Remember to review the syllabus expectations for initial discussion posts and peer replies.

Discuss the following: 1. What are blockchain’s potential applications in organizational functions such as human resource management, accounting, and supply chain management? You are required to cite this week’s assigned readings in your paper. You may also cite prior week’s reading assignments and external sources if you wish.

Use the following headings to organize your paper: Introduction, Question 1, Conclusion, References.

Submit your paper as a Word attachment in the discussion forum. I provide feedback within the paper and will not grade your post unless you submit it as an attachment. Your response to the discussion prompt should contain a minimum of 500 words and it should be submitted no later than Tuesday before 11:59 pm EST.  Your response should be formatted in APA style and reference this week’s readings.

 

From the Text

1. Chapter 1 from Blockchain for Business

From the Harvard Course Pack Link:  https://hbsp.harvard.edu/import/688391

2. Hughes, A., Park, A. Kietzmann, J., & Archer-Brown, C. (2019). Beyond Bitcoin: What Blockchain and distributed ledger technologies mean for firms. Business Horizons, 62, 273-281.

From the UC Library: Access the Library at  http://www.ucumberlands.edu/library/ and Search by Title

3. Gale, S. F. (2018, July/August). Blockchain: The future of HR? Workforce, 97(4), 10.

Follow the following writing requirements for all of your discussion prompt responses (note that these writing requirements DO NOT apply to your responses to other students):

Writing Requirements for all Assignments:

  • References MUST be cited within your paper in APA format. Your reference page and in-text citations must match 100%. Papers without in-text citations will earn failing grades.
  • Always include a cover page and reference page with all submissions
  • Your paper must have headings in it. For discussion posts Introduction, Prompt/Question, and Conclusion will suffice as headings.
  • Provide the EXACT web link for all online sources – do not provide just the home page, but the EXACT LINK – I check all sources
  • No abbreviations, no contractions – write formally
  • Write in the third person formal voice (no first or second person pronouns)
  • Write MORE than the minimum requirement of the word count assigned
  • As always, the word count is ONLY for the BODY of the paper – the cover page, reference page, and / or Appendix (if included) do not count towards the word count for the paper
  • Indent the first line of each new paragraph five spaces
  • Refer to the example APA paper in the getting started folder under the content tab if you need an example. Also, a power is provided under the information tab that addresses APA format.
  • Use double-spacing / zero point line spacing, a running header, page numbers, and left justify the margins.

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7. A quant jock from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results. Unfortunately, some entries are missing because the toner was low in her printer. Use the information presented below to find the missing values labeled ‘1’ through ‘7’ (round your answers to the nearest hundredth). Then, answer the accompanying questions. (LO6) SUMMARY OUTPUT Regression Statistics Multiple R 0.38 R-Square ‘1’ Adjusted R-Square ‘2’ Standard Error 20.77 Observations 150 Analysis of Variance Degrees of Freedom Sum of Squares Mean Square F Significance F Regression 2 ‘3’ 5199.43 12.05 0.00 Residual 147 63,408.62 431.35 Total ‘4’ 73,807.49 Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 58.87 ‘5’ 3.84 0.00 28.59 89.15 Price of X -1.64 0.85 ‘6’ 0.06 -3.31 0.04 Income ‘7’ 0.24 4.64 0.00 0.63 1.56 Final PDF to printerbay90611_ch03_064-100.indd 97 10/27/16 08:07 PM 97 a. Based on these estimates, write an equation that summarizes the demand for the firm’s product. b. Which regression coefficients are statistically significant at the 5 percent level? c. Comment on how well the regression line fits the data

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