NANYANG TECHNOLOGICAL UNIVERSITY

Similar documents
LESSON 6: CONSUMER ORIENTED E COMMERCE

THE COLLEGE STUDENTS BEHAVIOR INTENTION OF USING MOBILE PAYMENTS IN TAIWAN: AN EXPLORATORY RESEARCH

Module 3: Entrepreneurship

CONSUMER SATISFACTION IN INDIAN TELECOM INDUSTRY: A CASE STUDY OF BHARTI AIRTEL

Key Points of the 2016 White Paper on Information and Communications in Japan

ScienceDirect. Consumer Online Behaviour: A perspective on Internet Banking Usage in Three Non-Western Countries

How to use internal and external data to realize the potential for changing the game in handset campaigns

ACKNOWLEDGEMENT. hope this thesis will contribute to any parties that need information about shopping. online in Indonesia. Jakarta, March 2003

MOBILE DATA MONETISATION IN EMERGING ASIA-PACIFIC: PRICING AND BUNDLING STRATEGIES

End-User Acceptance Of E-Government Services In an Indonesia Regency

Exploring Technological Factors Affecting the Adoption of M-Commerce in Jordan

Knowledge of Security Protocols and Acceptance of E-commerce

Exploring User Behavioral Intention of the Tourist Guiding System by Users' Perspective

Fintech =Finance + Technology

THE CONTACT CENTER S ROLE

Luxoft and the Internet of Things

Market Analysis and a Detailed Study of a Leading Cloud Telephony and SMS Gateway Company Pawan Kumar Naik 1 Praveen Kumar 2 Dr.S.A.

Using UTAUT to explore the behavior of 3G mobile communication users

USER ACCEPTANCE OF INFORMATION TECHNOLOGY ACROSS CULTURES

CONSUMER ACCEPTANCE OF TRUSTWORTHY E- COMMERCE: AN EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL

The DealerRater Guide to Online Reviews: LEVERAGING REVIEWS FOR A COMPETITIVE EDGE

Contents. List of figures List of tables List of abbreviations Abstract of the PhD thesis Introduction

CONSUMERS PERCEPTION AND PREFERENCE TOWARDS SMARTPHONE

Chapter 4 Research Methodology

CHINA UNICOM ANNOUNCES 2018 INTERIM RESULTS

Factors Affecting Online Customer-to-Customer Purchase Intention: A Study of Indonesian Customers

Exploring Chinese Users Acceptance of Social Commerce Sites

WHAT HAPPENS AFTER ERP IMPLEMENTATION: UNDERSTANDING THE IMPACT OF IS SOPHISTICATION, INTERDEPENDENCE AND DIFFERENTIATION ON PLANT-LEVEL OUTCOMES

Beyond transactions Creating value through customer partnerships in telecommunications. An Economist Intelligence Unit white paper Sponsored by SAP

EFFECT OF CAUSE RELATED MARKETING ON CONSUMER S PURCHASE INTENTION

Management Science Letters

Top 10 Fixed-Line Operators in Western Europe, 3Q03

Journey to 3rd Platform Digital Customer Experience

AIS Contribution in Navigation Operation- Using AIS User Satisfaction Model

Key Performance Indicator (KPI)

EGUIDE TO THE CUSTOMER EXPERIENCE

AN ANALYSIS OF THE EFFECTS OF COMPETITIVE INTELLIGENCE PRACTICES ON THE PERFORMANCE OF PHARMACEUTICAL COMPANIES IN NAIROBI

THE DIGITAL LANDSCAPE IN SOUTH AFRICA A data driven look at South Africa s relationship with digital.

Will Insurance Brokers Use Mobile Insurance Service Platform: An Integration of UTAUT and TTF

Perception of end users from the Subjective Quality Study in the Americas

Prediction of User Acceptance and Adoption of Smart Phone for Learning with Technology Acceptance Model

Decision Making Delays with Regard to IT Investments

Wireless in the Era of Digital Transformation

Knowledge Management System Adoption and Practice in Taiwan Life Insurance Industry: Analysis via Partial Least Squares

Key Success Factors of Smartcard-based Electronic Payment: An Empirical Analysis

Strategy Analysis. Chapter Study Group Learning Materials

How Data Science is Changing the Way Companies Do Business Colin White

Consumer s buying behavior towards online shopping. *Balamurugan K and Munish Kumar M. Abstract

Adoption of mobile internet devices and services: a multinational study

The Influences of Perceived Factors on Consumer Purchasing Behavior: In the Perspective of Online Shopping Capability of Consumers

DECISION SCIENCES INSTITUTE. Explicating mobile banking acceptance in Oman: Structural Equation Model. (Full Paper Submission)

Evaluation Criteria for Enterprise Geocoding

Adopting Technology Acceptance Model to Explore E-shopping Use Intention of Retail Department Store Customers

The Role of Buying Center Members Individual Motivations for the Adoption of Innovative Hybrid Offerings

Mobility at a Crossroads

The value of performance. Capital investment in network quality leads to improved financial performance

Brunel Business School

Gyeong-Seok Byun Korea Institute of Civil Engineering and Building Technology (KICT) Corresponding Author Gyeong-Seok Byun

THE NEW BRAND LANDSCAPE

Transforming Telecom Business: Scaling the Shift using Predictive Analytics

Mobile Devices Usage in Jordanian Banking Sector: Critical Success Factors Based On an improved Technology Acceptance Model (TAM)

Certain unaudited financial and operational information for the nine months and three months ended 30 September 2018.

UNDERSTANDING SHIFTING CONSUMER PRIORITIES IN THE BANKING INDUSTRY

An Integrative Model of Clients' Decision to Adopt an Application Service Provider

First, I d like to talk a bit about how I see

Investing In Next Generation Mobile Platforms To Support Changing Business Models

Exploring Experiential Value in Online Mobile Gaming Adoption

ECOFORUM [Volume 7, Issue 2(15), 2018] CUSTOMER LOYALTY MODEL: CUSTOMER SATISFACTION AS INTERVENING VARIABLE

(Full Paper Submission) Yan Chen Auburn University at Montgomery

Factors Influencing Electronic Government Adoption: Perspectives Of Less Frequent Internet Users Of Pakistan

Toward Modeling the Effects of Cultural Dimension on ICT Acceptance in Indonesia

Mobile Industry Reputation Index April September 2011

A MARKETING BOOKLET: A SOLUTION TO COPE WITH THE UNCLEAR IDENTITY OF HIGH POINT SERVICED APARTMENT SURABAYA

iafor The International Academic Forum

Assessment of ERP Assimilation: The Case of ethio telecom

Challenges and Opportunities in the Digital Service

INTERNATIONAL JOURNAL OF RESEARCH SCIENCE & MANAGEMENT

Social Commerce Adoption Model

Which is the best way to measure job performance: Self-perceptions or official supervisor evaluations?

Interorganizational Systems and Transformation of Interorganizational Relationships: A Relational Perspective

State of the Competitive Nation

An Extended Tam Model to Evaluate User's Acceptance of Electronic Cheque Clearing Systems at Jordanian Commercial Banks

An Empirical Investigation of Consumer Experience on Online Purchase Intention Bing-sheng YAN 1,a, Li-hua LI 2,b and Ke XU 3,c,*

Organization Culture Dimensions as Antecedents of Internet Technology Adoption

CHAPTER 3 RESEARCH METHODOLOGY. This chapter provides an overview of the methodology used in this research. The use

A Study on Customer Satisfaction in Mobile Telecommunication Market by Using SEM and System Dynamic Method

Computer-Aided Dispatch: State-of-the-Art and Future Trends

(AA15) BUSINESS OPERATIONS AND MANAGEMENT

FACTORS INFLUENCING THE INTENTION TO USE MOBILE BANKING SERVICES IN BANGKOK, THAILAND

Top 10 predictions for the telecoms media and digital services sectors in 2018

The Technology Acceptance Model for Competitive Software Products

MIDTERM EXAMINATION Spring 2010 MKT501- Marketing Management

Port of Hamburg Relies on IoE Capabilities to Improve Management of Waterways, Roads, and Rail

HCL TECHNOLOGIES EARNINGS PRESENTATION SECOND QUARTER FY 16 WHERE VALUES DRIVE VELOCITY

ICT Innovation Spring 2017 MSc in Computer Science and MEng Telecom. Engineering EIT Masters ITA, S&P,SDE

Cloud Communications & the Modern Workplace

Make every contact count for you and your customers

Media Influence on Telecom Purchases Among Multicultural Consumers

Using Mobile-Push Technology in Public Transit

APPLICATION OF THE GLOBAL STAR RATING SYSTEM FOR SERVICES. In Collaboration with

Transcription:

NANYANG TECHNOLOGICAL UNIVERSITY Analysis and Findings of the Worldwide Mobile Data Services Survey (2010) Proposal for K6399 Critical Inquiry M.Sc. (Knowledge Management) School of Communication and Information Submitted by Rahul Ramanujam Visalakshi Sekar Kumar

Background and Introduction This project describes in great detail the behavior of customers worldwide in the market for mobile data services. This survey is basically an annual exercise that involves a loosely organized group of universities and research centers around the world. Apart from several other aspects, the main points covered in this research would be 1. Determining the user value that will in-turn facilitate better compartmentalization of users. 2. To gain a better understanding of the behavior of mobile data services in the international arena. 3. How different users perceive and use mobile and data services to satisfy their various needs. According to Analysys Mason which is a Market Intelligence firm, it s estimated that Mobile handset data revenue will lead the growth in telecoms retail revenue worldwide, which will reach USD 1.64 trillion in 2018, up from USD 1.50 trillion in 2012. It is also predicted that mobile handset data will be the single largest source of revenue growth in the next six years. The shift from voice to data looks robust in developed countries and smartphone penetration gains momentum in emerging markets. Traditional voice and messaging services are declining and new data services are taking their place, driven by next-generation mobile networks and the increased ownership of smart devices. The primary aim of this study is to do a statistical data analysis and strive in finding out unique patters in the data set. These unique patterns must correlate to customer behavior, how different users from different regions use mobile data services for various purposes and the overall penetration of mobile data services in various regions across the globe. Problem Statement Mobile data services are one major factor that has come of age in this era that is getting more and more technologically developed. With the increasing number of service providers, there is a rise in competition on a daily basis. This kind of competitive environment calls for newer insights into the what, how and when of mobile data services.

So this is basically about what kind of users use mobile data services. Secondly it s about how they use the data services and for what purpose they use it. And lastly, it s about when and where they use it most frequently. For example the AT&T website says they recently introduced the new sponsored data service for mobile devices. How does it work? Well the carrier says that if the service is in effect users will see a sponsored symbol in the status bar on the screen of their device. And this will indicate that all data charges are being redirected to the sponsoring company. How do plans like these come into effect? No company is going to blindly introduce new plans to customers without a proper survey of the market, understanding customer needs, and understanding how they use mobile data services. So mining and analysis of the data obtained through the worldwide survey is critical to understanding the fact about what users actually need and the penetration of mobile data services in any particular region and the necessary steps, if any, to further deepen the penetration and how the same is done. Moreover, to sustain in this highly competitive market, it s vital to gain user information so that they necessary action can be taken at the right time, in a way that can please the existing customer base as well as pull in new customers. Objective of the Research The primary objective of the research is to analyze the data sets that give us findings about the worldwide mobile data services, and figure out interesting patterns and observations as to how users perceive mobile data services and how they use them in their daily life. The core of this research is basically to identify customer behavior when it comes to using mobile data services and penetration rates in different regions of the world. So first things first, the following are the points that is going to be our main objective for the rest of this research. 1. Find out the profile of users who are more willing to pay for mobile data services. 2. The reason as to why and how they use mobile data services. 3. Penetration in different regions. In addition, we also have a lot of other factors that will come into picture once we have identified useful patterns in the data that correspond to two of our primary objectives.

Schedule & Timelines Here you go with the time frame and specific dates which the group expects to achieve. 30 th January 14 Submission of Research Proposal 6 th February 14 Clean and prepare the data set 20 th February 14 Start mining data using SPSS Statistics / Amos 6 th March 14 Data Analysis and finding out useful patterns 20 th March 14 Results and Conclusion 27 th March 14 Integrate findings and Report Writing 3 rd April 14 Submit 2 copies of CI report to supervisor and independent marker 21 st April 14 CI Presentation 5 th May 14 Submit executive summary Research Scope As the topic suggests, it is important to analyze and find the adoption rate of Mobile data services by the consumers or customers, based on the data collected by the previous researchers on Analysis and Findings on the worldwide Mobile Data Services Survey, this is a longitudinal study of the analysis done previously. From the last study, the scope of this research is as follows: 1) Have customers perception changed in adopting and using these mobile based services. 2) What are the Customer s needs on using mobile-based internet service in different markets that are considered for study and analysis? 3) Which class of customers prefers to use these services in those different markets? 4) What would be the customers preference to use these service in the different markets 5) Does income decides the adoption if these services in different markets 6) Customers perception in adoption to these services in different markets 7) How does the customer chose to adopt the mobile-based internet services This study again depends on the factors that the data collected are thoroughly analyzed and cleansed for this longitudinal study; thus, this puts us on a perspective that all data and information are collected considering the previous research.

Implications / Benefits This study on worldwide adoption rate of mobile data services, gives us the perspective theoretically that the research has to provide an understanding of consumers behaviors in each of the markets worldwide, on analyzing the data extracted. This study would let us propose models that would give profound data to the service providers on how to tackle markets to be sustainable in the business front. The benefits of this longitudinal study are pure benefits for the providers to know what the customers they are to serve and with the proposed model; they can target their customers to maintain their association, which indeed would sustain their growth significantly. This study also puts both the customers as well as the providers on a unique perspective in understanding each other s needs; which creates a momentum for the business for the latter. In addition, this study supplies critical information to service providers to identify features that could serve the right customer at the right market. Again, this study highlights the market needs, which the service providers can work on their strengths and weakness in those markets and identify gaps to serve better. Proposed Methodology The data for analysis is collected through various means from various categories of respondents through a set of questionnaire s, which gives us the categories of the respondents in specific to the markets. The questionnaires are set charily with the association of both the institute and the industry; which serves both the study and the implications that arrives from the research. The different respondents are categorized into common type for analyses. The study is set to execute in a small pilot project in the market that is most susceptible to needs on the mobile data services, where the market demands more but considerable on pricing structure. Further, for each market analysis the executions carried out statistically and are made with the carefully set questionnaires. Several hypotheses are tested statistically thus executed on different markets. We know that this study is very exploratory in nature so that we use the path analysis option of Structured Equation Modeling. According to Gefen et al. (2011), structured equation modeling is the best method for this analysis as it involves in the analyses of the path diagrams for covert variables for compound variables. The SEM is explored with maximum likelihood on IBM SPSS AMOS 22 the stable version of the tool available in the market. Thus, the different attributes and indicators are tested and proposed for the same from the analysis.

References Sharma, R.S. and Felix, L.S. (2008) The Worldwide Mobile Data Services Study (WMDSS): 2008 Singapore Survey and Results, SSRN Document dated December 1, 2008 [online] http://ssrn.com/abstract=1329873 (accessed 6 October 2013). Gefen, K., Rigdon, E.E. and Straub, D.W., (2011) Editor s comments: an update and extension to SEM guidelines for administrative and social science research, MIS Quarterly, Vol. 35, No. 2, pp.iii xiv. Brandon, Russel. Sponsored Data: AT&T will now let companies buy out your data charges for specific videos and apps. The Verge. 6 January 2014. Web. http://www.theverge.com/2014/1/6/5279894/at-t-announces-net-neutrality-baitingsponsored-data-mobile-plans Short, E., James, and Siegel, Jordan (2002) Customer Transitions in Adopting Mobile Data Services, MIS Quarterly, Vol. 35, No. 2, pp.iii xiv Venkatesh, V., Morris, M. G., Davis. G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view, MIS Quarterly, 27(3), 425-478 Kawahara, Toshiro (2002). Customer Transitions Among Mobile Services in the Japanese Telecommunications Industry. Unpublished Master s Thesis. Cambridge: MIT