ProjectProposal_Group019_WI24.ipynb

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   "source": [
    "# COGS 108 - Project Proposal"
   ]
  },
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   "metadata": {},
   "source": [
    "# Names\n",
    "\n",
    "- Sebastian Modafferi\n",
    "- McKayla David\n",
    "- Kirthin Rajkumar\n",
    "- Matthew Chan\n",
    "- Anna Potapenko"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Research Question"
   ]
  },
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   "metadata": {},
   "source": [
    "Is a larger company more likely to lay off employees than a smaller company? If not, what indicators can be viewed to analyze what influences company layoffs?"
   ]
  },
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   "metadata": {},
   "source": [
    "## Background and Prior Work"
   ]
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   "metadata": {},
   "source": [
    "Layoffs refer to economic and organizational changes, and are a significant indicator of the success and development of companies. While they affect employees, layoff rates have a broader implication on the health of the economy, industry trends, and the state of the workforce. Understanding the trends and impacts of layoffs is vital not only on a global economic scale, but within communities of stakeholders and individual communities.\n",
    "\n",
    "Layoffs are important to study due to their relevance to both companies and employees. For a company, understanding indicators which can predict imminent layoffs can help them course correct before reaching a point of no return. On the other hand, employees understanding layoff indicators can help them in choosing the correct company for their next role, ensuring job safety. \n",
    "\n",
    "Research published in the Journal of the European Economic Association [1^](#https://academic.oup.com/jeea/article-abstract/18/1/427/5247011) explored the economic influences that cause layoffs, and inquired into how financial health and market factors influence layoff decisions. A similar study published in Journal of Labor Economics looks into the effects of layoffs on unemployment rates, and found that layoffs can have lasting impact on the job market and employee career trajectory.\n",
    "\n",
    "The journal of Labor Empirical Finance [3^](#https://doi.org/10.1016/s0927-5398\\(01\\)00024-x) also looks into the different firms and what caused their layoffs, giving insight into company restructuring and different technologies that help to modify the workforce requirements. Additionally, past precedent reviewed by JSTOR [2^](#https://www.jstor.org/stable/117002?casa_token=m7s1bFw7mY4AAAAA%3AhaYXwJWsj5E0Xo7vbnjns6omvUnSFYlenLVZ99nBhONKkQRCLyfLIdEk3ZJycob9If4HtLaMga7y7cQzrzAO6QfJYXTkccHfVciVYhTXREH7HSHuGN4) article explains the repetition of layoffs and how it correlates with economic cycles. This suggests that layoffs are an essential part of economic growth.\n",
    "\n",
    "Research on layoffs adopts an interdisciplinary approach, using economic theories, organizational behavior, and societal impacts. Overall, it is imperative to understand the factors that influence layoffs because knowledge about these factors can help researchers develop strategies to mitigate the negative effects of layoffs on employees and the economy at large. \n",
    "\n",
    "1. <a name=\"Journal of the European Economic Association\"></a> [^](#https://academic.oup.com/jeea/article-abstract/18/1/427/5247011) Gathmann, C., Helm, I., & Schönberg, U. (2018). Spillover effects of mass layoffs. Journal of the European Economic Association, 18(1), 427–468. https://doi.org/10.1093/jeea/jvy045\n",
    "2. <a name=\"JSTOR\"></a> [^](#cite_ref-2) Hallock, Kevin, (1998). Layoffs, top executive pay, and firm performance on JSTOR. (n.d.). www.jstor.org. https://www.jstor.org/stable/117002\n",
    "3. <a name=\"Journal of Empirical Finance\"></a> [^](#https://doi.org/10.1016/s0927-5398\\(01\\)00024-x) Chen, P., Mehrotra, V., Sivakumar, R., & Yu, W. (2001). Layoffs, shareholders’ wealth, and corporate performance. Journal of Empirical Finance, 8(2), 171–199. https://doi.org/10.1016/s0927-5398(01)00024-x\n"
   ]
  },
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   "metadata": {},
   "source": [
    "# Hypothesis\n"
   ]
  },
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   "metadata": {},
   "source": [
    "We are inclined to believe this due to the fact that smaller companies already have less employees, so lay-offs are more likely to harm the business than benefit it. Additionally, larger companies are able to withstand more financial pressure, allowing them to perform large layoffs despite the impact on company performance given that they have enough capital with withstand the losses.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ideal dataset would include revenue, number of employees, percent laid off, year, type of company, size of company, share price (public or private), growth, year before data, number of mass layoffs in companies life, etc. Some promising datasets we have found are\n",
    " - https://www.kaggle.com/datasets/ulrikeherold/tech-layoffs-2020-2024\n",
    " - https://layoffs.fyi/\n",
    " - https://www.kaggle.com/datasets/mysarahmadbhat/inc-5000-companies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ethics & Privacy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Potential ethical concerns: \n",
    " - layoffs.fyi dataset has some data about fired employees with names (we should ignore that column)\n",
    " - Layoffs.fyi only pulls data from news articles, so it is a biased sample (information that is only accessible to the public)"
   ]
  },
  {
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   "source": [
    "How will we address these concerns?\n",
    " - Omit private employee information\n",
    " - Omit company name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Team Expectations "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - Be reliable in terms of completing one’s own work/contributions\n",
    " - Maintain open communication between team members\n",
    " - Be an active contributor to group discussions\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project Timeline Proposal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Meeting Date  | Meeting Time| Completed Before Meeting  | Discuss at Meeting |\n",
    "|---|---|---|---|\n",
    "| 02/04 | 1 PM | Read previous COGS 108 Final Projects | Complete previous quarters’ COGS 108 Final Project Analysis, plan meeting times, begin discussing project topics. | \n",
    "| 02/05  | 1 PM | Brainstorm project topics, potential data sources, and viability of research questions | Discuss and decide on final project topic; discuss hypothesis; begin background research Discuss ideal dataset(s) and ethics; draft project proposal| \n",
    "| 02/11  | 1 PM | Edit, finalize, and submit proposal; Search for datasets | Discuss Wrangling and possible analytical approaches; Assign group members to lead each specific part |\n",
    "| 02/18  | 1 PM  | Delegate Tasks and start wrangling | Go over what everyone has done. Make edits or revise things before. Also go over revisions and feedback from the proposal. |\n",
    "| 02/25  | 1 PM  | Finalize wrangling/EDA; Begin Analysis | Meet for Checkpoint #1 |\n",
    "| 03/13 | 12 PM  | Complete analysis; Draft results/conclusion/discussion | Discuss/edit full project |\n",
    "| 03/20  | Before 11:59 PM  | NA | Turn in Final Project & Group Project Surveys |"
   ]
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