A value chain model for mobile data service providers

2002 ◽  
Vol 26 (9-10) ◽  
pp. 551-571 ◽  
Author(s):  
Phillip Olla ◽  
Nandish V Patel
Keyword(s):  
Value Chain ◽  
Service Providers ◽  
Chain Model ◽  
Data Service ◽  
Mobile Data ◽  
A Value ◽  
Mobile Data Service

Determinants of Customers’ Brand Choice and Continuance Intentions with Mobile Data Service Provider: The Role of Past Experience

2018 ◽  
Vol 19 (6) ◽  
pp. 1478-1493 ◽  
Author(s):  
Obinna C. Ojiaku ◽  
Aihie Osarenkhoe
Keyword(s):  
Service Quality ◽  
Service Providers ◽  
Brand Image ◽  
Brand Choice ◽  
Past Experience ◽  
Mobile Service ◽  
Data Service ◽  
Mobile Data ◽  
Mobile Data Service ◽  
The Impact

The prevalence of mobile data services has intensified competition and structured the market for mobile telecommunication services, resulting in decreased revenue particularly from voices services and high churn rate. Mobile service providers therefore seek ways to increase revenue by attracting and retaining mobile data users. This study investigates the determinants of customers’ brand choice and continuance intentions with mobile service providers in the context of mobile data service. This study also captures the impact of past experience on behavioural outcomes. Data were collected from 304 customers of mobile data service firms and analysed using regression analyses. Results indicate that mobile service quality, pricing structure and promotion, but not brand image, affect brand choice, whereas continuance intentions are affected by the mobile service quality, brand image and price. Customers’ past experience relates significantly and negatively to brand choice but not continuance intention. The contribution and implication of the study are discussed.

scholarly journals The EU weather value chain - past, current and future perspectives

2021 ◽  
Author(s):  
Karl Gutbrod
Keyword(s):  
Value Creation ◽  
Value Chain ◽  
Service Providers ◽  
Annual Reports ◽  
Chain Model ◽  
Future Evolution ◽  
The Past ◽  
A Value ◽  
The Usa ◽  
The Eu

<p>The EU weather value chain has developed vigorously, with private services growing at a 20% p.a. rate over the past decade. Growth has also happened amongst national services, and the sector of instrument providers.</p><p>The study uses a value chain model of five steps : 1. Instrument Supply, 2. Networks, (for operation of Measurements & Observations), 3. Data processing, 4. Products (Mass distribution) and 5. Tailored services.</p><p>The study analyses the entire value chain in selected countries, mainly United Kingdom, Netherlands, Germany, Switzerland, Austria, France, Spain, Italy and Czechia, including all steps from instrument to service providers, including national and private services, and quantifies their evolution over the period from 2010 to 2019. It uses annual reports, press articles and other sources to estimate development of value creation, in terms of annual budgets, revenues, profits and employment. It also attempts to identify the sources of uncertainty for the assessments and propose techniques to reduce this uncertainty.</p><p>Further, it classifies the value creation by value chain step and market segment, and attempts to differentiate between domestic and export of products and services.</p><p>The study further compares the value creation by inhabitant, GDP, area and other social parameters, to create parameters which can be used for characterising the value chain, and developing a better understanding of causal factors enhancing the development of the weather value chain in selected countries. These parameters are then compared with those of more other highly developed value chains in the USA and Japan.</p><p>In a final step, the study makes some projections about future evolution of the weather value chain and recommendations for the future development of a more productive and beneficial value chain.</p>

Mobile devices for academic practices by students of college of sciences in selected Nigerian private universities

2015 ◽  
Vol 33 (4) ◽  
pp. 749-759 ◽  
Author(s):  
Joseph Kehinde Fasae ◽  
Idowu Adegbilero-Iwari
Keyword(s):  
Mobile Devices ◽  
Service Providers ◽  
Private Universities ◽  
Data Service ◽  
Science Students ◽  
Mobile Data ◽  
Content Type ◽  
Academic Practices ◽  
Mobile Data Service ◽  
Privately Owned

Purpose – This study aims to look at the use of mobile devices by science students with emphasis only on privately owned universities in Nigeria. Design/methodology/approach – A descriptive research design was used, as the study was a survey research. Eighty copies of structured questionnaire were distributed to collect data from science students in advanced levels of their undergraduate programmes in Afe Babalola University, Ado-Ekiti (ABUAD) and Joseph Ayo Babalola University (JABU) Ikeji-Arakeji, in their lecture halls and laboratories with the permission and assistance of their lecturers. The data were collected within a period of five weeks. All the administered questionnaire were correctly filled and returned, yielding a 100 per cent return rate. The data were analysed using descriptive statistics which includes frequency and percentage presented in tables and charts. Findings – The study found that science students in the selected private universities mostly (83.7 per cent) use smartphones than other mobile devices. Also, the students own mobile devices for the purpose of using educational applications (77.50 per cent) and to chat with people (72.50 per cent). The students use the Internet on their devices very often. The Internet facilities mostly used by the students are e-mails (71.25 per cent), social media (68.75 per cent) and search engines (60.50 per cent). The challenges mostly faced by the students using mobile devices for academic practices are poor Internet connectivity (81.25 per cent) and high cost of data subscription (53.75 per cent). Practical implications – Given the knowledge gained from this study, it is desired that universities across Nigeria would encourage the integration of the use of mobile devices into core educational programmes. Also, mobile data service providers need to reduce the cost of data subscription, especially on campuses for students. Moreover, owners of private universities should ensure the provision of good Internet connectivity for mobile devices campus-wide. Free and accessible Wi-Fi hot spots should be created for students. Social implications – Policy makers in the country should encourage mobile data service providers to reduce cost of data subscription on university campuses so as to enable students enjoy to the fullest the numerous features of mobile devices for academic practices. Originality/value – Research on the use of mobile devices for academic practices by students is somewhat new in Nigeria more so that privately owned universities are in focus. The study has therefore opened the floor for more in-depth studies on the subject now that mobile devices should be seen as tools rather than fanciful gadgets.

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.

Understanding a Business Incubator as a Start-Up Factory: A Value Chain Model Perspective

2019 ◽  
Vol 16 (03) ◽  
pp. 1950025 ◽  
Author(s):  
Eric Christian Brun
Keyword(s):  
Value Chain ◽  
Qualitative Content Analysis ◽  
Chain Model ◽  
Venture Creation ◽  
Business Incubator ◽  
Business Incubation ◽  
Theoretical Understanding ◽  
A Value ◽  
Start Up ◽  
Development Processes

This study proposes a value chain model for business incubation. It describes both an incubated start-up’s development of its own product and business and the incubator’s development of the start-up from entrance to exit as a “product” of the incubator. The reported research is based on qualitative content analysis of 15 start-up cases in a Norwegian business incubator. The reported research enhances our theoretical understanding of start-up development processes within an incubator and provides a framework that will be useful for incubator management to guide incubatees through their venture creation process.

scholarly journals Performance trends for operational intelligence through value chain model

2016 ◽  
Vol 5 (2) ◽  
pp. 34 ◽  
Author(s):  
Rajeev Kaula
Keyword(s):  
Value Chain ◽  
Business Processes ◽  
Chain Model ◽  
Business Rules ◽  
Successful Management ◽  
Business Operations ◽  
A Value ◽  
Performance Trends ◽  
Operational Intelligence ◽  
Business Competitiveness

Value chain is a successful management model for improving business competitiveness. A value chain based analytic approach facilitates meaningful grouping of business processes such that appropriate value from business operations can be derived. As organizations focus on competitive advantage and growth, a value chain derived operational intelligence provides insight to compete successfully in the marketplace. This paper outlines an approach to develop performance based value metrics in the form of analytic business rules for operational intelligence through the value chain model. The paper illustrates the concepts through a University value chain prototype which is implemented in Oracle’s PL/SQL language.

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