The evolution of technology has provided significant changes during the 21st century, especially in regards to digital technologies. Companies have found a way to combine digital technologies and innovative ways of doing things, it comes as no surprise that different companies have capitalized on these opportunities and have experienced rapid growth. The changes have provided an increase in social interactions. Significantly, digital technology innovations have created “improvements in the quantity and quality of the information transformed into strings of zeros and ones are allowing rapid advances to be made in many other domains of science and engineering” . A new method of communication are dependent upon societal changes, which can occur through social media sites.
The business changes have occurred through cloud computing. The changes can be more impactful in specific sectors like services, which can include the automotive industry. In fact, as automobiles become more advanced and computerized, those engaged in the industry must shift to using technology to make connections with others . In fact, there has been an increase in innovation during recent time periods, which have led to “shorter product life cycles, ever-changing customer needs, and growing internationalization of businesses, have made customer service performance critical for firm survival. [Significantly,] there is substantial evidence that 40 percent of customers who experience poor customer service stop doing business with the target company” . The resultant changes to maintain and or improve customer service has occurred in the ability of these companies to retain their market.
Big Data has also shown that it can generate value. This is done through at least four stages: “(1) Data is collected where it originates. During the data generation stage, a stream of data is created from a variety of sources: sensors, human input, etc. (2) The raw data is combined with data from other sources, classified and stored in some kind of data repository. (3) Algorithms and analytics are applied by an intelligence engine to interpret and provide utility to the aggregated data. (4) The outputs of the intelligence engine are converted to tangible values, insights or recommendations” .
Terms of References
Big Data – is a very large set of data which can be analyzed computationally to show trends, patterns, and associations which provides understanding of human interactions and behavior.
Technology acceptance model (TAM) – is an information system theory that provides a model for how users accept and use technology. TAM provides a model suggestion for users who are presented with new technology to use a number of other factors which can influence their decision and how and when they use it.
Perceived usefulness (PU) – Fred Davis defined perceived usefulness as the degree in which a person believes that a specific system would provide an enhancement to their job performance.
Perceived ease of use (PEOU) – is the degree that a person believes that using a specific system would require minimal to no effort.
Cloud computing solution – is a generic term for the delivery of hosted services available via the internet.
Server architecture- is a network architecture that each process or computer on the network is either a sever or a client. Servers are powerful computers or dedicated processes to managing file servers, print servers, or network servers.
Algorithms – is a set of rules or process which needs to be followed in problem-solving operations or calculations, especially when using a computer for calculations.
Aggregated data – is a statistical analysis of data which is compiled from several measurements. The data is aggregated which provides groups of observations and replaces with a summary statistics based upon the observation.
Specific Investigation
The specific investigation of this paper will focus on the following research objectives:
Explore theoretical consumer behavior discourse concerning the subject matter, including the technology acceptance model (TAM).
Examine expert-reviewed literature within the last five years in order to determine how Big Data principles have shaped the ability of automotive companies to reach their customer conversion goals.
Explore data regarding how Big Data principles have been applied, the resulting outcomes regarding business performance, and how these companies may leverage them to enhance their user outcomes.
Address potential risks and threats to security and system integrity.
Illuminate how data analytic approaches will improve communication and help business management quickly comprehend the circumstances related to enhanced profitability.
Brief Background
Big Data has been in the works for decades, from the first observation of data to information explosion. “What do people think about ‘Big Data’? In general, he noted that not all comments were positive. Many people don’t like the term and he pointed out that analytics is not a new concept. In fact, Big Data has been used for a while, with companies such as UPS and others doing a lot of these things for some time. There is definitely something going on and we have been heading in a new direction for a while, but it is relatively unstructured at the moment. Many new kinds of data are being analyzed and new ways of addressing are coming to the forefront; this is a new development afoot, called Analytics 3.0” (Handfield, 2013). With the existence of new data, and methods for compiling it, businesses can make better business decisions. The consumer’s behavior and habits can be used to reach the customers and their demands. There are many different methods that Big Data can be used to aid in the automobile industry and meeting the demands of the industry. Ultimately, Big Data is instrumental to creating value for the company, which, in turn, enhances economic growth, suggesting that companies would do well to improve performance and cut costs through making decisions optimized by Big Data applications. As such, companies, including those within the automotive industry, can effectively use Big Data to use technology and capital (monetary, physical resources, and human) most efficiently. This is due to improved decisions made by decision makers.
Research Questions
The questions to be answered in this paper include the following:
How big data analytics influence the decision making process to enhance business performance?
What big data analytics will be used by automotive dealership service and sales?
Is their viable concerns regarding inaccuracies or securities which need to be taken into consideration?
Outline of Content Chapters
Introduction
Terms of Reference – will provide definition for terms used within paper that are not commonly known.
Specific Investigation
Brief Background
Research Question – detailed the main questions that the paper will focus on answering.
Literature Review
Principles of Big Data – will discuss the different principles of Big Data. The goal of this section is select principles which will assist decision makers in making the best decisions for their organization.
Communication Improvements – will discuss how Big Data can be utilized to improve communication on levels.
Leverage and Profitability Improvements – Big Data is instrumental in assisting companies in meeting customer needs . Furthermore, Big Data analytics are important because they “may enhance the ability of an organization to sense and respond to a changing business environment” .
Potential Risk Threats to Security and System Integrity – it is important to consider the potential risk threats to security and system integrity. Big Data affects privacy and a greater risk of data misrepresentation from users.
Methodology
Research Topic – will detail the 21st century changes within society. This section will detail digital technologies and different work approaches have transformed the way enterprises operate and how people interact in society. These applications include social media sites, smart phone technology, video streaming, and cloud computing, and have impacted society and business rapidly.
Problem Statement and Justification – the proposal is that Big Data provides a competitive advantage and provides a new and accurate way to do business. “Data are now woven into every sector and function in the global economy, and, like other essential factors of production such as hard assets and human capital, much of modern economic activity simply could not take place without them” .
Research Objectives – the research objectives fill focus on the following:
Explore theoretical consumer behavior discourse concerning the subject matter, including the technology acceptance model (TAM).
Examine expert-reviewed literature within the last five years in order to determine how Big Data principles have shaped the ability of automotive companies to reach their customer conversion goals.
Explore data regarding how Big Data principles have been applied, the resulting outcomes regarding business performance, and how these companies may leverage them to enhance their user outcomes.
Address potential risks and threats to security and system integrity.
Illuminate how data analytic approaches will improve communication and help business management quickly comprehend the circumstances related to enhanced profitability.
Variables and Justification – the study will include TAM which will be considered a variable for the study. TAM is a useful variable because it asserts that the attitude of users towards adopting technology is highly dependent on their perception towards the usefulness and simplicity of technology.
Research Design
Results – the study considers how Big Data analytics influence the decision making process to enhance business performance. Additionally, the research study objectives are to: explore theoretical consumer behavior discourse concerning the subject matter, including the technology acceptance model (TAM); examine expert-reviewed literature within the last five years in order to determine how Big Data principles have shaped the ability of automotive companies to reach their customer conversion goals; explore data regarding how Big Data principles have been applied, the resulting outcomes regarding business performance, and how these companies may leverage them to enhance their user outcomes; address potential risks and threats to security and system integrity; and illuminate how data analytic approaches will improve communication and help business management quickly comprehend the circumstances related to enhanced profitability.
Discussion – the expansion of new technologies available and how they aid in big business decisions.
Leverage Opportunities and Increased Profitability – this section will discuss how Big Data can be used to find out customer’s needs and trends while focusing on increasing profitability.
Potential Risks – will address concerns when considering that “the dominant conceptions of privacy as secrecy and as control are increasingly untenable [and] the future of privacy will have to be built upon a foundation of trust—between individuals and the technologies that will be watching and listening” .
Conclusion
