This study focuses on 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.

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Decision Making Process
It is well-known that decision making is important for the success of businesses. However, Big Data has influenced decision making by the implementation of data metrics (measurements of selected data important to the company/industry) which have allowed for improved processes, basing decisions on data, rather than using intuition alone . Big Data has been impactful as an approach geared towards prompting more insightful decision making, suggesting that leadership capabilities within organizations can be increased through the use of Big Data analytics.

Initial successes using Big Data are evident with certain companies, such as Ford, which allows decisions makers to make tactical decisions that have been beneficial to the company overall, including those that determine “which brands and models to discontinue, where to procure parts and materials, and how to enable dealers to tweak their inventories to improve sales” .

Technology Acceptance Model
It has been found that the technology acceptance model (TAM) focuses on how the attitude of users towards technology adoption depends on personal perceptions regarding the usefulness and simplicity of technology, suggesting that intentions are based on behavior, which will, in turn, determine adoption and use . Based on these concepts, it is assumed that digital applications will be used in increasing rates if the application is deemed as being useful and easy to use, considered through computer self-efficacy (CSE), which refers to the “perception of one’s ability to use a computer” .

Research establishes that digital technology solutions are instrumental in providing more efficient educational opportunities, as well as business strategies, particularly servicing and establishing stronger communication exchanges between both internal employees and customers. Big Data analytics will need to be user friendly in order to be most influential. That is, employees and consumers alike will need to be able to use the analysis results in ways that meet their needs best. For instance, consumers will need to use the results to determine what product to purchase next. In contrast, employees will need to use the results to determine what product to sell next based on purchasing activities. Furthermore, the data collected today through Big Data analytics can be used in the future to determine the future needs of consumers.

Big Data Principles
The principles of Big Data are established to create an atmosphere that allows decision makers to make the most effective decisions for their organizations. Big Data refers, not to an initiative, but an umbrella term that encompasses “many problem spaces, data sets, technologies, and opportunities for enhancing business value” . As a result, it is possible to see how Big Data can help companies determine where improvements are needed and can be made. These capabilities allow organizations to improve their existing business processes, efficiently streamlining operations, which will, in turn, increase productivity and profitability, particularly through lower costs .

It is also important that organizations are aware that the acquisition of data does not prove reliability. In fact, reliability is shown through patterns within the data . With this reliability, value is generated through four stages: (1) data generation from different sources of origin; (2) generated data is combined with existing data from other sources, leading to classification and storage; (3) intelligence engines are used to interpret data, providing utility for the organization; and (4) analyses provide “tangible values, insights or recommendations” . Much database technology has come from social media websites, such as “Google, Facebook, LinkedIn and Twitter” .

It is paramount that automotive companies be prepared for rapid implementation of needed changes to improve the business preparations. Therefore, it will be increasingly important for these companies to be up-to-date on current innovations, especially those involving technology, which will, in term, allow organizations to obtain new products that will meet customer expectations (creating value for the organization and meeting stakeholder expectations). These types of preparations will allow organizations to defend themselves against technological invasions, allowing the company to be defined by the rate that it accepts challenges .

Leverage Opportunities and Increased Profitability
Through making data-driven decisions, decision makers have become effective in creating strategic goals for the organization that are highly effective towards meeting stakeholder expectations. As a result, Big Data applications have become instrumental for many industries, including the automotive industry, in retaining customers and even increasing their customer bases. It has been established through research that Big Data applications have and will continue to impact strategic management decisions. Due to technological advancements, the automotive industry is becoming more advanced, requiring the use of data applications aimed at meeting the needs and expectations of both customers and stakeholders. Big Data is noted to help provide competitive advantages to companies. As a result, Big Data has been seen to create competitive advantage for these companies. However, there is a very real possibility that this competitive advantage will not remain sustainable.

Big Data helps meet customer needs . This stresses the importance of Big Data analytics in order to allow organizations to “sense and respond to a changing business environment” . Big Data analytics is proposed to assist in organizations being able to increase leverage and profitability through improved customer service .

Potential Risks
Privacy concerns can potentially decrease leverage and profitability. Privacy concerns are emphasized by the intellectual property law, which “encourage[s] technological disclosure in order to speed innovation” . Big Data has security risks and can be argued in two different ways: the potential to change the world in positive ways or has the potential to result in “the biggest civil rights threat of our generation” . However, Big Data also has the potential to influence security and system integrity, creating challenges in relation to public policy . These threats could increase the possibility of cyber-attacks, causing many organizations to develop more stringent protections to trade secrets. Therefore, the consideration of ethics allows organizations to utilize Big Data with integrity. However, critics of Big Data view it as “enabling invasions of privacy, decreased civil freedoms, widening of inequality and increased state and corporate control” . This shows that Big Data can be used in harmful ways as well, if one so desired. As a result, ethical integrity is important when utilizing Big Data.

Communication Improvements
It has been discovered through research studies that “40 percent of customers who experience poor customer service stop doing business with the target company” . Big Data has been instrumental in assisting organizations to create changes within their customer service departments, allowing them to retain their market and customer loyalty.

However, the use of data also requires the use of intuition because intuition allows the needs and expectations to be met most effectively by determining the appropriate data treatment for the raw data . This provides organizations the opportunity to resolve issues before they develop, which further allows them to meet the needs and expectations of interested parties, such as consumers and stakeholders. These technological changes have resulted to changes in the service delivery process, especially as these processes include interactions with technology-based systems and/or/with face-to-face interactions .

Conclusion
Big Data has been instrumental in meeting the expectations of the industry through increasing the decision making process. Furthermore, these analyses have been instrumental in improving communication capabilities between organizations and the market, which influences future customer loyalty. Finally, Big Data has allowed for enhanced future security considerations, including cyber-attacks.

    References
  • Adolph, M., 2014. Big Data, its Enablers and Standards. PIK – Praxis der Informationsverarbeitung und Kommunikation, 37(3), pp.197 – 204.
  • Christiansen, L., 2011. Personal privacy and internet marketing: an impossible conflict or a marriage made in heaven? Business Horizons, pp.509 – 514.
  • Curran, J.M., Meuter, M.L. & Surprenant, C.F., 2003. Intentions to use selfservice technologies: a confluence of multiple attitude. Journal of Service Research, 5(3), pp.209–224.