- Internal Code :
- Subject Code : HI6008
- University : Holmes Institute
- Subject Name : Business Research
Business Research
Introduction to Business Research
Big data is increasingly used in business organisations for prioritising and comprehending the needs of the customers. In modern technology, big data plays a critical role in understanding and anticipating the needs and desires of the customers. Big data can be defined as a wide array of information resource which produces economical and advanced information processing which is incorporated to make effectual decisions and also in terms of mechanization of the firm (Oussous et al. 2018). This topic is a major concern because it is cardinal that the data is analysed in a proper custom and precisely by the organisations to acknowledge the behaviour and gain insight into the customers' requirements. A properly analysed set of data is useful for organisations for framing their business strategies, product development and marketing campaigns. There is an urgent need to determine the role of big data in attaining competitive advantage. The research project intends to determine the way by which businesses can accomplish comparative advantage by utilising big data analytics. To address and study the research objective in an efficacious custom, it is further broken down into four research questions which are as follows:
- What are the benefits of big data analytics technology in business?
- Which factors are responsible for implementing the big data in business?
- What is the impact of big data on the competitive advantage of business?
- How firms can employ big data technology into their business?
Research Methodology of Business Research
The research methodology is a speculative analysis of the methods that are logically followed to investigate a particular domain of knowledge. It is a systematic procedure that aids in gaining an enhanced understanding of the information concerned with a topic. It is a set of specific procedures that are used to analyse, select and process the information regarding a particular subject. The foremost purpose of a research methodology is to validate and increase the credibility of the study (Dougherty et al. 2019). This section of the study is majorly aimed at justifying the process of the collection so the data and its analysis. Qualitative and quantitative methodological choices are made based on the type of research. Qualitative researches are usually richer and are relied upon the idiosyncratic standpoint. It supports a particular situation in an efficacious manner. It usually involves a small number of participants due to the time constraints as it is usually a time-consuming process. In the considered research project, the qualitative research method is employed. The research encompasses the use of both primary as well as secondary qualitative data.
Research Philosophy
Research philosophy rehearses around the foundation, expansion and the nature of the knowledge. It is simply a belief associated with the way in which data is assimilated and analysed to draw the relevant findings (Dougherty et al. 2019). It is known to provide direction to research. It is also called as the major driving element of research. In the considered research, interpretivism research philosophy is incorporated. This philosophy incorporates the interpretation of the elements of the study. This research philosophy is suitable for the deliberated study because the research study aims to gradually underpin the subject by making use of communal constructions. Unlike the positivism research philosophy, this philosophy makes use of the qualitative data which is more suitable for the pondered study. This philosophy is more suitable as compared to the positivism research philosophy in terms of comprehending diverse attitudes (Dougherty et al. 2019). This research philosophy appreciably studies the difference in opinions of different individuals and constructively incorporates the suitable methods to reflect on the varied facets.
Research Approach
Research approach encircles all the broad assumptions that further validate the study. It is completely dependent upon the nature of the research and varies as per the problems being addressed in the researches (Tuffour 2017). Research approach further elaborates the process of data collection, analysis and interpretation. The inductive approach is incorporated in this research project because it relies upon the observation of the results. It encompasses thorough observation of the environment and thus, derives generalizations and ideas. This approach helps constrict the raw data into the format of a brief summary. It also aids in the process of establishing a bridge between the assessment of the research and findings' summary. It is employed in the deliberated study because of the reason that it makes use of the systematic set of tactics for the analysis of the qualitative data. In reference to the evaluation process, this research approach aids in obtaining the findings (Tuffour 2017).
Research Design
Research design is an array of events helpful in carrying out the compilation and investigation of data variables concerned with a research study (Creswell and Poth 2016). It is also denoted as a framework that is used for finding the answers for a set of pre-defined research objectives. The major objective of the research design is to safeguard that the relevant evidence is assembled to fulfil the research objective. Exploratory research design is used in this research project because it investigates the problem and provides a better understanding of the same. This research design analyses the subject in such a manner that future research can be conducted further. This research design is also referred to as the ground theory design as it is employed when an issue is at an introductory stage. The benefit associated with using this research design is that it involves low associated costs (Creswell and Poth 2016). It is more interactive in nature as compared to the descriptive research design. Another pro associated with this research design is that it is malleable in nature and can be amended as per the changes in the progression of the research. This research design aids the researcher to understand at an early stage if the research is worth investing or not (Creswell and Poth 2016).
Data Collection
Data collection process assists in answering the research question of the research and in evaluating the outcomes of the study (Cyr 2016). In order to maintain the integrity of the study, it is cardinal that the appropriate data collection method is used. There are two diverse sorts of data collection methods that involve primary data collection method and the secondary data collection method. Primary data collection method aids in gaining first-hand data. Primary data incorporates assembling fresh data that increases the reliability of the research. In comparison to the secondary data, it is more customized and can be altered as per the requirements of the researcher and the research (Cyr 2016). This method of collection of data is more time-consuming. In comparison to the secondary method, it is also not cost-effective. The secondary method of data collection involves the collection of data from the secondary sources involving articles, journals, company websites and annual reports. In the pondered study primary method of data collection is used. Qualitative data is collected in this method and the primary method is used because it elevates the credibility of the research and also contributes to the trustworthiness of the overall findings (Cyr 2016). In the research project, qualitative data is collected via both primary and secondary sources.
Primary qualitative data is collected utilizing an interview. The interview involves 10 participants. The major points of the interview were noted by the accompanying research companion. The interviews were recorded as well for analyzing them in future. A questionnaire is prepared to ask the respondents. The questionnaire involves 10 questions. Out of which seven questions are structured and three are unstructured. The secondary data is collected through the journals and articles. It is sorted by using keywords like ‘big data’, ‘benefits of big data in businesses’, ‘data in customer needs’, ‘competitive edge’ and ‘big data technology in businesses’. For maintaining the credibility of the research project, it is ensured that the data collected is not older than 2015. All the articles considered are peer-reviewed.
Research Instrument
A research instrument is a measurement tool that assists in the process of data collection. It eases the process of collection of data on a particular topic of interest (Stupnisky et al. 2019). The research instrument employed in the deliberated study is a structured interview. The interview is a standardized procedure that follows a logical structure and aims to identify the deeply rooted aspects of the significance of big data in organizations. A questionnaire is used as the research tool.
Sampling Technique
The selected research philosophy and the research approach determine the sampling technique of the study. The foremost goal of the sampling technique is to make sure that the data is collected and analysed in the most feasible manner (Etika et al. 2016). This results in efficaciously meeting the research objectives. In the considered research project, the convenience sampling technique is used to select the sample size and conduct the interviews. By employing the convenience sampling technique, it is made sure that the data research analysts from different organizations are considered. This sampling technique is employed because of the fact that is a cost-effective procedure and also consumes less time which makes it easier to obtain the results. It allows drawing the information within the comfort zone. In comparison with the other sampling methods, it is economical in nature (Etika et al. 2016).
Data Analysis Technique
Data analysis is the procedural step of the research study that involves cleaning, transforming and modifying the data into useful information. It incorporates inspection of the data while transmuting it into convenient evidence. In this research project, the data analysis technique employed is the thematic data analysis (White et al. 2017). Qualitative analysis is used as it endeavours to unknot the motivation and behaviour of the participants which aids in addressing the research questions’ answers. The research study uses qualitative analysis because this type of analysis is suitable for the study as the study incorporates qualitative data. Qualitative analysis is used for studying the interviews conducted with the participants. For conducting the analysis, there are different types of tools that can be used. In this study, thematic analysis is used as a tool.
This tool is used because it aids in interpreting the patterns of the collected data and also analyses the data by formulating different themes. Four key themes are formed for categorizing and analyzing data. The four themes involved are benefits of big data analytics technology in business, factors responsible for implementing the big data in business, the impact of big data on the competitive advantage of the business and ways of employing big data technology in businesses. The data obtained via the interview is categorized under these themes relying on the transcripts obtained.
Findings of Business Research
Big data has become an integral part of the firms and is increasingly employed to gain enhanced insight into the perceptions of the customers. Data analysis incorporating both primary and secondary data revealed that the key benefits of big data in businesses are rooted in enhanced visibility of the customer requirements and needs. On being asked about the benefits of big data analytics technology in business, most of the data analysts believe that big data analytics is useful in organisations as it cuts off the costs; it reduces the company maintenance charges for contractors in comparison with the other vendors. It is also useful in eliminating invoice processing errors and other automated service schedules. After reviewing the literature, it is evident that big data is useful in enhancing the market value; it ensures the effectiveness of the operations and hence, increases the framework of satisfied customers.
Organisations are increasingly using information technologies for assessing big data and hence implementing and improving decision-making skills. The literature brings forward the transparent picture of how Google and Amazon have used the technique of big data for monitoring the performance in the market and hence improving the overall performance of the business (Khine and Shun 2017).
Most of data analysts agree on the fact that big data improves the pricing and acts as a business intelligence tool for evaluating the finances and providing a clearer picture about the position of the business in the market. They also agreed that it allows businesses to focus on the local environment by catering to the needs of the loyal customers and is helpful in zooming into the likes and dislikes of the clients on the basis of their preferences. The literature lays emphasis on the fact that infrastructure of information technology; cost expectations, financial conditions and sources of data collection are some of the key factors that impact the implementation of big data (Liu et al. 2016). It is in compliance with the primary data obtained from the interview data analysts. They also agree that information technology maintenance of applications and cost of the software and hardware related to big data are integral factors impacting the implementation of big data in organisations.
According to authors Kubina, Kubinova and Varmus (2015), big data is applicable in diverse fields involving e-learning, public sectors, and internet of things, e-health, government organisations and many more. It makes information more accessible and transparent hence assists in the process of collecting information about the competitors in the market and hence contributing to the improvement of the quality of the products. The data analysts also agree with the fact that companies become more aware of the clients' requirements and are able to effectively target the audience with the assistance of big data and are also a better segmentation tactic. Employing big data into businesses can be a challenging process as it requires the development of BDT; it requires updated data handling methods for controlling the volume (Oussous et al. 2018). It can be inferred from the analysis of primary data that modern machine learning is useful in extracting data.
Conclusion on Business Research
The findings of the research lay prominence on the efficaciousness of big data in today’s businesses in terms of effectively identifying the potential customers, targeting the potential segment and staying ahead of the competitors. It is beneficial in making sure that competitiveness is maintained in the market. The assessment has revealed that big data poses a substantial influence on the performance of a business in the market. The assessment is relied on identifying the significance of big data analytics technology in organizations. The assessment determines the factors accountable for big data that incorporate skilled employees, cost, expectations and financial condition of the firm. The impact of data is elaborated in the assessment which is a key research question of the research project. It contributes to high performance and providing accurate and most relevant information to the firms. It also discusses the ways of implementing big data which incorporate the development of BDT and adopting DBT through significant data machine learning.
References for Business Research
Creswell, J.W. and Poth, C.N. 2016. Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks: Sage publications.
Cyr, J. 2016. The pitfalls and promise of focus groups as a data collection method. Sociological methods & research, 45,2 pp.231-259.
Dougherty, M.R., Silva, L.R. and Grand, J.A. 2019. Making research evaluation more transparent: Aligning research philosophy, institutional values, and reporting. Perspectives on Psychological Science, 14,3 pp.361-375.
Etikan, I., Musa, S.A. and Alkassim, R.S. 2016. Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5,1 pp.1-4.
Khine, P. V. and Shun, Z. W. 2017. Big data for organizations: A review. Journals of Computer and Communication, 5(3).
Kubina, M., Varmus, M. and Kubinova, I. 2015. Use of big data for the competitive advantage of the company. Procedia Economics and Finance, 26 pp. 561-565.
Liu, O., Chong, W. K. and Chan, O. C. 2016. The application of big data analytics in the business world. IMCES, 2 pp. 16-18.
Oussous, A., Benjelloun, Z. F., Lahcen, A. A. and Belfkih, S. 2018. Big data technologies: A survey. Journal of King Saud University - Computer and Information Sciences, 30,4 pp. 441-448.
Stupnisky, R.H., Hall, N.C. and Pekrun, R. 2019. Faculty enjoyment, anxiety, and boredom for teaching and research: instrument development and testing predictors of success. Studies in Higher Education, 44,10 pp.1712-1722.
Tuffour, I. 2017. A critical overview of interpretative phenomenological analysis: a contemporary qualitative research approach. Journal of Healthcare Communications, 2,4 p.52.
White, A., Moore, D.W., Fleer, M. and Anderson, A. 2017. A thematic and content analysis of instructional and rehearsal procedures of preschool social emotional learning programs. Australasian Journal of Early Childhood, 42,3 pp.82-91.
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