A Survey on Processing of Information and Computer Usage Among U.S. Hog Producers

Luiz Carlos Miranda
miranda@elogica.com.br
Universidade Federal de Pernambuco
CCSA - Departamento de Ciências Contábeis
Av. dos Economistas, s/n
Cidade Universitária
50.740-580 - Recife - PE
fone: (081) 361-5399, fax: (081) 271-8376

Resumo

Para promover o uso de softwares entre fazendeiros, é importante estudar o uso de computadores entre eles. Este estudo investiga uso de computadores entre suinocultores norte-americanos. O objetivo é determinar se diferenças na escolha de mecanismos de coordenação afetam o uso de computadores entre esses suinocultores. O estudo também investiga: (a) como suinocultores processam sua informação, (b) as atividades para as quais computadores ou assistência externa são usados para processar informação, e (c) os fatores que afetam a adoção de computadores. Os dados foram obtidos de uma pesquisa conduzida pelo autor entre 166 suinocultores em 1996 (Miranda, 1997). Os resultados indicam associação entre uso de computador e escolha de mecanismos de coordenação. Todavia, o efeito de outras variáveis pode estar afetando os resultados. Idade, nível de educação, tamanho do negócio e número de fazendas são as principais. Os resultados são comparados com os de Ortmann et al. (1992), Putler e Zilberman (1988), Batte et al (1990), Lazarus e Smith (1988), Gunter e Tuner (1993), Baker (1990), Fulton e King (1993), Harsh et al. (1994), e Jarvis (1990).

Abstract

In order to promote the usage of software among farmers, it is important to study the computer usage among them. This study investigates computer usage among U.S. hog producers. The objective is to determine whether differences in the choice of coordination mechanisms affects computer usage among U.S. hog producers. The study also investigates: (a) how hog producers process their information, (b) the activities for which computer or external assistance are used to process information, and ( c) the factors which affect computer adoption. The data was obtained from a survey conducted by the author among 166 hog producers in 1996 (Miranda, 1997). The results indicate association between computer usage and choice of coordination mechanisms. However, the effect of other variables may be masking the results. Age, education level, size and number of sites are the main ones. The results are compared with the findings of Ortmann et al (1992), Putler and Zilberman (1988), Batte et al (1990), Lazarus and Smith (1988), Gunter and Tuner (1993), Baker (1990), Fulton and King (1993), Harsh et al (1994), and Jarvis (1990).

Key Words

Processing of Information, Computer Usage, Computer adoption, coordination mechanisms, hog production, supply chain management.

1. INTRODUCTION

In order to promote the usage of software among farmers, it is important to study the computer usage among them. This study investigates computer usage among U.S. hog producers. The main objective is to investigate whether differences in the choice of coordination mechanisms affects computer usage among U.S. hog producers. Producers were classified in three groups of hog producers: independent hog producers who do not network with other hog producers, independent hog producers who network with other hog producers, and contract growers. The study also investigates: (a) how hog producers process their information, (b) the activities for which computer or external assistance are used to process information, and ( c) the factors which affect computer adoption. Miranda (1997) presents a richer set of details on this study.

2. METHODOLOGY

A survey was conducted among 166 hog producers in 1996. Miranda (1997) presents detailed information on the survey. The chi square statistic is used to test association between computer usage and the choice of coordination mechanisms. The null hypothesis in this test is

Ho: No association between the two attributes in the population.

The null hypothesis (Ho) is rejected if the chi square_c > chi square_{t (r-1) (c-1),} , where:

chi square_c is the calculated statistic. See Newbold (1988, p. 425) for formula of chi square_c;

chi square_t is the Chi-square from the table;

r is the number of rows in the table, i.e., the number of classes of one of attributes;

c is the number of columns in the table, i.e., the number of classes of the other attribute;

is the level of significance.

Producers were classified in three groups, identified as follows:

IND - independent hog producers who do not network, with 44 respondents.

NET - independent hog producers who network with other hog producers, with 95

respondents.

CON - contract growers, with 27 respondents.

3. RESULTS

The results indicate some association between computer usage and the choice of coordination mechanisms. Data on Table 1 reveal that the group NET have higher proportion of farmers processing their information with computer than the farmers in the groups IND and CON. While 68.4% of farmers in the group NET process their information with the help of a computer (either alone or with the help of professional external assistance), this percentage in the groups IND and CON falls to 38.6% and 34.6%, respectively. However, other variables also may affect computer usage. Age, education level, size and number of sites are the main ones considered in this study. The results are compared with the findings of Ortmann et al (1992), Putler and Zilberman (1988), Batte et al (1990), Lazarus and Smith (1988), Gunter and Tuner (1993), Baker (1990), Fulton and King (1993), Harsh et al (1994), and Jarvis (1990).

Most of the respondents in the survey (71%) process their production and financial information with the help of either on-site computer or professional external assistance or both (table 4.17). The analysis in this study focus only on on-site computer usage, that should be lower than total computer usage. This later concept includes the indirect computer usage that a farmer makes when assisted by professional external assistance which uses computers. The percentage of respondents using on-site computer in the survey (55%) confirms the findings of Ortmann et al. (1992) that farmers in the Cornbelt have a higher incidence of computer usage than in other U.S. regions. For example, this percentage can be compared with the 26% revealed by the survey of Putler and Zilberman (1988) on farmers in Tulane County, California, the 24% found by Batte et al. (1990) surveying Ohio commercial farmers, the 15% of Lazarus and Smith (1988)'s study on New York dairy farmers, and the 37% of Jarvis (1990)'s survey on Texan rice producers.

Earlier studies have found that age, education level, size, and number of sites have a significant impact on computer adoption by farmers (Gunter and Turner, 1993; Ortmann et al. 1992; Batte, et al., 1990; Putler and Zilberman, 1988) and by agribusiness firms (Baker, 1990; Fulton and King, 1993). The relationship between computer usage and level of education is consistent with findings in previous empirical studies. A high incidence of computer usage was registered among more highly educated producers. Sixty nine percent of producers with college degree or higher use computer, while only 38% of producers with high school degree or less use computer.

The usage of computer in this survey is also significantly correlated with number of sites and size (measured by number of hogs). Adoption of computer is higher among hog producers managing multi-site operations. While only 45% of producers operating one site adopt computer, this percentage is 69% for two sites, 77% for three sites, and 82% for four sites operation. The analysis of association between computer usage and number of sites resulted in a chi-square of 12.37, significant at 1%. With respect to size, the survey reveals that while only 27% of hog producers in the size range of 1-500 adopt computer, 65% of producers with sales of 5000 or more use computer to process their production and financial information.

With respect to age, the numbers from the survey do not show a strong association of this variable and computer usage. The analysis of association registers statistical significance only for the comparison between the stratum of age 44 or under and 55 and over. Chi-square is significant at 9%, and Fisher's exact test is significant at 7% (one-tail test).

With respect to the use of professional external assistance to process financial and production information, the survey reveals that 44% of the respondents use such professional assistance. Data in Table 1 reveals that 16% of respondents use professional external assistance but do not use computer and 29% use both.

Table 1: Distribution of Producers by Methods of Processing the Financial and Production Information

As suggested by other studies (Harsh et al, 1994; Batte et al., 1990), data in Table 2 indicates that the most common use of computer and/or external assistance is to process information for tax purpose. Among those producers who use either computer or external assistance to process information, 89% use them to process information for tax purpose, 85% use them to process production information, and 82% use them to process financial information.

Table 2: Distribution of Producers by Activities for which Computer or External Assistance Are Used to Process Information

4. CONCLUSION

The choice of coordination mechanisms to coordinate the activities affects computer usage among U.S. hog producers. Computer usage is also affected by some characteristics of farmers and of the enterprise. Level of education is higly correlated with computer usage suggesting that highly educated farmers make more use of computer to run their farms. The study also presents evidence that the size matters in the adoption of computer. The adoption of computer to process production and financial information is higher among farmers which produce more hogs.

5. REFERENCES

• Baker, G. (1990) Characteristics of computer usage and determinants of microcomputer success by agribusiness. Agribusiness, 6 (2), 109-119.
• Batte, M. T., Jones E., and Schnitkey, G. D. (1990) Computer use by Ohio commercial farmers. American Journal of Agricultural Economics. 72 (4), 935-945.
• Fulton, J. R. and King R. P. (1993) Relationships among information expenditure, economic performance, and size in local grain marketing cooperatives in the Upper Midwest. Agribusiness. 9 (2), 143-157.
• Gunter, L. F. and Turner, S. C. (1993) Computerization in the US ornamental nursery industry. Agribusiness 9 (1), 77-90.
• Harsh, S., Schwab, G., Hepp, R. , and Jones, J. (1994) Designing financial records systems for spporting business decisions. Computers in Agriculture 1994: Proceedings of the 5th International Conference. D. G. Watson, F. S. Zazueta, and T. V. Harrison (Eds.), Michigan: American Society of Agricultural Engineers, St. Joseph.
• Jarvis, A. M. (1990) Computer adoption decisions - implication for research and extension: the case of texas rice producers. American Journal of Agricultural Economics, 72, 1388-1394.
• Lazarus, W. F., and Smith, T. R. (1988) Adoption of computers and consultant services by New York dairy farmers. Journal of Dairy Science, 71, 1667-1675.
• Miranda, L. C. (1997) The role of interfirm information exchange and choice of coordination mechanism on performance in the U.s. prok supply chain. Unpublished Ph.D. Dissertation, University of Illinois, Illinois.
• Newbold, P. (1988) Statistics for Business and Economics (2nd Ed.). Englewood Cliffs, Prentice Hall, New Jersey.
• Ortmann, G. F., Patrick, G. F., Musser W. N., and Doster D. H. (1992) Information sources, computer use, and risk management: evidence from leading commercial cornbelt farmers. Station Bulletin 638, Department of Agricultural Economics. Agricultural Experiment Station. Purdue University. West Lafayette, IN.
• Putler, D. S., and Zilberman, D. (1988) Computer use in agriculture: evidence from Tulare County, California. American Journal of Agricultural Economics, 70 (4), 790-802.

6. BIOGRAFIA

Luiz Carlos Miranda é Bacharel em Economia, Mestre em Contabilidade (Controladoria) pela USP, e Ph.D. (Agribusiness e Contabilidade Gerencial) pela Universidade de Illinois. Suas áreas de interesse incluem Contabilidade Gerencial, Controladoria, Sistemas de Informações Intra e Inter-Empresariais, Desempenho Gerencial, Supply Chain Management, Agribusiness. Trabalhou no Banco Central do Brasil, no Grupo Sanbra/Santista, onde foi responsável pela coordenação do sistema de planejamento (na Holding, em São Paulo, e nasTintas Coral do Nordeste, onde foi controller. É professor do Departamento de Ciências Contábeis e do Executive MBA em Finanças da UFPE e consultor de empresas. Coordena a pós-graduação em Ciências Contábeis da UFPE. Publicou diversos artigos em revistas e participou como apresentador e coordenador de vários seminários.