Hiring workers under seasonal recruiting contracts causes significant variation of workers skills in the vineyards. This leads to inconsistent workers performance, reduction in harvesting efficiency, and increasing in grape losses rates. The objective of this research is to investigate how the variation in workers experience could impact vineyard harvesting productivity and operational cost. The complexity of the problem means that it is difficult to analyze the system parameters and their relationships using individual analytical model. Hence, a hybrid model integrating discrete event simulation (DES) and agent based modeling (ABM) is developed and applied on a vineyard to achieve research objective. DES models harvesting operation and simulates process performance, while ABM addresses the seasonal workers heterogeneous characteristics, particularly experience variations and disparity of working days in the vineyard. The model is used to evaluate two seasonal recruiting policies against vineyard productivity, grape losses quantities, and total operational cost.
In order to be competitive, grape growers have to show high operational performance through effective control of crop operation, accurate and timely execution of tasks, and effective use of workers. Grape harvesting is labor intensive and time consuming operation given the vulnerable, highly variable and complex work environment (Meyers et al. 2006). Many biological, technological, and sociological factors affect harvesting efficiency and cost. Among others, worker experience is a crucial factor that have direct impact on crop productivity, waste rate, and total operational cost. Agricultural workers, in particular those who are hired based on seasonal contracts, often have few qualifications and their skills are highly diverse. According to the human capital theory, introduced by Becker (2009), productivity is changed in terms of the level of experience that the individuals can accumulate. In some situations, experience is appropriate indicator of worker’s productivity level, in particular when imperfect information exist (Bellit 2014). Although the direct relationship between worker’s experience, skills and operations productivity, the topic has received less attention in the literature. This raises many questions between researchers and growers alike such as, how the variation in worker skills impact grape crop productivity and waste rate?, is it economical to work with low skilled, low paid workers?, and what are the alternative recruiting scenarios that improve harvesting operations performance and how much does it cost?
In order to answer these questions, systematic and analytical decision support models that analyze and simulate harvesting operation in grape vineyards are needed. Such models can be used to support decision makers and help to investigate the impact of workers experience on grape harvesting efficiency. In addition, they can be used to quantitatively evaluate labor hiring policies and investigate their effect on vineyard operations. However, only few applications of such models have been described in the cultivating systems and in particular at vineyards operations (Ferrer et al. 2008, Bohle, Maturana, and Vera 2010).
Seasonal Worker State Chart in the Model
Using simple mathematical models to achieve this objective in a complex and dynamic cultivating system such as the vineyards is not applicable. These models tend to be static, deterministic and mostly handle one single objective. Discrete event simulation (DES), on the other hand, is an alternative approach that is able to capture the complex relationships, time dynamics and stochastic behavior of the cultivating systems (Krejci and Beamon 2012). However, this approach comes short in its ability to consider human behavior and the sociological issues in the cultivating systems – the heterogeneous characteristics of seasonal labor markets and its high turnover (Whatman and Van Beek 2008). Agent based Modelling (ABM) is effectively used in the literature to model the heterogeneous, autonomous and interacting actors within the complex systems (Higgins et al. 2010). Therefore, this paper contributes to the research area by introducing an integration between DES and ABM approaches to develop a hybrid decision support model for the vineyard. The presented model presents the complex relationships within the vineyard harvesting operations while considers the characteristics of the seasonal workers in the vineyard operations.