scholarly journals How Do Emotions Impact Mobile Services Acceptance? A Systematic Literature Review

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Boris Ovčjak ◽  
Marjan Heričko ◽  
Gregor Polančič
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Mobile Services ◽  
Services Research ◽  
Related Factors ◽  
Emotional Factor ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
Emotional Factors

Mobile data services have been rapidly developing and expanding in the recent years; therefore many studies focus on researching their acceptance and use in general or by observing different viewpoints. One of these is emotions, which influence our beliefs and attitudes that impact our decisions and actions. The objective of our research was therefore to explore the field of mobile data services acceptance in regard to emotional factors. We performed a systematic literature review of emotional concepts and their relationships, provided by 43 primary studies. Consequently, our study includes an aggregation of emotional factors obtained from related and reviewed literature, with their definitions and the extent of their usage. Furthermore, it analyses the proportion of emotional factors against all acceptance-related factors as well as the extent of their use through time. Our study tries to guide future work by aggregating the relations that include at least one emotional factor and by providing the rate of their significance. Finally, the study tends to determine the viability of the emotional factors by observing their direct influences on users’ intention and proposes a generic theoretical model for supporting future mobile services research.

Mobile Markets vs. Mobile Ecosystems

2011 ◽  
pp. 194-211
Author(s):  
Jarkko Vesa
Keyword(s):  
Double Helix ◽  
Mobile Services ◽  
Future Trends ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Current Structure ◽  
Data Services ◽  
The Future ◽  
Services Industry ◽  
The Uk

Now as we have gone through the characteristics of the three case markets, it is time to figure out what our analysis has revealed. In other words, what can we tell about the differences between the Japanese and the European mobile services markets — or more specifically, the Finnish and the UK market? It is time to merge the theoretical discussions of Chapters IV to VI, and the case analyses of Chapters VII to X in order to gain a better understanding of the current structure and the future trends of the mobile data services industry. Let us start by comparing the three markets by using the Double Helix model.

User intention and consumer needs of packaged mobile data services in Mexico

2010 ◽  
Vol 1 (2) ◽  
pp. 129 ◽  
Author(s):  
Alejandro Ibarra Yunez ◽  
Raquel Castano ◽  
Luis E. Perez Monjaras
Keyword(s):  
User Intention ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services

Performance Measurement for New Mobile Data Services During Generation Upgrading Period: A Case of China's Telecom Industry

2021 ◽  
Author(s):  
Yu Du ◽  
Xiaohang Zhang ◽  
Zhengren Li ◽  
Yijun Guo
Keyword(s):  
Performance Measurement ◽  
Quantitative Model ◽  
Service Development ◽  
Data Service ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
Reliability Indicators ◽  
Mobile Data Service ◽  
New Generation

Abstract For the global telecom operators, mobile data services have gradually taken the part of traditional voice services to become the main revenue growth point. However, during the upgrading period of new generation networks (Such as 5G), new mobile data services are still at the stage of exploration, the network capabilities and the application scenarios are unmatured. In this phase, it is incomplete and misleading to simply measure the performance of new services from one dimension, such as data traffic or revenue, and the measurement should be dynamically changed according to the development of the new services. Therefore, telecom operators want to improve the existing performance measurement from the aspect of integrity and dynamics. In this paper, we propose Mobile-data-service Development Index (MDDI), and build a quantitative model to dynamic measure the overall performance of mobile data services. To approach a fuller understanding, we creatively bring investment indicators and networks reliability indicators into performance indicators system, and discuss the relationships among subindices and the selection of outcome criteria in MDDI. In the part of empirical research, we use the model to analyze the dynamic characteristics of a new mobile data service in China, and summarize the development strategies of every stage. The findings can also give guidelines for new services of 5G and other new generation networks in the future.

United States of America

2011 ◽  
pp. 240-258
Author(s):  
Mats Samuelsson ◽  
Nikhilesh Dholakia ◽  
Sanjeev Sardana
Keyword(s):  
United States ◽  
United States Of America ◽  
New Technologies ◽  
Mobile Telephony ◽  
Technological Capabilities ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
Mobile Industry ◽  
The U.S

Somewhat behind in the mobile telephony adoption than leading European and Asian markets, the U.S. market caught up in the 2000s. While simple types of mobile data services — such as messaging and downloads — had made some headway, the preexisting popularity of PC-based Internet made the U.S. users somewhat resistant to m-commerce offerings that did not match the richness of PC e-commerce. By the mid-2000s, however, network and technological capabilities were in place to usher in rich, new m-commerce offerings in U.S. markets. By taking advantage of new technologies, the U.S. mobile industry had the opportunity to become an innovator in m-commerce offerings.

Modeling the Dynamics of Emerging Mobile Data Services Markets

2011 ◽  
pp. 161-178
Author(s):  
Arthur Lee Gilbert ◽  
Hilda Han Mei Ian
Keyword(s):  
Critical Mass ◽  
Field Research ◽  
Social Contexts ◽  
Enabling Technology ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Technology Learning ◽  
Data Services ◽  
Innovation Diffusion Theory ◽  
Value Propositions

Like the Internet, a critical mass is essential in recovering the initial costs of development and deployment of mobile data services (MDS). Thus, MDS deployment must create new value and generate new behaviors in specific social contexts over time. Some behaviors of interest include making decisions to acquire the enabling technology, learning to use it, applying it, and then, by word-of-mouth, encouraging others to join in. This chapter examines the evolving MDS phenomenon and recommends a multimodal approach to research in emergent MDS markets based on recent findings. This work draws on field research by Nanyang Business School’s Information Management Research Center (IMARC) focused on the application of innovation diffusion theory to market segmentation. The authors also describe the enabling technology and applications, discuss the value propositions, and propose a model to segment the MDS market.

Buongiorno! MyAlert

2009 ◽  
pp. 1738-1753
Author(s):  
Guillermo de Haro ◽  
José María García
Keyword(s):  
Mobile Devices ◽  
Charles Darwin ◽  
Vice President ◽  
Internet Services ◽  
Mobile Data ◽  
Mobile Data Services ◽  
Data Services ◽  
The Creation ◽  
European Sector ◽  
Bubble Burst

In 1999 Jorge Mata, vice president of Broadvision and former expert in interactive solutions for Banco Santander and McKinsey, decided to leave everything to create MyAlert. The company was born on the basis of offering the same Internet services on the new and growing mobile devices. With a strong financial capitalization after raising more than 50 million euros during the bubble burst, in 4 years the company figures were in the black, and the journey had led to the creation of the European sector of mobile data services market and the European leader in that sector. As Charles Darwin emphasized, if a being wants to survive in a shifting environment, it must evolve at least as fast as the medium itself: Buorngiorno! MyAlert ruled the change.

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