The main purpose of the research is to analyze the effect of omitting small data analytics (SDA) in decision making processes in the Telecom industry to enhance innovation. The researcher hopes to achieve this objective by investigating the effects that Telecom companies in Jordan face due to omission of the SDA in promoting innovation to gain competitive advantage in the dynamic market. The researcher will use qualitative research method to analyze the collected data. Data collection will be done through face to face interviews by senior executives of the firms. NVivo software will be used to analyze the data ensuring that the data is coded to the relevant themes attained throughout the research. Scholarly peer reviewed articles published between 2013 and 2018 will be used to further enhance the concept of integrating SDA in short term decision making processes for innovation.
Keywords: Small data analytics, big data analytics, innovation.
Introduction: Background Information
The technological developments witnessed in the contemporary world have enabled generation of data for various analytical research projects in different scopes of the economy. For instance, technology has been used to generate data to assess the market value of a company’s product, the level of competition as well as the significance of corporate social responsibility to business organizations. Data has become a necessary resource in the current world. The recent past years have been characterized by the use disruptive technology, which has introduced the big data (BD) concept. Fundamentally, BD has been used to distinguish the old structured and known data from the current era of data.
To begin with, BD is a huge amount of diverse data types that can be used to support a number of different categories of decisions in firms. BD can be generated both internally and externally by organizations. The organizations are left with the task of comprehending the usefulness of BD in promoting sound organizational management and decision making processes. According to Tsai et al. (2016, P.15), firms need to fashion sustainable practices that are tailored towards harnessing the BD in their systems thereby enhancing the need for promoting quality performance characterized by insightful decision making brought about by technological inventions and innovations. Firms that do not focus on integrating the use of BD in their decision making are likely to be rendered redundant.
Statement of Purpose
Although there has been notable increase in the use of BD by firms in Australia that has positively transformed the way business organizations in the Telecom industry have enhanced quality, efficiency and effectiveness in service delivery, there are deficiencies in the use of BDA (Butler-Kisber, 2017, P.5). Unlike in the traditional use of SD, Telecom Companies have successfully integrated BDA to enhance innovation. In simpler terms, there is a general literature gap on how Telecom Companies use BDA to meet the diverse consumer needs in the ever competitive and dynamic market in Australia.
Scope of the Research
The research will be restricted to professional analysis conducted in Jordan between 2014 and 2018 on how Telecom Companies used big data analytics (BDA) to promote innovation. The decision to consider recent professional analysis was based on the idea that BDA is a new concept in the Telecom industry and thus Telecom Companies are at a startup level of integrating it in their operations (Gandomi and Haider, 2015, P. 138). The study was conducted in Jordan since it has three well established Telecom Companies that command a relatively huge consumer market base.
This study report aims at addressing the effect of using BDA in enhancing innovation among Telecom Companies in Jordan. Imperatively, this research was motivated by the recent professional analyses that indicate BDA is the new concept in the market that firms need to integrate in their decision making to promote innovation thereby maintaining a competitive advantage in the current market dynamics (Gandomi et al., 2015, P.140). More so, the recent speculation about the disruptive technology in the simulation of data and assessment of market trends in meeting consumer needs was a key factor in motivating further the need to carry out this study report. The new technologies especially at the startup level of integrating BDA in Telecom Companies in Jordan was instrumental in strategizing and developing sustainable practices (Dubey,, 2016, P. 632). However, some researchers argue that BDA cannot suffice as the only tool to be used to track a company’s market command through innovative and inventive ideas. The traditional practices used in simulation of data and consequent decision making can still be used to promote the market competitiveness of a Telecom brand. The use of BDA is a new concept among many business organizations that have overseen firms purposefully work towards aligning their services in line with the current market trends over a short period of time. BDA involves sorting data that is important and tailoring it to meet the consumer preferences and tastes in both the short and long run.
It is important to note that the integration of BDA in enhancing innovation the Telecom industry is characterized by a “culture shock” in data management. The Telecom Companies are exposed to the risk of aligning their already established systems to the new concept of BDA (Yin and Kaynak, 2015, P. 142). It is on this background that this study seeks to addresses the significance of using BDA in Telecom Companies in enhancing innovation. This study, therefore, will seek to earnestly investigate the impact of using BDA in decision making processes for promoting innovation among the three main Telecom Companies in Jordan for both short and long terms respectively.
General Research Question
– What is the general role of using BDA in this research?
Specific Research Questions
– How did the use of BDA affect the final innovative decision making processes among the Jordanian Telecom companies?
– What is the role of SDA in making innovative decisions for a short run in the Telecom industry?
Firms in the Telecom industry are characterized by their decision making processes that facilitate their existence and competitiveness in the market. Their marketing strategy and appeal to customers plays a significant in ensuring they remain relevant to the dynamic market trends (Gandomi et al., 2015, P.141). Due to the changing nature of technology, Telecom companies in Jordan have to comprehensively adjust to the market forces by looking at new dimensions and definitions of innovation based on the sets of data they have within their systems.
There is need for such Telecom companies to come up with relevant tools for capturing, collecting analyzing and making innovations from big data. The inadequacy of such firms to maximize on this area of research is tantamount to losing their market command and grip. According to Yin et al. (2015, P. 143) BDA remains to be one of the top salient tools that Telecom companies can use to initiate different levels of innovation at given stages of maturation indicators for respective communication firms in Jordan.
SDA in Telecom Industry in Jordan
Prior the invention of BD concept, Telecom companies in Jordan solely relied on SDA to initiate innovative ideas to meet market competition. The implementation and subsequent execution of the SDA was vital in initiating short term goals for the firms. This presided over continuous analysis of data which out rightly was time consuming. The limitation in diversity of data quality by SDA, the need for firms to increase productivity and the requirement to reduce costs, increase revenue, detect fraudsters while fostering greater innovation has overseen the transition of the Telecom industry to embracing the BDA concept.
Competition in the Telecom industry is inevitable given that each Telecom company comes up with unique services, products and tariffs that are aimed at luring consumers to them. The need for developing a sound decision making process is anchored on the fact that the firms are able to clearly analyze and interpret data collected from the market. The decisions should be customer centered so that the Telecom firms remain relevant (Tsai et al., 2016, P.20). However, despite innovative ideas being customer centered and maintaining a competitive advantage, firms need to adjust their running costs so that they can make profits and remain sustainable.
The small markets theory: The market determinants of prices for both goods and services are based on the available information in the market. Precisely, the prices of commodities reflect the information circulating the market. The decision making process that is aimed at fostering innovation for innovation should match the current information in the market (Epstein and Zin, 2013, P. 208). The small markets theory further identifies that there is need for business firms to understand the key stakeholders in the market plus their roles to alleviate any conflict of ideas and enhancing the variability and visualization of the simulated BDA.
HO1: There is no significant impact on the role of BDA in enhancing innovation among Telecom Companies.
HO2: The use of BDA does not affect the innovative decision making process in Telecom Companies.
HO3: SDA does not play any significant role in the short term innovative decision making process.
The already published and academic and business articles illustrate that the emergence of BDA among Telecom companies and other business organizations have had a great impact in the manner by which business organizations have used the BDA concept to enhance innovation (García et al., 2016, P. 9). It is important to note that the BDA concept is an emerging trend that has gained root in the Telecom industry due to its use large volumes of data that guide in decision making and enhancing sound management practices across several business organizations. To get the most out of the BD, companies have the sole responsibility of enacting and implementing a BDA (Kitchin and Lauriault, 2015. P. 463). Maintains that the incorporation of BDA and its subsequent implementation among business firms enables the firms to be in a better position to capture huge amounts of data, integrate it through analyzing its various formats and structure and the ability of transforming such knowledge into sound decision making. BDA has become a useful resource for managing competition, measuring performance and enhancing innovation among business organizations. BDA continues to be a critical useful resource in the business that can be used to tame the levels of innovation.
It is worth noting that innovation is a very important aspect for business growth and survival of any business enterprise. In the contemporary business settings, firms rely on both external and internal knowledge to promote innovation. According to the argument proposed by Kambatla et al (2014, P. 2562) business organizations have opted to opening their research and development methods to allow for tapping and integration of external knowledge which forms the foundation for goal and skill driven innovation. The innovation developed through adoption of external knowledge should be intensive, effective and efficient.
Although BDA seem to have encroached major decision making processes in the Telecom industry and other business organizations, the role played by SDA cannot be underscored. The SDA have promoted short term decision making processes and thus ensuring the firms remain slightly above their competitors in the market based on the small markets theory (Jones and Kierzkowski, 2018, P.234). The study done by Jones et al (2018, P. 235) indicates that there is a big significant relationship for Telecom industries and business organizations to incorporate BDA in their decision making processes for a number of reasons. To begin with BDA is flexible and it does not need special talent. The use of BDA will be easy since less than four individuals can be hired to give the desired data analysis and interpretation. BDA enhances data quality due to its variability (McCusker Sand Gunaydin, 2015, P. 538). The reporting process can be easened since the data quality provided is specific to the study research area. However, BDA may lack data quality since most of the collected data is not sorted out to remain with the most relevant data for analysis.
BDA is easily integrative in Telecom industry and other business firms. The adoption of the BDA concept and its subsequent integration in firms is punctuated by the need to develop a new type of corporate culture that will be accommodative of the new innovative system. In a study by Kambatla et al (2014, P. 2566) the legal requirements for compliance in using BDA remains challenging to the Telecom companies and other business firms.
Methods Research Methodology
The qualitative research method approach was employed in the development of the research report. A qualitative research method was considered because it is easy to analyze the information the collected through behaviour in natural settings. It is easy to capture the information conveyed via qualitative research since it inculcates the beliefs, feelings and values that cannot be captured in quantitative research (McCusker et al., 2015, P. 539). Importantly, qualitative research was used since it promotes the provision of insights that help in solving the problem statement through formulation of hypotheses. Due the employment of both structured and unstructured techniques by qualitative research, researchers are able to deeply understand the research problem. The qualitative method is anchored on interpretive methodology principles.
The study sample for the research is limited to Telecom companies in Jordan. The strategy that was adopted and used to facilitate the success of the sampling method was to the use of a simple multiple case study methodology since it presented the best avenue upon which the research was to identify the common patterns of multiple innovation from the three main Telecom companies in Jordan (Palinkas et al., 2015,P. 534). This case study sampling method was relevant to this research since there were very few studies that were conducted in this area. The sample size was three Telecom companies in Jordan namely Zain, Orange Jordan and Umniah respectively. The inclusion criteria and or the rationale used for this research report was Telecom companies operating in Jordan that use BDA in decision making. Furthermore, the companies have to be registered with the ministry of communication and information technology in Jordan.
Data Collection Instruments
The research report used in-depth interviews as a tool for data collection. The interviews were conducted on the senior management team of the Telecom companies. Additionally, business executives were identified as the ideal subjects for data collection (Lewis, 2015, P. 473). Business executives were ideal since they were conversant with factors that constituted innovation within their respective firms and they were also better placed to explain the capabilities of their firms in using and interpreting BDA (García et al., 2016, P.9) To facilitate data quality, the interviews will be face to face and semi structured which forms the basic component of qualitative research.
The analysis of data collected will constitute reading the interview transcripts line by line a number of times to facilitate easy coding hence analyzing the responses of the interviewees. Microsoft word was used to organize and manage the collected data from the interview transcripts. NVivo, a computer software package concepts were employed to sort and analyze the data using word software.
The topic the role of BDA is significant in the contemporary Telecom industry in Jordan. According to Dubey et al. (2016, P. 637) as earlier mentioned there is need for firms and other business organizations to integrate and consolidate the use of BDA in enhancing innovation. The need to understand the role of SDA in the decision making processes of the firms and other business organizations is vital since it promotes faster decision making in the short run. By carrying out this research on the importance of including SDA in decision making to enhance innovation among business organizations, the findings and the results will be significant in helping the Telecom companies and other firms in ensuring that promote innovative decision making based on quality data and gain a competitive market advantage.
This study is also significant because there is a huge literature gap on the topic. Firstly, the study is limited to three Telecom companies and the results derived from the study may not be true to other business organization in the different economic sectors in Jordan. A small sample size has high tendency for variability hence increased chances of bias in the study (Rai et al., 2013). The researcher further worked with the most influential individuals from leading Telecom companies. This reduces the scope of the study to a few individuals thus increasing chances for bias in data analysis. Since there are only three Telecom companies in Jordan, this research cannot be stretched to apply in other market structures that have less or more than three Telecom companies in operation.
Limitations and Delimitations
The main limitation of this research report lies in the qualitative research used as a method data collection. The research focused on fewer people and companies. For instance, the research focused on three Telecom companies and the people who were interviewed was limited to business executives of the Telecom companies who understood the dynamics of BDA in enhancing innovation within their respective organizations. Orcher (2016) maintains that researchers need to ensure data collection uses primary techniques such as questionnaires to maintain objectivity of the research.
Qualitative research is time consuming and the intended respondents may give half-baked answers if they have to attend to other managerial duties in the course of the interviews. Some managers and business executives might also decide conceal some relevant information that they use for maintaining a competitive advantage in the market dynamics. Lastly, the study is likely to suffer bias. Since the researcher has an already established objective to be achieved, there is likelihood that the researcher developed objectiveness in sorting the data for analysis (Berger, 2015, P.220). The interviews are prone to bias since the researcher might decide not to follow the inclusion-exclusion criteria in the processes and this may dent the desired outcome of the research. Any bias in data collection will facilitate very weak and incomprehensive conclusions for the specific study research.
The intention of the research is to investigate the role of using BDA in decision making processes for innovation. As earlier stated, the research was limited to Telecom companies in Jordan. The data collected was not cross cultural based.
The researcher will start by seeking the approval of the university’s internal research board for approval of the topic and the objectives. Before conducting the qualitative research, the researcher will look for relevant academic peer reviewed articles and journals to get a general overview of the study research topic (Chonko and Hunt, 2018, P. 87). The reviewing of these academic sources will be vital enhancing the ability of the researcher to critique and analyze the study objectives and the limitations presented in the respective articles. Having prior knowledge of previous studies helps the researchers to refine their study objects and define a strong problem statement.
The researcher will formulate a confidential form that will encompass the ethical guidelines and principles that will guard the interview sessions and the use of collected data for the intended purpose. The researcher will not be allowed to leak collected data or information to the firm’s competitors (Chonko et al., 2018, P. 89). After conducting the research, the results will be used to promote innovation by integrating BDA in Telecom Companies and other business organizations. The policymakers and shareholders will be in a better position to understand the value of BDA in ensuring innovation for both short and long term success of business organization. With permission from the university, the researcher will publish the research report for future reference.Free research paper samples and term paper examples available online are plagiarized. They cannot be used as your own paper, even a part of it. You can order a high-quality custom research paper on your topic from expert writers:
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Berger, Roni. “Now I see it, now I don’t: Researcher’s position and reflexivity in qualitative research.” Qualitative research 15, no. 2 (2015): 219-234.
Butler-Kisber, L., 2017. Statement of Purpose. LEARNing Landscapes, 11(1), pp.5-5.
Dubey, R., Gunasekaran, A., Childe, S.J., Wamba, S.F. and Papadopoulos, T., 2016. The impact of big data on world-class sustainable manufacturing. The International Journal of Advanced Manufacturing Technology, 84(1-4), pp.631-645.
Epstein, L.G. and Zin, S.E., 2013. Substitution, risk aversion and the temporal behavior of consumption and asset returns: A theoretical framework. In handbook of the fundamentals of financial decision making: Part I (pp. 207-239).
Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), pp.137-144.
García, S., Ramírez-Gallego, S., Luengo, J., Benítez, J.M. and Herrera, F., 2016. Big data preprocessing: methods and prospects. Big Data Analytics, 1(1), p.9.
Jones, R.W. and Kierzkowski, H., 2018. The role of services in production and international trade: A theoretical framework. World Scientific Book Chapters, pp.233-253.
Kambatla, K., Kollias, G., Kumar, V. and Grama, A., 2014. Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), pp.2561-2573.
Kitchin, R. and Lauriault, T.P., 2015. Small data in the era of big data. GeoJournal, 80(4), pp.463-475.
Lewis, S., 2015. Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), pp.473-475.
McCusker, K. and Gunaydin, S., 2015. Research using qualitative, quantitative or mixed methods and choice based on the research. Perfusion, 30(7), pp.537-542.
Orcher, L.T., 2016. Conducting a survey: Techniques for a term project. Routledge.
Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood, K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), pp.533-544.
Rai, A., Goodhue, D.L., Henseler, J. and Thompson, R.L., 2013. To PLS or not to PLS: That is the question.
Tsai, C.W., Lai, C.F., Chao, H.C. and Vasilakos, A.V., 2016. Big data analytics. In Big data technologies and applications (pp. 13-52). Springer, Cham.
Yin, S. and Kaynak, O., 2015. Big data for modern industry: challenges and trends [point of view]. Proceedings of the IEEE, 103(2), pp.143-146.