The Influence of Mobile Technology on Modern Business Practices, Capstone Project Example

Introduction

The influence of mobile technology on modern business practices is explored here. The breadth and depth of disseminating business information and communication via mobile technology is staggering. This topic is related to the MPS program in that it requires the development of a research design and data collection protocol. Furthermore, the knowledge gained will be of applicable and immediate business use. The combination of research methodology and business logic merges to underscore some of the core concepts of the program.

Ultimately, it is of primary interest what impact mobile communications technology has on the average wealth of a given demographic. Based on a sufficiently designed study and data collection process, researchers hope to discover a significant R-squared coefficient for some standard measures for mobile technology dissemination within a given demographic while controlling for demographic characteristics such as age range, gender, country, and economic status. Basically, researchers are trying to answer certain questions with respect to the level of mobile technology use and changes in economic status. Are individuals and business more affluent in places where mobile technology is widely used? Have there been fiscal improvements that can be seen as resultant of mobile technology usage at least in part? If so, what mobile technologies and behaviors are associated with such trends? Based on previous research, it appears as if individuals and business are more affluent in places where mobile technology is widely used, and fiscal improvements can be seen as resultant of mobile technology usage at least in part. As a pilot to further research, behavioral measures will include an open ended question about how mobile technology is used for business. Based upon responses to this question, closed questions can be formulated for further research.

Review of Literature

Some business applications of mobile technology span education and commerce. One of the most important contributions of information communication technologies (ICT) to distance education was the fact that the programs offered had systems that operated with information communication technologies, and with developments in the field, the distance education structure has been changing and developing (Aybar & Gokaliler, 2011). In order to survive in a global environment, distance education institutions have to develop strategies to promote the course contents and benefits to target audiences. To reach target varied demographics, distance educational programs should personalize their advertising messages differently for specific audiences. Mobile marketing provides the availability to institutions to consumers any time, anywhere. By mid-2012, there will be 6 billion mobile phones on worldwide, about three times as many mobile phones as personal computers. Such flexibility and range of communications is unprecedented (Chae & Yeum, 2010). Such convenience and affordability have never before been combined in one device (Jisun & Tugrul, 2010).

ICT has affected business practices in that it has manifested the development of new products, marketing, and in the methods of payment consumers have been adopted (Mbogo, 2010). The methods of payments through the use of mobile phones have been identified as one of the key developments that have revolutionized how business is conducted by small business owners (Mbogo, 2010). Small business who informally and consist mostly of sole proprietors and family businesses employing 5 or less persons are largely unregulated and highly concentrated in specific rural and urban areas (Mbogo, 2010). The critical aspects of their operations is that they do not have bank accounts and find it cumbersome to leave their business and operate these accounts should they acquire them (Mbogo, 2010). These limits provided opportunities for Safcron in 2007 when it created a mobile money transfer system it call M-Pesa, which has become extremely popular with business owners with or without bank accounts to the extent that transactions like paying for goods and services, payment of bills, money transfers to friends and relatives, cash withdrawals and the topping off airtime has dominated activities in the Kenyan small business sector (Mbogo, 2010). Micro-business economies have yet to fully experience entrepreneurial impact of this new technology (Mbogo, 2010). This is one microcosmic example of how what we expect to gauge.

It has been the practice of branding that marketers interacting with their audience, using mobile channels equipped with SMS, MMS, E-mail, mobile internet, wireless advertising, voice, alternate alerts, date services like mobile TV, and picture recognition among others (Becker, 2012). The objective of mobile marketing is based on the approach of the Direct Marketing Association model of striving to achieve response fulfillment through CRM, advertising, branding, customer service support, sales promotions support, research and data collection, interactivity direct sales and store traffic generation (Becker, 2012). The concept also provides insights into why the innovation has been adopted, and how it was being used to meet changing needs, given its attributes, which include relative advantage, compatibility, and capacity to reorient to fit local conditions as well as its propensity to uncover uses capable to meeting greater spectrum of needs (Martin & Abbot, 2011). Mobile phones, like all other technological devices, have different impact on people and societies, and as such business organizations will need to conduct culture specific research, in order to develop and market phones with specific capabilities that will have the ideal customer appeal (Martin & Abbot, 2011).

The Network Readiness of a country is an indication of the level of technological business activity that it is undergoing, as well as its capacity to develop and attract even more in the future, once proper assessment, investments and acquisitions are made (Dutta and Mia, 2009). Out of 134 countries, Denmark scored the highest with 5.85 (Dutta and Mia, 2009). Twenty-three countries scored above 5, 30 scored between 4 and 5, and 69 between 3 and 4 (Dutta and Mia, 2009). The rate of technological advancement globally has left only about 15 countries needing business organizations to develop their market (Dutta and Mia, 2009). This bodes well for both market seeking global mobile technology corporations as well as people living in abject poverty to mutually benefit (Dutta and Mia, 2009). The global recession has negatively impacted global economies, but the resilience of the technological sector rapidly manifested a response due innovation that spawned a market retailing PCs under $300 such that that working and lower class demographics can afford them (Dutta and Mia, 2009).

Such trends have positively impacted productivity across the global economy as a result of the extraordinary leverage of technological innovation (Dutta and Mia, 2009). South Korea, Singapore, Israel, Finland and Estonia have increased their global competitiveness by positioning their ICT at the heart of their national motivation and strategy development (Dutta and Mia, 2009). Mobile technology in Africa, Latin America and Asia has also transformed social interactions, reduced poverty, and improved the lives of millions of people in these regions (Dutta and Mia, 2009).

Consumers do not usually rate products on the basis of its main utility but more on the set of intangible factors like image and service (Foret & Prochazka, 2007). With mobile technology beyond mere calling devices, manufactures were bringing to light features that would influence consumers to buy their products in diverse locations (Hjorth, 2008). Four different types of consumption activities beyond basic need satisfaction have been identified (Solomon, 2008). These are consumption as an experience, as an instrument of integration, a game, and a classification scale which deal with how they are perceived and ranked in society (Solomon, 2008). Thus, consumers are more likely choose companies that best tend to these consumption issues in the making processes so companies strategically provide the relevant solutions to these considerations with the necessary incentives.

The Global Information Technology Report has provided an internet classification status report which be used as a launching pad for global corporations to use to export mobile technology to the 157 listed countries of the world, and successfully influence the type and nature of business activities that will take place (Dutta and Mia, 2009). Each country in terms of internet development has to go through six stages, and these are the Pro-Internet phase, Early Days, Familiarization phase, Extensive and Intensive phase and finally the Ubiquity stage (Dutta and Mia, 2009). The description given for each classification provides vital information to mobile technology and other business organizations to use to develop market penetration strategies to establish viable infrastructural networks (Dutta and Mia, 2009). A Pro-Internet country is one in which less than 5% of its population has had internet experience, and at the time of reporting there were 45 countries that falls into this category and together that have a population of 800 million people (Dutta and Mia, 2009).

In terms of the Early Days category, these are countries that have had 5 to 15 % of their people having internet experience and the report found 32 countries totaling 2.2 billion in population falling in this category with most of the usage of the technology concentrating mainly in urban areas (Dutta and Mia, 2009). It could be argued that the reason for the concentration of internet user in urban areas of these countries may be due to the availability of electricity, wealth distribution, job availability, a high concentration of educational institutions, and access to other vital social amenities like water and roads and adequate food and health facilities. Thirty-nine countries with population internet experience averaging 28% constitute the Familiarization category, and they include Brazil, Chile, Turkey and Thailand, which all had a combined population of 2.2 billion people (Dutta and Mia, 2009).

In comparison the Extensive user stage countries are all at a transitional development stage in terms of internet connection, with only one-quarter of the population of 400 million people having experience in the use of the technology (Dutta and Mia (2009). These countries, which include Russia, Malaysia, and the Czech Republic, are yet to have broadband technology widely distributed across their environmental technological landscape (Dutta and Mia, 2009). Intensive category users encompass 23 countries numbering 850 million whose internet experience amounts to 66.66 % (Dutta and Mia, 2009). The same percentage of these households provide best practice examples for Net Strategy model that companies globally, can study and replicate in other categories, for the future maximization of their investments (Dutta and Mia, 2009). The USA, Finland, South Korea and the Republic of Korea as countries falling into the Intensive Internet development stage, and has hastened to add that no country has been identified as qualified applicants for the Ubiquity Phase to date, but these countries are positioned to enter and fulfill the scenario, where internet connections would follow connection users around the world, instead of users traveling around seeking internet connections (Dutta and Mia, 2009). Business practices will differ in different parts of the world, in terms of the type, prices, and quality and volume of mobile technology products and services successfully marketed, as well as the pre and post purchase training and other services that will be offered (Dutta and Mia, 2009). Marketing strategies for Pro-Internet countries with only 5% internet experience will drastically differ from countries that are in the Intensive phase with nearly 67% of their populations having internet experience, and some companies may seek to develop niche market in either of these areas as well as those in the intermediate stage, but would have to significantly modify their final package to meet the attributes of each target market (Dutta and Mia, 2009).

One way of gauging the impact upon a demographic or sector is to simply correlate trends over time. That is, if a measure of mobile technology applicability, acceptance, and usage over time could be compared to profit or production or some such indicator over the same time frame for the same sample set, analysts could statistically estimate the relative impact of the one against the other. It seems such an endeavor would include a partial replication of some of the previous research while synthesizing elements from previous studies into a pilot platform. At any rate, it behooves researchers to avoid reinventing the wheel. Precautions should be taken to implement previously standardized measures and methods for the sake consistency between protocols. The primary concern of this research is to investigate how mobile phone usage impacts wealth. It has been demonstrated in some countries to show a positive correlation. This investigation seeks to delineate the magnitude of this impact.

This particular research project leaders has identified network readiness distribution across regions, sales and distribution patterns of mobile technological devices, comparative revenue growth among mobile technology providers by region, type and description of marketing strategies, target markets populations and revenue gain per thousand, percentage of market penetration, growth in mobile banking transactions, annual growth and changes in rural and urban business structure by regions as variables that will be considered for use in measuring the influence of mobile technology of business practice.

Definitions of Variables

To measure the influence of mobile technology on business practices globally, a number of variables have been identified to research relationships between network readiness, usability, technology diffusion, personal productivity, national wealth, and quality of life. Network readiness distribution across regions, distribution patterns of mobile technological devices, affluence, rural and urban differences have been considered.

The following are the established research variables.

1. Income Level
2. Rural/Urban
3. Country
   1. GDP (as an indicator of national wealth)
   2. Human Development Index (HDI) (as an indicator of quality of life)
   3. Network Readiness (actual)
4. Adaptability
5. Mobile Device Type
6. Effect on Finance
7. PC Usage Compared to Mobile Device
8. Effect on Productivity

The final yes/no question in Appendix A is geared toward measuring impressions of network adaptability (Liang, Huang, Yeh & Lin, 2007). The final true/false question in Appendix B is geared toward measuring usability (Vuolle, Aula, Kulju, Vainio & Wigelius, 2008). The questions has been verified for reliability and validity (Liang, Huang, Yeh & Lin, 2007; Vuolle, Aula, Kulju, Vainio & Wigelius, 2008). Researchers will be required to mine data from publically available sources to code variables for GDP, HDI, and Network Readiness.

Because this is essentially a correlative study, there really are no dependent or independent variables. Each research variable will be compared against all others.

Method of Investigation

To attain a statistically significant sampling, researchers expect to collect no less than 30 surveys and no more than 100. The data collection process will include online surveys. Country data will be gathered from appropriate nationally published datasets as found on the Web to perform the correlation matrix data analysis. Random selection will ensure an unbiased sample. The reason for choosing an unbiased sample is an effort to implement standard control procedures in the investigation. Callers will call randomly generated numbers and ask the answering party to participate in the study. No compensation will be offered in an effort to further control selection bias. This correlation design will rely upon questionnaires (Appendices) as the data collection measure. Correlation analysis between each of the variables will constitute the results of the study.

Appendix A: Research Instrument

Demographic Questionnaire

1. Which of the following best describes your income level?
   1. Under $1,000 per year
   2. $1,000 to $10,000 per year
   3. Over $10,000 up to $20,000 per year
   4. Over $20,000 up to $30,000 per year
   5. Over $30,000 up to $50,000 per year
   6. Over $50,000 up to $70,000 per year
   7. More than $70,000 per year
2. Do you live in a more rural or more urban community?
   1. Rural
   2. Urban
3. In what country do you live?
4. Does the system satisfy the user needs?
   1. Yes
   2. No

Appendix B: Research Instrument

Mobile Usage and Acceptance Questionnaire

1. Which best describes your mobile device?
   1. Cellular phone
   2. Smart phone
   3. Tablet
   4. Net Book
   5. Multiple devices
   6. None
2. Which of the following best describes how you feel about the way your mobile device or devices have affected your finances?
   1. My mobile device or devices have made me more money than I spend on them.
   2. My mobile device or devices have made me less money than I spend on them
3. Which of the following best describes your PC use compared to your mobile device use?
   1. I use mobile device or devices less than a PC.
   2. I use mobile device or devices more than a PC.
4. Using the mobile service in my job increases my productivity.
   1. True
   2. False

References

Aybar, A.S., and Gokaliler, E. (2011). A more effective way to advertise the distance education programs: Mobile marketing approach. Turkish Online Journal of Distance Education, 12(2).

Becker, M. (2012). Mobile marketing research priorities: Roadmap to engaging the “connected customer”. Academic Review. Retrieved from http://www.mmaglobal.com/articles/mobile-marketing-research-priorities-roadmap-engaging-%E2%80%9Cconnected-customer%E2%80%9D

Chae, M. & Yeum, D. (2010). The impact of mobile technology paradox perception and personal risk-taking behaviors on mobile technology adoption. International Journal of Management Science, 16(2): 115-138.

Dutta, S., Mia, I. (2009). The global information technology report, 2008–2009: Mobility in a networked world. World Economic Forum. Retrieved from www.members.weforum.org/pdf/gitr/2009/gitr09fullreport.pdf

Foret, M. & Protozoa, P. (2007). Buying behavior of households in the Czech Republic. Agricultural Economics – Czech, 53 (7): 318–324.

Hjorth, L. (2008) Being real in the mobile reel. Convergence: The Journal of Research into New Media Technologies, 14(1): 91-104.

Jensen, R. (2007). The digital provide: Information (technology), market performance, and welfare in the South Indian fisheries sector. The Quarterly Journal of Economics, 122(3): 879–924.

Jisun, K. & Tugrul, A. (2010). A look into the future of wireless mobile communication technologies. Technology Analysis and Strategic Management, 22(8): 925-943.

Liang, T., Huang, C., Yeh, Y. & Lin, B. (2007). Adoption of mobile technology in business: a fit-viability model. Industrial Management & Data Systems, 107: 1154 – 1169.

Martin, B, L. & Abbot, E. (2011). Mobile phones and rural livelihoods: Diffusion, uses, and perceived impacts among farmers in rural Uganda. Annenberg School for Communication & Journalism, 7(4): 17–34

Mbogo, M. (2010). The Impact of mobile payments on the success and growth of micro-business: The case of M-Pesa in Kenya. The Journal of Language, Technology & Entrepreneurship in Africa, 2(1).

Solomon M.R. (2004). Consumer Behavior. Buying, Having, and Being. Prentice Hall: Saddle River.

Vuolle, M., Aula, A., Kulju, M., Vainio, T. & Wigelius (2008). Identifying usability and productivity dimensions for measuring the success of mobile business services. Advances in Human-Computer Interaction: doi:10.1155/2008/680159.