Big data analytics sentiment: US-China reaction to data collection by business and government
Introduction
The collection and management of “big data” has become a charged topic not only within the information technology (IT) field, but more broadly in society, including the corporate and government arenas (Chen et al., 2012, Wang et al., 2016). First perceived as just another technology used for forecasting, to better target customers and to increase corporate growth, its use, and misuse, has propagated into other societal realms. Big data can provide benefits such as more focused advertising and marketing of products and services – leading to higher prosperity and more adoptable and sustainable products and services. However, there is also the concern of privacy and intrusion into one's personal life (van de Pas and van Bussel, 2015). There is tension between a corporation's desire for economic growth and the consumers' desire for privacy. Do personalized advertisements increase sales by focusing on an individual's specific needs and wants or do they create frustration by demonstrating to an individual that some entity knows a lot more about them then they would like others to know? Continuously convincing an individual of new products they “need” (assuming the analytics produce an accurate calculation of the “need”) is a great business model for creating profit for the corporation, but may have the opposite effect on societal and environmental progress toward lack of privacy and sustainability. While technology can contributes toward environmentally unfriendly practices (i.e. planned obsolescence of computing and mobile devices), it can be used toward environmentally sustainable practices such as reducing waste. For example, enabling mailings to go to individuals who more likely have an interest or need for a particular service or product—rather than to everyone, thus saving on mail delivery, ink toner and paper product usage.
While there is no grand theory for “big data” at this time there is no doubt that this phenomenon is taking the research world by storm. Abbasi et al. (2016) provide a research framework that spans disciplines and research methodologies arguing the impact big data will have on research. At its heart big data differs from traditional data when you consider the big V's of Big Data (Buhl et al., 2013, McAfee and Brynjolfsson, 2012), namely volume, variety, velocity, and veracity. Volume in terms of gigabytes to petabytes (and beyond) of data to analyze requiring new hardware and software solutions to handle this size. Variety considers that all data is not just text and numbers but rather more complex objects such as documents, images, sound, and video that could be analyzed for additional insights. Velocity reflects the incoming pace of new data. Consider a smart city solution that tracks people and automobile traffic through its intersections. Finally, veracity, one of the major underlying themes of this research, deals with the privacy, confidentiality, integrity, trustworthiness, and availability of big data. Chen et al. (2012) and Wang et al. (2016) discuss how the advances in business intelligence, analytics, and big data technologies are reaching into the political and governmental arenas ranging from healthcare to transportation and national infrastructure. It is in this spirit, with an eye toward business and governmental usage of big data that we conducted this research, to gauge the concerns of respondents from the two largest economies in the world.
As corporations and governments use technology to better identify and track their customers and citizens, it is important to determine appropriate, acceptable, and sustainable limits. Otherwise customers and citizens may complain and rebel—even leading to the organization's demise and downfall. This paper examines perceptions of the use of new technologies to collect and analyze big data by respondents from China and the United States. We analyze how these new big data and data analytics technologies impact consumer behavior in adopting new products and services, often with serious concerns of privacy—within two quite different countries and cultures. Chinese and US respondents report on their attitudes toward the collection and use of personal data, big data, data mining, and data warehousing usage by business and government. Finally, this work provides insights for corporate business and government entities suggesting how they might adjust their approach to big data collection and management in order to better support and sustain their organization's services and products.
Section snippets
Background
Examining some general country metrics show that the United States of America (US) and the People's Republic of China (China) share many similarities. Both countries cover approximately the same total area and land area; the US has a total area of 9,629,090 km2 and covers a land area of 9,158,960 km2; China has a total area of 9,596,961 km2 and covers a land area of 9,327,420 (United Nations, 2006). The US and China are the two largest economies by gross domestic product (GDP) by an order of
Research framework
This big data analytics sentiment research gathers data on perceptions of individuals toward big data collection and analysis – especially as they relate to data collected by corporate business and government. In order to decipher the differences and similarities between the US and China in how their citizens view big data collection, analytics and technology usage, and how they may perceive them in the future, a theoretical framework can be useful in framing our data analysis. There have
Method/model
In this survey research we seek insights on individual sentiment toward big data usage by business and government. Propositional statements are provided for respondents to reflect on and judge. In this study we extend the survey instrument utilized in LaBrie et al. (2014). Foundations for our current study can be found in Cazier and LaBrie (2007) where seven myth – counter-myth pairs (what we refer to in this research as propositions) on data mining/warehousing usage were proposed and
Results and discussion
A total of 398 people were surveyed, consisting of 221 that attended two universities in the US and 177 who attended a university in Beijing, China. One US university is a private university on the West Coast while the other US university is a public university on the East Coast. In both China and the US both undergraduate and graduate students were surveyed. The first test performed on the data was to make sure we could reject the null hypothesis that survey respondents had an opinion
Conclusion and future research
Technological change continues to happen – Moore's law assures us of that. More and more of an organization's (business or governmental) value is being placed on how it manages and sustains its use of big data. This research provides key insights on how respondents from the two largest economies of the world, namely China and the US, think about how individuals, businesses, and governments employ big data collection and analytics. Three of our findings suggest that:
- 1)
Chinese respondents tend to
Ryan C. LaBrie, Ph.D. is an Associate Professor of Management and Information Systems in the School of Business, Government, & Economics at Seattle Pacific University. Dr. LaBrie received his Ph.D. from Arizona State University. Prior to entering academia Ryan spent ten years with the Microsoft Corporation in a number of different capacities ending his time as a Program Manager in the Enterprise Knowledge Management group. His current research interests include information ethics, knowledge
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2022, International Journal of Hospitality ManagementCitation Excerpt :Hofstede’s cultural theory can provide an alternative insight into this issue. According to the dimension of indulgence versus restraint (IVR), Chinese culture is characterized by suppressing immediate gratifications (Hofstede Insights, 2021, para. 18) and seeking self-restraint (LaBrie et al., 2018). In contrast, Anglosphere societies are found to value the gratification of individual needs associated with “enjoying life and having fun” (Hofstede Insights, 2021, para. 18).
Ryan C. LaBrie, Ph.D. is an Associate Professor of Management and Information Systems in the School of Business, Government, & Economics at Seattle Pacific University. Dr. LaBrie received his Ph.D. from Arizona State University. Prior to entering academia Ryan spent ten years with the Microsoft Corporation in a number of different capacities ending his time as a Program Manager in the Enterprise Knowledge Management group. His current research interests include information ethics, knowledge management, and the development of the information systems discipline. Dr. LaBrie has published in the Journal of Electronic Commerce Research, Journal of Management Systems, International Journal of Internet and Enterprise Management, Measuring Business Excellence, Encyclopedia of Knowledge Management, and the Encyclopedia of Information Ethics & Security, among others. Ryan teaches courses in database management, knowledge management, and data mining & visualization. He has presented seminars or taught courses in over a dozen countries. Dr. LaBrie is also one of the co-founders and the Chief Data Scientist for UpperAnalytics.com.
Gerhard H. Steinke, Ph.D. is a Professor of Management and Information Systems in the School of Business, Government, & Economics at Seattle Pacific University. He completed his doctoral work at the University of Passau in Germany. He has taught courses in various areas of Information Systems Management, Information Security, IS Project Management, IT Governance and Healthcare Informatics, as well as Privacy, Legal, and Ethical issues at Seattle Pacific University since 1992. He has published in the Communications of the International Information Management Association, Journal of Information Privacy & Security, Journal of International Technology and Information Management, Journal of Industrial Management and Data Systems, Telematics and Informatics Journal, Science and Engineering Ethics, Journal of Teaching in International Business, Journal of Computer Information Systems, and Hong Kong Computer Journal. Current research interests are in the areas of information security, privacy and software quality. In addition, he has consulted for organizations such as Boeing, Microsoft, AT&T Wireless, and the State of Washington. He has provided seminars not only in the US, but also in Mexico, Malaysia, and Romania.
Xiangmin Li is the Dean and a Professor of Business English in the School of English Education at Beijing International Studies University in the People's Republic of China. He earned his MA at Beijing Normal University, and is now working at Beijing International Studies University, supervising post-graduate students majoring in Business English. His research interests are in the area of Business English and English as a Second Language. He has published in the Journal of Chinese Economics, Computer Science and Applications, Asia-Pacific Management and Engineering Conference, and the International Conference on Social Science and Higher Education. Mr. Li has been a visiting scholar at Northern Arizona University and the University of Northern Florida. He is the founder and vice director of Chinese International Universities' Association of Foreign Language, vice director of Beijing College English Education and Development Center, and expert member of the Chinese Translation Association. Apart from administration work, he teaches courses in Business Communication and Business Interpretation for both undergraduates and postgraduates.
Joseph A. Cazier, Ph.D. has a background as a scientist for a large biotechnology company, a technologist with degrees and work experience in information systems, and a businessman with an MBA and consulting and entrepreneurship experience with several startups, and university administration having serviced as Associate Dean for Graduate Programs and Research. Additionally, Dr. Cazier is a faculty fellow for the University of North Carolina General Administration where he helps build and implement analytical solutions to the challenges the 17 campus system faces. Joseph is a Certified Analytics Professional (CAP) through the INFORMS organization. He is also the founder and director of the Center for Analytics Research and Education (CARE) and the Dean's Club Professor in Information Systems where he uses big data and analytical techniques to help organizations and society. Dr. Cazier has over 100 peer reviewed publications and is active in grant work. Also noteworthy, Joseph is fluent in Spanish and is the Chief Analytics Officer for Blowing Rock Software.