Socioeconomic Impact of Automation on Horticulture Production Firms in the Northern Gulf of Mexico Region

Abstract

<jats:p>Using results of a socioeconomic survey of nurseries and greenhouses, Tobit regression analysis was used to estimate empirical models to measure the socioeconomic impact of automation or mechanization on annual gross sales, annual employment, and workers' earnings, safety, and retention. The survey was conducted among 87 randomly selected nurseries and greenhouses located in Mississippi, Louisiana, and Alabama, from Dec. 2003 to Mar. 2005. About 20% of all the identified major tasks were performed by workers in nurseries and greenhouses with some form of mechanization or automation. Regression results showed that nurseries and greenhouses that experienced higher levels of sales also demonstrated higher levels of automation or mechanization. The employment impact of automation or mechanization was neutral, indicating that any improvement in automation or mechanization did not necessarily lead to a reduction, but instead to a more efficient use of labor by nurseries and greenhouses. Improvements in automation or mechanization resulted in higher total workers' earnings reported by participating nurseries and greenhouses. Further Tobit regression results showed that automation or mechanization had neutral effects on the length of training period, workers' safety, and retention rates and enabled nurseries and greenhouses to hire less-skilled workers.</jats:p>

Economic Impacts of Mechanization or Automation on Horticulture Production Firms Sales, Employment, and Workers’ Earnings, Safety, and Retention

“…The TR of nurseries and greenhouses were derived from the midpoint of the annual gross sales category reported by each participating nursery or greenhouse operation. The TR were deflated by the consumer price index (CPI, 2009 = 100) This empirical TWE model is similar to Posadas et al (2008) except with the use of deflated values of workers' earnings, addition of the interview date as explanatory variable, and estimation of a variant model where the number of FTE workers was broken down into PW and PTW. The separation of the number of FTE workers allowed for the comparison of the marginal earnings of the PW and PTW.…”

“…These annual gross sales categories were based on the suggestions made by Hoppe et al (2007) which included the following: less than $250,000, $250,000 to $499,999, $500,000 to $999,999, and more than $1,000,000. The empirical WS model is analogous to Posadas et al (2008) with the addition of the interview date, the three farm sizes as explanatory variables, and a variation where the independent variable FTE workers was broken down into PW and PTW. Training time (TT) was determined by the length of the basic training period for the newly hired workers.…”

“…The workers' TT impact (TTI) was indeterminate depending on the need for increased training in the handling of specialized equipment and the lower requirement for manual workers as a result of automation or mechanization. The TTI hypothesis was tested using the following empirical model: The empirical TT model is equivalent to Posadas et al (2008) with the addition of the interview date, the three farm sizes as explanatory variables, and a variation where the independent variable FTE workers was separated into PW and PTW.…”

“…Workers in this industry perform varied functions and are subjected to different working conditions (O*Net Online, 2012). Posadas et al (2008) reported that at least 8 of the 15 major tasks were performed by workers with significant number of nurseries using mechanized or automated systems in media preparation, filling containers with substrates, moving containers from potting to transport, transporting containers to field, plant pruning, and fertilizer, pesticide, and irrigation application. Six of the 10 major tasks were performed by workers employed by a significant number of greenhouse operations with mechanized or automated systems in media preparation; filling containers with substrates; environmental control; and fertilizer, pesticide, and irrigation application.…”

“…This article is a spatially, temporally, and analytically expanded version of an earlier article which covered 87 growers located in the three northern Gulf of Mexico states (Posadas et al, 2008). With the data collected by face-to-face interviews of nurseries and greenhouses, multiple linear regression analysis was applied to estimate empirical models to measure the socioeconomic impact of automation or mechanization on annual gross sales; annual employment; and workers' earnings, safety, and retention.…”