a certain type of online community – health and fitness social networking sites, physical activities and health status become more important factors in this case. Essay 1: Location-sensitive Friend Recommendations in Online Social Networks GPS-embedded smart devices and wearable devices such as smart phones, tablets, smart watches, etc., have significantly increased in recent years. Because of them, users can record their location at anytime and anyplace. SNSs such as Foursquare, Facebook, and Twitter all have developed their own location-based services to collect users’ location check-in data and provide location-sensitive services such as location-based promotions. None of these sites, however, have used location information to make friend recommendations. In this essay, we investigate a new model to make friend recommendations. This model includes location check-in data as predictors and calculates users’ check-in histories--users’ life patterns--to make friend recommendations. The results of our experiment show that this novel model provides better performance in making friend recommendations. Essay 2: Novel Friend Recommendations Based on User-generated Contents More and more users have joined and contributed to SNSs. Users share stories of their daily life (such as having delicious food, enjoying shopping, traveling, hanging out, etc.) and leave comments. This huge amount of UGC could provide rich data for building an accurate, adaptable, effective, and extensible user model that reflects users’ interests, their sentiments about different type of locations, and their personalities. From the computer-supported social matching process, these attributes could influence friend matches. Unfortunately, none of the previous studies in this area have focused on using these extracted meta-text features for friend recommendation systems. In this study, we develop a text analytic framework and apply it to UGCs on SNSs. By extracting interests and personality features from UGCs, we can make text-based friend recommendations. The results of our experiment show that text features could further improve recommendation performance. Essay 3: Friend Recommendations in Health/Fitness Social Networking Sites Thanks to the growing number of wearable devices, online health/fitness communities are becoming more and more popular. This type of social networking sites offers individuals the opportunity to monitor their diet process and motivating them to change their lifestyles. Users can improve their physical activity level and health status by receiving information, advice and supports from their friends in the social networks. Many studies have confirmed that social network structure and the degree of homophily in a network will affect how health behavior and innovations are spread. However, very few studies have focused on the opposite, the impact from users’ daily activities for building friendships in a health/fitness social networking site. In this study, we track and collect users’ daily activities from Record, a famous online fitness social networking sites. By building an analytic framework, we test and evaluate how people’s daily activities could help friend recommendations. The results of our experiment have shown that by using the helps from these information, friend recommendation systems become more accurate and more precise