Information Technology Adoption: Implications for ... - CiteSeerX

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Information technologies afford the agriculture industry the opportunity to increase information flow to all industry participants at a decreased cost. Identifying the ...
Tammy Kurtenbach1 Sarahelen Thompson

Information Technology Adoption: Implications for Agriculture Abstract Agriculture constantly experiences advances in technology. Recently, the use of information technologies (IT), such as e-mail and the World Wide Web, has become commonplace. Information technologies afford the agriculture industry the opportunity to increase information flow to all industry participants at a decreased cost. Identifying the factors associated with IT adoption and use in agriculture will allow the industry, especially managers, to increase information flow and increase the demand for a firm’s products and services, while increasing the level of trust in the firm. This research contributes to the understanding of these factors by analyzing IT use in state soybean producer organizations. Continuous dependent variables were developed using a scoring system and were used in regression models to identify the factors most significantly influencing IT use. Results show that an individuals access to IT, level of training, IT knowledge, and trust level all have a positive influence on IT adoption. Managers can use these results to increase training and trust levels of their employees as well as their customers.

Introduction Accurate and complete information is vital to all market sectors and industries including agriculture. Information promotes competition and improves market performance (Thompson and Sonka). At the firm level, information promotes the efficiency and effectiveness of production and customer service. Information may also increase the level of trust consumers have in a product or firm leading to increased demand.

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Tammy Kurtenbach, Teaching Associate, and Sarahelen Thompson, Professor, are both in the Department of Agricultural and Consumer Economics at the University of Illinois at Urbana-Champaign.

It is readily accepted that increased information flow has a positive effect on the agricultural sector and individual firms. However, collecting and disseminating information is often difficult and costly. Information technologies (IT) offer the ability to increase the amount of information provided to all participants in the agricultural sector and to decrease the cost of disseminating the information. Research and literature already conducted regarding IT and the food and agribusiness industry have predominately focused on the effects that IT will have on the industry (Cragg). Fewer works can be found that attempt to understand the factors that cause the adoption and use of IT in agricultural organizations. Therefore, the need exists to understand why some agricultural industry participants adopt use of IT faster and more readily than others. An understanding of the factors associated with IT adoption and use in agriculture will enable the development of strategies to promote IT adoption and increase the effectiveness and efficiency of information use in agriculture. Objective The objective of this research is to contribute to the understanding of the adoption and use of information technology (IT) over time in agricultural organizations. More specifically, the research focuses on identifying the reasons why some individuals in agricultural service organizations use IT more than other individuals. It is hypothesized that multiple factors are associated with IT use. These factors include, among others, user knowledge of IT, trust level in the IT system, and access to IT. Procedures State soybean producer organizations served as the observation group used in this research to identify factors that influence IT adoption and use in agriculture. This study began in 1996 with personal interviews of state association employees that were then used to identify

important user and organizational characteristics and current applications of IT in the state offices. The results from the interviews, input from the technical staff of StratSoy, and academic literature were used as the basis for structuring the final mail survey. The final survey was sent to the state association offices twice over a period of two years and contained questions regarding World Wide Web (WWW) use, e-mail use, and user comfort level with these technologies. This research work was conducted as part of the larger project, StratSoy (http://www.ag.uiuc.edu/stratsoy.html), an electronic and communication system sponsored by the United Soybean Board (USB) and developed by the University of Illinois at UrbanaChampaign. StratSoy has played the role of the diffusion mechanism of information technologies to the state soybean offices by providing education, training, and support for IT users. The surveys were analyzed with statistical and regression methods to identify factors most closely associated with IT adoption and use. A continuous index variable was created for the dependent variables, e-mail and WWW use, and the categorical explanatory variables were dichotomized. In previous studies, such as the one conducted by Batte, et al., adoption of a technology is measured as a dummy variable: a one is assigned if the user adopted the technology and a zero is assigned if the user did not adopt the technology. The continuous dependent variables created by this research allow for the degree of adoption to be studied and not just whether or not the technology was adopted. A scoring system was applied to a selection of the survey questions to create EINDEX and WINDEX to represent e-mail and WWW use respectively. The method of creating a scored index from categorical data has been used previously in research works (Westgren et al.,

Fredrickson, and Fredrickson and Mitchell). EINDEX and WINDEX were computed by applying scores to the responses for each of the following questions: E-mail Use = EINDEX Send and check e-mail More than once a day Daily Every few days Once a week Rarely Never

100 75 50 25 10 0

Receive e-mail Daily Every few days Once a week Rarely Never

100 75 50 25 0

Number of e-mail received Sometimes don’t get any 1-4 5-10 11 and above

0 25 75 100

Frequency of receiving and sending attachments Never Very rarely Occasionally Frequently

0 25 75 100

Number of attachments received and sent Less than 1 per week 1-3 4-6 7-9 10 and above

0 25 50 75 100

These questions form eight variables whose scores were summed and then divided by eight to obtain the average score EINDEX.

Web Use = WINDEX I use the Internet: More than once a day Daily Every few days Once a week Rarely Never

100 75 50 25 10 0

Have you been involved in the creation or maintenance of material for a homepage? Do you know, or use any HTML? Do you do any shopping/purchasing via the Internet? Yes 100 No 0 These questions form four variables and the scores for each variable were summed and then divided by four to obtain the average score WINDEX. Regressions were run using these two use indices as dependent variables to determine which factors from the survey had the greatest impact on WWW and e-mail adoption and use. For EINDEX in the 1997 survey, the following variables were found to be significant in influencing IT adoption and use with the signs of the coefficients indicated in parentheses: •

E-mail is helpful for work related communication (+)



Individual worked in a very small office (-)



Individual can solve IT related problems alone or with help (+)



Days of training (+)



More than 75% of his/her job in marketing (+)

For WINDEX, the following variables were significant in relation to IT adoption and use in the 1997 survey: •

Using the Internet is easy (+)



Days of training (+)



More than 75% of his/her job in marketing (+)



Do job related work at home (+)



Individual worked in a very small office (-)

This paper focuses on the results and implications of the 1997 survey combined with the second mail survey conducted in 1998. It evaluates the significance of those factors that emerged as most important in the 1997 survey and identifies new variables that over time influenced IT adoption. Particular attention is given to factors associated with a user’s level of trust in IT as well as those factors that may promote trust such as training and access to user support services. Theory, previous survey results, and initial regression testing were used to determine which of the survey variables are most significant in influencing IT adoption. Theoretical Background Two fundamental steps exist in establishing an innovation as a valuable, readily used tool: diffusion and adoption. Both diffusion and adoption must occur in order for an innovation to successfully reach its target user and be implemented (Mahajan, et al.). First, diffusion, the process by which an innovation “is communicated through certain channels over time among the members of a social system” (Rogers), must occur. In this study, the StratSoy project was a major factor in the IT diffusion process in state soybean organizations. Other factors that influenced diffusion included the media, word-of-mouth, and experiences of friends, associates and family members. In addition to individuals having access to a new technology, adoption must also occur, which means individuals accept the innovation as valuable and use it. Numerous factors could influence IT adoption and use in agricultural organizations and can be grouped into five categories: access to IT, demographic, IT training/education, trust, and time. It is possible for adoption factors to fit into more than one category.

In the case of IT, access to the technology means an individual must have access to a computer equipped with IT such as e-mail and access to the WWW. The category “access to IT” would not only include the use of a computer with IT ability, but would also include the ability to upgrade computer hardware and software to facilitate IT use. The price of needed computer equipment and the expense of Internet use are also related to access to IT. It is predicted that the higher the level of access to IT, the higher the level of IT use by an individual. The demographic category includes adoption factors such as age, education level, gender, and income level. It is hypothesized that factors in the demographic category will not significantly influence IT adoption and use. Although previous literature suggests that IT use will be higher for younger, more educated individuals (Batte, et al.), 1997 survey results suggest that demographic factors have little influence on IT adoption and use. This may reflect that demographic factors may influence the decision to adopt a new technology, but once that decision to adopt is made, demographic factors may have little influence on use. Another category of IT adoption factors is IT training/knowledge. This IT adoption factor can be measured with variables such as type of IT training, days of IT training, and the level of knowledge on IT use. It is hypothesized that as the quality and level of IT training increases, the use of IT will also likely increase. An important factor influencing the adoption of any new technology is an individual's perception of that technology. It is hypothesized by this research that one of the key perception aspects influencing the adoption of IT is the level of trust that the potential adopter has in the IT system and in those who use IT. Trust can be defined as “an individual’s optimistic expectation about the outcome of an event” (Hosmer 1995). There are different aspects of trust related to IT. An individual must first trust that information technologies will work and that IT will be

beneficial in accomplishing his/her goals and in completing his/her tasks. An individual must also trust that the information they obtain via IT is accurate and the information they send via IT will not be tampered with and privacy levels will be maintained. Trust proves to be a difficult variable to measure. Factors included in the trust category include an individual’s perception of the ease of use of IT as well as the benefit of IT. In this study, trust is measured by variables such as helpfulness of IT for work-related communication, problem solving ability, and banking and shopping via the Internet. Some individuals, either due to their background or current environment, have a fear of IT and feel that it is difficult to use. It is hypothesized that an individual will use IT more if they have a positive perception or high trust level in IT. The final IT adoption category proposed by this research is the passage of time. It is hypothesized that individuals will increase their use of IT over time, as access to IT becomes more commonplace. In this study, the same group of people were surveyed twice to evaluate their changes in IT use over time. Time was measured by establishing a dummy variable where each survey response from the 1997 survey was assigned a value of zero and each survey response from 1998 was assigned a value of one. Time-interaction variables were also created for each variable by multiplying the original variable by the time variable. For example, the “days of training” variable (tdays) was multiplied by the time variable and became the “timeinfluenced days of training” variable (tdayst). The diffusion and adoption categories discussed above and the survey questions that pertain to these factors are summarized in table 1.

Table 1: Hypothesized Factors Influencing IT Adoption/Use and Related Survey Questions FACTORS of IT ADOPTION and USE in CATEGORIES RELATED SURVEY QUESTIONS Access to IT Ø Do you share a computer with others at work? Ø Average hours spent on a computer each day. Ø Do you have a computer at home? Ø Do you do job related work at home? Ø Size of office. (The state soybean offices were divided into size categories based on state production levels and number of staff.) Demographic

Ø Ø Ø

IT Training/ Knowledge

Ø

Trust

Ø Ø Ø Ø

Age. Gender. Education Level.

Have you participated in any hands-on Internet and/or e-mail training sessions? Ø Total number of days of IT training. Ø Do you know html? How helpful is e-mail for work related communication? How easy is it to use the Internet/e-mail? Can you solve IT related problems yourself or with help? Do you do any banking via the Internet? Ø 1997 Survey vs. 1998 Survey. Ø All of the time influenced variables i.e. days of training x time.

Time Results

Using both theory and stepwise regression results, the following variables were identified as providing the greatest explanatory power with respect to WWW and e-mail use: WINDEX IT Training/Knowledge • Days of Training Trust •

Send e-mail attachments



Using the Internet is easy



Solve IT related problems myself or with help

EINDEX Access to IT •

Sharing computer at work



Trust

Average hours spent on computer



each day •

Very small office



Time influenced do job related work

communication •

Solve IT related problems myself or with help

at home •

E-mail is helpful for work related

Percentage work related e-mail

IT Training/Knowledge •

Know html

EINDEX = f(cshare, hours, vsmall, hworkt, wemail, html, emhelps, probsol) WINDEX = f(tdays, sattach, intez, probsol)

The estimated regression equations for both the EINDEX and WINDEX models are presented in table 2.

Table 2: Regression Equations for EINDEX and WINDEX for the Combined Data Set that Identify New Significant Variables Variables Intercept Using the Internet is easy (intez) Days of Training (tdays) Send e-mail attachments (sattach) Know html (html) Sharing computer at work (cshare) Average hours spent on computer each day (hours) Time-influenced do job related work at home (hworkt)

EINDEX Coefficients -2.339

T -0.299

% Sig. 0.765

12.741 -15.136

3.397 -3.244

0.001 0.002

2.597

4.024

0.000

12.074

3.740

0.000

WINDEX Coefficients -18.430 15.524

t -1.939 2.222

% Sig. 0.056 0.029

3.886 7.211

3.312 3.674

0.001 0.000

Very small office (vsmall) E-mail is helpful for work related communication (emhelps) Percentage work related email (wemail) Solve IT related problems myself or with help (probsol) R2 Adjusted R2 F (degrees of freedom)

-6.119 9.064

-1.421 1.399

0.159 0.166

0.175

3.467

0.001

14.614

2.299

0.024

0.612 0.574 15.793 (8, 80)

0.000

15.681

1.802

0.357 0.326 11.644 (4, 84)

0.075

0.000

Just as important as identifying the factors that influence IT adoption and use is understanding the implications of these factors. All of the independent variables used in the final models impact IT use and adoption as originally hypothesized. In the category of access to IT, both sharing a computer at work and working in a very small office have a negative impact on EINDEX. If the individual has to share a computer, they obviously do not have as much time or privacy to use information technologies. A very small office may not have the resources needed to remain current with computer upgrades needed to use IT effectively. Thus, individuals working in these small offices may not even have much opportunity or time to use e-mail or the WWW. Individuals who have greater access to IT would include those who have a high number of “average hours spent on the computer each day” and who do job related work at home. These variables have a positive impact on IT usage. As hypothesized, no variables in the demographic category were significant in influencing IT use in agricultural organizations. It is possible that these results reflect that demographic factors may influence adoption more than use. Variables related to the IT training/knowledge category were found to be significant. “Days of training” and “know html” have significant, positive coefficients indicating people with more days of training and html

knowledge use IT more. These results support the original hypotheses that IT training and knowledge promote the adoption of information technology. Several trust variables, “e-mail is helpful for work related communication,” “using the Internet is easy” and “Solve IT related problems myself or with help,” emerged as being significant in influencing IT usage. All of these variables had significant, positive coefficients indicating the more trust an individual has in the IT systems, the more the individual will use IT. Finally, the only time-related variable that was significant in influencing IT use was the “time-influenced do job related work at home” variable which has a positive effect on e-mail use. The significance of this variable on EINDEX implies that individuals use e-mail more when they are physically separated from work as in the case of traveling or telecommuting. IT use appears to increase as there are more contexts or settings to use IT. For example, if an individual begins to use IT at home, they will more than likely use the technologies at work and vice versa. Forum Discussion The implications of this research for adoption of information technology in agriculture was an area of interest among forum participants. Discussion focused on the finding that demographic factors do not seem to influence use of information technology as much as they may influence adoption. A factor such as age may not influence use once the adoption decision is made. Due in part to the use of continuous dependent variables in the analysis, this research points to the importance of distinguishing between adoption and use decisions in future research. Managerial Implications Identifying the determinants of IT adoption and use will help industry participants, especially managers, use information technologies to increase information flow and increase the level of trust in the firm and the demand for the firm’s products or services. For example, if a

livestock company promotes the use of IT to its producers, it will open up more efficient means of communicating product information and providing other services to its customers. As consumers increase their use of IT, firms will be able to communicate more effectively with them, and demand for the firm’s product may increase. Determining the factors that influence IT adoption can assist companies in determining the IT use profile of their customers based on the significant adoption factors identified in this study. Knowledge of the factors that influence IT adoption can also help companies target individuals, who due to their progressiveness and use of IT, may be potential customers of the company’s products and/or services. The company can then focus marketing and advertising campaigns on attracting these individuals to their business. This research is also important because IT can possibly substitute for trust with an organization just as trust often substitutes for contracts. A customer’s comfort and trust level with a company may increase as they are able to gain more information about a company via IT. For example, a customer’s trust level with a company will increase if he is able to track his shipment order via the Internet. In addition to the general managerial implications of identifying IT adoption factors, this research also suggests specific ways in which a manager can promote IT adoption that can lead to more efficient communication and increased demand for the firm's products and services. First, the research shows that IT training increases IT adoption and use. Therefore, firms may benefit from providing training on information technologies for both employees as well as customers. Second, managers should proactively use IT to promote the trust their employees, customers, and other business associates have in IT, and thus increase the overall use of IT. The positive coefficient on the variable "e-mail is helpful for work related communication" suggests

that the more those with whom you communicate use e-mail, the more helpful e-mail is in communicating with them. An agricultural producer might consider using e-mail to communicate with the firm because she observes that her well-respected chemical sales representative uses IT successfully. This research also suggests that an individual’s use of IT is greater when the individual’s access to IT is not restricted. Therefore, managers may want to provide greater access to IT by providing each employee his or her own computer hardware equipped with Internet capabilities. The employees will be free to use IT at their convenience and will be less concerned with privacy or security problems related to sharing a computer. Managers should promote the use of IT in all aspects of employees' and customers' personal lives and work. The significance of the variable "time-influenced do job related work at home" indicates that employees use e-mail more when they are physically separated from work. The implication for managers is that IT use is greater when people work outside the office, or have flexible work relationships such as telecommuting. Increasingly, individuals will turn to IT when they need information or to communicate with the firm for personal or work-related reasons. Certainly many individuals and organizations within society at large still have a fear or mistrust of IT. At the same time, agriculture constantly experiences advances in technology and the use of information technologies is becoming more common place each day. Therefore, it is essential for firms and managers to understand the reasons for IT adoption to remain competitive and to best serve their industry and customers.

REFERENCES Batte, Marvin T., Eugene Jones, and Gary D. Schnitkey. 1990. “Computer Use by Ohio Commercial Farmers.” American Journal of Agricultural Economics, 72:935-45. Cragg, Paul. “Adoption of the Internet by Small Firms.” http://www.scu.edu.au/sponsored/ausweb/ausweb96/business/cragg/ Fredrickson, J. W. 1984. “The Comprehensiveness of Strategic Decision Process: Extension, Observations, Future Directions.” Academy of Management Journal, 27:445-466. Fredrickson, J. W. and T. R. Mitchell. 1984. “Strategic Decision Process: Comprehensiveness and Performance in an Industry with an Unstable Environment.” Academy of Management Journal, 27:399-423. Hosmer, LaRue Tone. 1995. “Trust: The Connecting Link Between Organizational Theory and Philosophical Ethics.” Academy of Management Review, 20:379-403. Mahajan, Vijay, Eitan Muller and Frank M. Bass. 1990. “New Product Diffusion Models in Marketing: A Review and Directions for Research.” Journal of Marketing, 54:1-26. Rogers, Everett M. 1995. Diffusion of Innovations – 4th Edition, New York: The Free Press. Thompson, Sarahelen and Steven T. Sonka. 1997. “Potential Effects of Information Technologies on the Economic Performance of Agricultural and Food Markets.” American Journal of Agricultural Economics,1997:657-662. Westgren, Randall E., Steven T. Sonka, and Gunta S. Vitins. 1993. “The Comprehensiveness of Strategic Decision Making and Its Relationship to Business Unit Performance.” Competitive Strategy Analysis in the Food System. Boulder: Westview Press, Inc.