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Electronic Commerce Research
Published in: Electronic Commerce Research 2/2015

01-06-2015

Access to the Internet and financial performance of small business households

Authors: Aditya R. Khanal, Ashok K. Mishra, Krishna H. Koirala

Published in: Electronic Commerce Research | Issue 2/2015

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Abstract

With increased focus on survival strategies for small farm businesses, we investigate the impact of access to the Internet on household income and expenses of small farm businesses and households. Using a nationwide data from the U.S. and non-parametric matching estimators, the study finds a significant positive impact of access to the Internet on total household income and off-farm income. Our study suggests that small farm businesses benefit from Internet access as it increases business income, off-farm income and total household income. Also, access to the Internet reduces some input costs and household expenses.
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Footnotes
1
Gross cash farm income is the sum of the farm’s cash and marketing contract revenues from the sale of livestock and crops. It includes all farm-related revenue, not just crop and livestock sales, and is based on annual sales, not the value of annual production.
 
2
Further, in addition to other reasons for Internet adoption, Mishra et al. [25], studying farm business households, point out that the Farm Service Agency, a major provider of farm program payments to farmers, has about 78 farm program forms available online for farmers to complete and submit electronically via the Internet.
 
3
Total household income is composed of off-farm income and farming income. Total off-farm income includes income from wages and salaries, off-farm business income, and income from non-earned sources.
 
4
It should be pointed out that most existing studies have explored Internet applications, purchasing patterns, and factors influencing Internet adoption.
 
5
The financial measures used in this study are (1) incomes: total household income,  total off-farm income, gross cash farm income, and net farm income; (2) cost: total variable costs, marketing and storage cost, fertilizer and chemical cost, and utilities, household supplies, and other household expenses.
 
6
Recall total household income is composed of income from both off-farm sources and farm sources.
Table 3
Estimates of the average treatment effect on treated (ATT)
Variable
Number of matches (m)
ATT
Standard errors
p value
Income variables
    
Total household income ($ per year)
1
27,464
8,949.577
0.002
2
27,630
8,725.659
0.002
3
26,058
8,611.950
0.002
4
24,699
8,694.806
0.005
5
23,935
8,733.610
0.006
Total off-farm income ($ per year)
1
29,762
8,992.094
0.001
2
29,729
8,783.844
0.001
3
28,164
8,675.245
0.001
4
26,881
8,756.092
0.002
5
26,025
8,797.191
0.003
Gross farm income ($ per year)
1
2,767
1,182.436
0.019
2
2,239
1,147.775
0.050
3
2,291
1,104.129
0.038
4
2,425
1,089.196
0.026
5
2,547
1,073.766
0.018
Net farm income ($ per year)
1
\(-\)705.014
1,387.100
0.611
2
\(-\)765.003
1,342.123
0.569
3
\(-\)527.301
1,297.571
0.601
4
\(-\)504.575
1,280.629
0.647
5
\(-\)324.911
1,271.625
0.689
Production under marketing contract
1
418.979
378.117
0.268
2
398.100
372.135
0.285
3
404.498
363.562
0.266
4
409.276
358.982
0.254
5
397.757
356.254
0.264
Cost and expense variables
    
Total variable expenses
1
1,569
842.351
0.062
2
1,284
833.466
0.123
3
1,102
808.317
0.173
4
1,210
788.922
0.125
5
1,131
782.377
0.148
Marketing and storage charges
1
\(-\)7.410
54.721
0.791
2
\(-\)6.191
50.722
0.892
3
\(-\)5.281
50.052
0.901
4
\(-\)10.132
48.941
0.923
5
\(-\)9.152
48.490
0.850
Fertilizer and chemical expenses
1
\(-\)74.112
211.990
0.526
2
\(-\)307.191
220.051
0.132
3
\(-\)318.473
209.531
0.105
4
\(-\) 332.833
201.787
0.090
5
\(-\) 355.714
201.607
0.078
Utilities, housekeeping supplies, and other household expenses
1
4.226
432.228
0.992
2
\(-\)221.185
429.587
0.509
3
\(-\)302.7059
439.838
0.491
4
\(-\)270.432
427.010
0.527
5
\(-\)318.991
435.516
0.464
* Bold indicates significance at the 1 % level, while the italic indicates significance at 5 or 10 % level, and no style indicates that results were insignificant
 
Literature
1.
Abadie, A., & Imbens, G. W. (2002). Simple and bias-corrected matching estimators for average treatment effects. Cambridge, MA: T0283, National Bureau of Economic Research Inc.
2.
Abadie, A., Drukker, D., Herr, J. L., & Imbens, G. W. (2004). Implementing matching estimators for average treatment effects in stata. Stata Journal, 4, 290–311.
3.
Alam, S. S., & Noor, M. K. M. (2009). ICT adoption in small and medium enterprises: An empirical evidence of service sectors in Malaysia. International Journal of Business and Management, 4(2), P112.CrossRef
4.
Batte, M. T. (2004). Computer adoption and use by Ohio farmers. Journal of American Society of Farm Managers and Rural Appraisers, 67(1), 108–111.
5.
Batte, M. T. (2005). Changing computer use in agriculture: Evidence from Ohio. Computers and Electronics in Agriculture, 47, 1–13.CrossRef
6.
Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2, 358–377.
7.
Briggeman, B. C., & Whitacre, B. E. (2010). Farming and the internet: Reasons for non-use. Agricultural and Resource Economics Review, 39(3), 571–584.
8.
Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and applications. Cambridge, NY: Cambridge University Press.CrossRef
9.
Chang, H., & Just, D. R. (2009). Internet access and farm household income: Empirical evidence using semi-parametric assessment in Taiwan. Journal of Agricultural Economics, 60(2), 348–366.CrossRef
10.
11.
Dasgupta, P., & Sengupta, K. (2002). E-commerce in the Indian insurance industry: Prospects and future. Electronic Commerce Research, 2(1–2), 43–60.CrossRef
12.
Deakins, D., Mochrie, R., & Galloway, L. (2004). Rural business use of information and communications technologies: A study of the relative impact of collective activity in rural Scotland. Strategic Change, 13, 139–150.CrossRef
13.
Dholakia, R. R., & Kshetri, N. (2004). Factors impacting the adoption of the internet among SMEs. Small Business Economics, 23(4), 311–322.CrossRef
14.
Dubman, R. W. (2000). Variance estimation with USDA’s farm costs and returns surveys and agricultural resource management study surveys. Staff paper no. AGES00-01 resource economics division. Washington, DC: Economic Research Service, U.S. Department of Agriculture.
15.
García-Murillo, M. (2004). Institutions and the adoption of electronic commerce in Mexico. Electronic Commerce Research, 4(3), 201–219.CrossRef
16.
Gloy, B. A., & Akridge, J. T. (2000). Computer and internet adoption in large U.S. farms. International Food and Agribusiness Management Review, 3, 323–338.CrossRef
17.
Gökmen, A. (2012). Virtual business operations, e-commerce & its significance and the case of Turkey: Current situation and its potential. Electronic Commerce Research, 12(1), 31–51.CrossRef
18.
Henderson, J., Doley, F., Akridge, J., & Carerre, A. (2005). Adoption of internet strategies by agribusiness firms. International Food and Agribusiness Management Review, 8(4), 42–61.
19.
Hoppe, R. A., McDonald, J. M., & Korb, P. (2010). Small farms in the United States: Persistence under pressure. Washington, DC: Economic Information Bulletin Number 63, Economic Research Service, U.S. Department of Agriculture.
20.
Jennex, M. E., Amoroso, D., & Adelakun, O. (2004). E-commerce infrastructure success factors for small companies in developing economies. Electronic Commerce Research, 4(3), 263–286.CrossRef
21.
Khandker, S. R., Koolwal, G. B., & Samad, H. A. (2010). Handbook on impact evaluation: Quantitative methods and practices. Washington, DC: The World Bank.
22.
Martin, L. M., & Matley, H. (2003). Innovative use of internet in established small firms: The impact of knowledge management and organizational learning in accessing new opportunities. Qualitative Market Research: An International Journal, 6(1), 18–26.CrossRef
23.
McFarlane, D., Chembezi, D., Befecadu, J. (2003). Internet adoption and use of e-commerce strategies by agribusiness firms in Alabama. Working Paper SFRC-03., Small Farms Research Center, Alabama A&M University. Selected Paper, Southern Agricultural Economics Association annual meeting, Mobile, AL, Feb 1–5, 2003.
24.
Mishra, A. K., & Park, T. A. (2005). An empirical analysis of internet use by U.S. farmers. Agricultural and Resource Economics Review, 34(2), 253–264.
25.
Mishra, A. K., Williams, R. P., & Detre, J. D. (2009). Internet access and internet purchasing patterns of farm households. Agricultural and Resource Economics Review, 38(2), 240–257.
26.
Mishra, A., Morehart, M., El-Osta, H., Johnson, J., & Hopkins, J. (2002). Income, wealth, and well-being of farm operator households. Washington, DC: Agricultural Economics Report No. 812, U.S. Department of Agriculture, Economic Research Service.
27.
Mishra, A. K., El-Osta, H. S., & Steele, C. J. (1999). Factors affecting the profitability of limited resource and other small farms. Agricultural Finance Review, 59(6), 77–91.
28.
Narayanasamy, K., Rasiah, D., & Tan, T. M. (2011). The adoption and concerns of e-finance in Malaysia. Electronic Commerce Research, 11(4), 383–400.CrossRef
29.
Obiri-Yeboah, K., Owusu-Ansah, W., & Odei-Lartey, E.O. (2013). Factors that drive internet usage among small and medium scale enterprises: evidence from Ghana. International Journal of Management & Marketing Research, 6(2).
30.
Putler, D. S., & Zilberman, D. (1988). Computer use in agriculture: Evidence from Tulare County, California. American Journal of Agricultural Economics, 70(4), 790–802.CrossRef
31.
Robison, L., & Barry, P. (1987). The competitive firm’s response to risk. New York: McMillian Publishing Company.
32.
Rosston, G., Savage, S., & Waldman, D. (2011). Household demand for broadband Internet service. Communications of the ACM, 54(2), 29–31.CrossRef
33.
Savage, S. J., & Waldman, D. M. (2009). Ability, location, and household demand for internet bandwidth. International Journal of Industrial Organization, 27, 166–174.CrossRef
34.
35.
Sila, I. (2013). Factors affecting the adoption of B2B e-commerce technologies. Electronic Commerce Research, 13(2), 199–236.CrossRef
36.
Solaymani, S., Sohaili, K., & Yazdinejad, E. A. (2012). Adoption and use of e-commerce in SMEs. Electronic Commerce Research, 12(3), 249–263.CrossRef
37.
Stenberg, P., Morehart, M., Vogel, S., Cromarti, J., Breneman, V., & Brown, D. (2009). Broadband Internet’s value for rural America. Research report no.: 78. Washington, DC: Economic Research Service, U.S. Department of Agriculture.
38.
Strempel, D. (2002). Small businesses expecting growth despite economy. Fairfield County Business Journal, 41(48), 2.
39.
40.
Uematsu, H., & Mishra, A. K. (2012). Organic farmers or conventional farmers: Where’s the money? Ecological Economics, 78, 55–62.CrossRef
41.
Warren, M. (2004). Farmers online: Drivers and impediments in adoption of Internet in UK agricultural business. Journal of Small Business and Enterprise Development, 11(3), 371–381.CrossRef
42.
Wooldridge, J. M. (2002). Econometric analysis of cross-section and panel data (1st ed.). Cambridge, MA: The MIT Press.
Metadata
Title
Access to the Internet and financial performance of small business households
Authors
Aditya R. Khanal
Ashok K. Mishra
Krishna H. Koirala
Publication date
01-06-2015
Publisher
Springer US
Published in
Electronic Commerce Research / Issue 2/2015
Print ISSN: 1389-5753
Electronic ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-015-9178-3

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