Implicaciones de la cultura en el proceso de

Data was collected using a survey in the form of an electronic questionnaire delivered via email. Surveys collect information about the same variables from a number of cases resulting in a variable by case matrix or a structured data matrix (de Vaus, 1995, p. 3). The production of a data matrix is central to data analysis which is based on the comparison of cases (de Vaus, 1995, p. 5).

Questionnaires ensure this structured data matrix and are a commonly used technique in survey research (de Vaus, 1995, p. 5; Punch, 2005, p. 75).

Internet based or email surveys can offer large cost and time efficiencies when compared with postal surveys through the near elimination of paper, postage and data entry costs (Dillman, 2007, p. 352). Greater time efficiencies in survey design, implementation and the processing of survey data are also an attractive feature of electronic surveys. Some disadvantages of email based surveys include internet connection/access, deliverability (accurate email addresses and spam filters), computer literacy and online survey fatigue (relentless requests to participate in online surveys), which may lead to reduced response rates (Dillman, 2007; Ilieva, Baron, & Healy, 2002; Pecoraro, 2012). In general, response to email surveys is in the 5-10 per cent range (Semler, 2010, p. 1).

3.4.1

Farmer questionnaire background

The survey was conducted with the help of the Department of Agricultural Management and Property Studies at Lincoln University and was funded by the SIDDC with a postgraduate student summer scholarship. The online questionnaire was to determine the socio-demographics, farm characteristics and ISCs of Canterbury dairy farmers, and to assess the level of adoption of ten innovations that had been trialled by the LUDF between 2001 and 2012. Data was also collected on additional topics of interest to the SIDDC, for example farmers’ suggestions regarding future research for the SIDDC. This data was not relevant to this study and a result has been excluded.

Qualtrics, a secure online survey software application available through Lincoln University was used in the design, distribution and preliminary evaluation of the electronic questionnaire. Qualtrics provides rigorous privacy standards with account password protection and real-time data replication (Qualtrics.com, 2012). Pangborn’s (2009) postal questionnaire was used as a template in the design

from SIDDC and Lincoln University, the questionnaire was tested on a trial group of individuals involved in dairy farming, agricultural extension, and research. Suggestions from this group as to question content and survey format were included in the final questionnaire. The questionnaire was submitted for review and approval by the Lincoln University Human Ethics Committee, with approval granted on 28/11/2012 (application number 2012-46, Appendix A, page 121).

3.4.2

Questionnaire format and content

The electronic questionnaire consisted of three sections. Section one gathered quantitative data on farmer and farm characteristics which included the position of the person answering questions, highest level of formal education, gender, age, dairy farming experience, if they had a

financial/managerial interest in more than one dairy farm, farm size (effective ha), production per cow and per effective ha (kg of milksolids (MS) to the factory), farming system (as defined by DairyNZ), pre-dominant breed of dairy cow, replacement dairy stock management and farmer opinion on standoff facilities/partial housing for livestock.

Section two collected quantitative data on attendance at industry extension events and reasons for attendance at these events, and asked farmers to rank sources of information used for learning about LUDF results, and new agricultural technology and innovations. Section two also asked farmers to indicate their adoption or rejection of ten FMP innovations practiced by the LUDF and briefly comment on their decisions. These FMP innovations included low and consistent grazing residuals, re-grassing based on measurement of poor performing paddocks, synchronising of heifers to calve two weeks before the herd, zero induction policy, use of Eco-n, monitoring of soil moisture to drive irrigation practice, regular monitoring of cow condition to facilitate alternative management, creating a separate herd of young cows to facilitate alternative management, use of nitrogen fertiliser and gibberellic acid simultaneously to promote dry matter production and pre-graze mowing to increase animal intakes. A description of these FMP innovations is provided in Chapter 4, section 4.4.2.

The final part of the questionnaire, section three, contains questions on the farmer’s use of a private consultant/advisor, the services provided by their consultant and how information is received from their consultant. Farmers were also asked to indicate the degree of difficulty experienced when obtaining relevant industry information on a number of topics. The final question regarded planned changes to farm infrastructure to accommodate environmental concerns and asked farmers to comment on what these changes might be.

3.4.3

Sample selection

The primary objective of this research was to determine how Canterbury dairy farmer, dairy farm and farmer information seeking characteristics influence the adoption/rejection of a range of FMP innovations. To achieve this, the survey sample should include every person responsible for production/management decision-making on Canterbury dairy farms. However, the availability of reliable and current farmer contact details ultimately influenced sample selection. For this research, the farmer email contact list used to distribute the electronic survey was supplied by the Canterbury Dairy Effluent Group (CDEG) and consisted of dairy effluent discharge consent holders. The

Canterbury Dairy Effluent Group includes AgITO, DairyNZ, Environment Canterbury, Federated Farmers, Fonterra, NZ Dairies, SIDDC, Synlait and Westland Milk Products (Beck, 2012).

Dairy effluent discharge consents require a detailed knowledge of the dairy production system and of the land on which dairy effluent is to be discharged, as evidenced by the consent application form (see Environment Canterbury, 2013). The discharge consent holders are responsible for compliance with consent conditions and are typically land owner(s) but may also be lessees or the occupier of the land. Non-compliance with the conditions specified in the consent can result in the issuing of infringement notices, abatement notices and/or prosecution by the Canterbury Regional Council (Beck, 2012). Therefore, it is assumed that the dairy effluent consent holder will occupy a position of authority and/or high responsibly on-farm and as a result, will also be intimately involved in on-farm decision making.

The CDEG contact list contained the contact information for 1012 dairy effluent discharge consent holders identified by a unique consent identification number. After duplicate email addresses (i.e. same email address associated with more than one discharge consent number) and contacts which had no or an invalid email address were removed, the final list contained 647 dairy farmer email addresses (64 per cent of the population).

3.4.4

Distribution of the electronic questionnaire

The survey was emailed to the 647 farmer email addresses on the 12th December 2012. A reminder to participate in the survey was distributed on the 21st December 2012 with a second reminder distributed on 15th January 2013. This is in line with research which suggests multiple contacts may help increase online survey response rates (Dillman, 2007; Kaplowitz, Lupi, Couper, & Thorp, 2012). The opportunity to win a choice of two prizes (an iPad or two free registrations to the SIDE 2013 conference) was also used to incentivise participation. A total of 144 surveys were returned by 15th February 2013 giving a response rate of 22 per cent.