You will review your classmates initial postings and choose one classmate to complete the following for your reply: Write a 250 to 300-word response to your cla

Stephen

Economic Data

Governments worldwide, the United States included, are significant producers and repositories of data, openly made available to be used by private citizens and business alike (Coronado, J. & Hughes-Cromwick, E., 2019, Gottfried, A., et al., 2021, and Mohamed, M., et al., 2020). Mohamed, M., et al. (2020) continues stating that government data is property of the public, often required by law to be so, and designed to be of utility. It is further noted that this breadth of data is often segmented and thereby isolated in its respective silos, Grainger, A., et al. (2020) suggests an expansion of collaboration efforts in information sharing to include various levels and branches of government, foreign governments, as well as private and non-profit organizations. Mohamed, M., et al. (2020) contends this iconic shift in strategy portrays organizations that openly share non-confidential information for the common benefit of all, while simultaneously maintaining and developing its own competitive advantage. Gottfried, A., et al. (2021) add that the benefits, although uniquely specific to an industry, spans industry type from health, finance, manufacturing and beyond.    

Coronado, J. and Hughes-Cromwick, E. (2019) note that data produced internally by an organization is often insufficient to fully execute business decisions, therefore data collected from the government serves as a supplement. Gottfried, A., et al. (2021) state that although open government data provides a wealth of information, many organizations within the public sector have yet to leverage its benefits. Coronado, J. & Hughes-Cromwick, E. (2019) indicate that these benefits include, but are not limited to obtaining competitor price data, applying census bureau demographic data to commercial real estate decisions and employee cost of living rates, demand expectations to inform production projections, etc. Gottfried, A., et al. (2021) add that open government data offers business insight on industry competition, market stability and consumer behavior. Kiviat, B. (2019) cites a slightly more obscure use of open data, noting that employers utilize credit reports in the hiring process as they evaluate the potential character of candidates based on financial behaviors. Gottfried, A., et al. (2021) suggests that despite the ample benefits of open government data, challenges face its implementation in business, further emphasizing the lack of knowledge regarding its existence and utility. The authors additionally cite organizational willingness to adopt as a significant challenge. Still, the primary recurring barrier to implementation is the usability of data. Mohamed, M., et al. (2020) notes that users are faced with a substantial undertaking when attempting to collect and analyze open government data, which is often raw and coded in unfriendly formats, creating the need for excessive human manipulation.       

Becker, M., et al. (2022) asserts that despite the significant growth in the digital economy, minimal attention has been devoted to its integration with open government data. The authors suggest additional research be conducted on the open government data lifecycle including adoption, barriers, and reciprocation with government systems. Additionally, Mohamed, M., et al. (2020) echoes the need for the greater influence of technology in the data extraction and synthesis processes. Successful integration of open government data in business decisions requires collective participation of participants at all governmental levels and business sectors, wherein the parties embrace a culture of cooperation and trust.     

References

Becker, M., Muller, W., Weyerer, J. & Wirtz, B. (2022). Open government data: A systematic literature review of empirical research.  Electronic Markets, 32, 2381-2404. https://doi.org/10.1007/s12525-022-00582-8.

Coronado, J. & Hughes-Cromwick, E. (2019). The value of US government data to US business decisions.  Journal of Economic Perspectives, 33(1), 131-146. https://doi.org/10.1257/jep.33.1.131.

Gottfried, A., Hartmann, C. & Yates, D. (2021). Mining open government data for business intelligence using data visualization: A two-industry case study.  Journal of Theoretical and Applied Electronic Commerce Research, 16, 1042-1065. https://doi.org/10.3390/jtaer16040059.

Grainger, A., Heijmann, F., Huiden, R., Ravulakollu, A., Rukanova, B. & Tan, Y. (2020). A framework for voluntary business-government information sharing.  Government Information Quarterly, 37, 1-12. https://doi.org/10.1016/j.giq.2020.101501.

Kiviat, B. (2019). The art of deciding with data: evidence from how employers translate credit reports into hiring decisions.  Socio-Economic Review, 17(2), 283-309. https://doi.org/10.1093/ser/mwx030.

Mohamed, M., Pillutla, S. & Tomasi, S. (2020). Extraction of knowledge from open government data: The knowledge iterative value network framework.  VINE Journal of Information and Knowledge Management Systems, 50(3), 495-511. https://doi.org/10.1108/VJIKMS-05-2019-0065.

Toni

Economic Data

            The value of government data to the private sector is not currently quantified.  The question of value of government data is how it is to be defined for the quality and quantity of the data.  Hughes explains this value to be a firm’s own data complemented with a wide range of data collected by the government.  It is an accessory not the foundation.  The US Department of Commerce reported that in 2012, government data intensive businesses (GDIS) revenues were over $220 billion.  The growth of these businesses is rapidly expanding.  This growth in value added government data is improved by interfaces linking directly to government data.  Automotive, energy, and financial services are examples of industries that benefit greatly from government data access.  The relatively low cost of government data provides a sound investment to expand the public budget to enhance quality, scope, access, and timeliness of this data to private sectors.  This stance on benefit and value is not shared by many, the risk of declining support for government data will affect both existing businesses and new ventures.

            Data analytics and improvement of the process to retrieve, qualify, and quantify this data is a topic of intense review. (Hughes-Cromwick and Coronado, 2019; Marjanovic, 2022; Monino, 2021; Szukits, 2022) The ability to calculate the value add that big data provides is still an issue of research and study.  Business decisions are based on analytics and statistics, these numbers are derived from data.  The automotive industry uses government data to make various short-term decisions around production rates, desired inventory, and pricing.  They also use the data for long term commitments around expansion, supply chain management, and logistics. The energy sector makes short-term decisions on pricing and inventory usage as well.  The financial industry looks at data linked to interest rates, credit, and money supply. (Hughes-Cromwick and Coronado, 2019) These are examples of industry usage of government data but the question of how valuable the data is warranting discussion.  Is the value added worth the potential risk? (Di Vaio, Hassan, & Alavoine, 2022; Gupta and Bansal, 2022; Marjanovic, 2022; Szukits, 2022) Artificial intelligence (AI) is gaining more importance around the field of dig data and what it can bring to the table in the public and private sectors.  There are concerns that AI will eliminate the need for human intervention and replace jobs in an economy that is already teetering on recession. Di Vaio and team explain that an intellectual capital market is a framework of both human and AI interaction.  AI is directed by human guidelines and then AI produces intelligent data based on those criteria.  AI is useless without human instruction. (Di Vaio, Hassan, & Alavoine, 2022) Marjanovic goes further to state that big data is rich with value but only if the human mind can understand and interpret that data. (Marjanovic, 2022) Human knowledge and experience along with bug data create a competitive advantage.  On the side of the coin, human involvement can detract from the value of information.  Government policy and political pressures, human consequences, can skew or interpret that data as it benefits their agenda. (Gupta and Bansal, 2022; Szukits, 2022)

             Government data value is challenging to quantify but plays an important role in business decisions in the private sector.  As technological advances continue to develop more and more data is available to analyze. Further research needs to be completed in the value add of government data, to justify continued public support and financial investment into government data platforms and production.  The transition from raw data to usable knowledge also has additional research that needs to be done to streamline this process.  AI is a tool in this transition process but understanding the human factor of AI interaction will require further discussion and investigation to maximize the relationships benefits. 

References

Di Vaio, A., Hassan, R., & Alavoine, C. (2022). Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting & Social Change, 174, 121201.  https://10.1016/j.techfore.2021.121201 Links to an external site.

Gupta, S., & Bansal, S. (2022). Optimal market-integration decisions by policymakers: Modeling and analysis of agriculture market data. Operations Research, 70(1), 352-362.  https://10.1287/opre.2021.2191 Links to an external site.

Hughes-Cromwick, E., & Coronado, J. (2019). The value of US government data to US business decisions. The Journal of Economic Perspectives, 33(1), 131-146.  https://10.1257/jep.33.1.131 Links to an external site.

Marjanovic, O. (2022). A novel mechanism for business analytics value creation: Improvement of knowledge-intensive business processes. Journal of Knowledge Management, 26(1), 17-44.  https://10.1108/JKM-09-2020-0669 Links to an external site.

Monino, J. (2021). Data value, big data analytics, and decision-making. Journal of the Knowledge Economy, 12(1), 256-267.  https://10.1007/s13132-016-0396-2 Links to an external site.

Szukits, Á. (2022). The illusion of data-driven decision making – the mediating effect of digital orientation and controllers’ added value in explaining organizational implications of advanced analytics. Journal of Management Control, 33(3), 403-446.  https://10.1007/s00187-022-00343-w

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