Study Design

3.6.1 Measuring Psychic Distance

Two measures will be used to determine the psychic distance between New Zealand and the 25 selected markets. Initially the index developed by Brewer will be used to provide an indicator of distance using an objective method. Secondly, Dow’s (2000) methodology will be used to determine a perception based response from the expert panel on the psychic distance between New Zealand and the selected group of countries. Table 7 specifies the indicators constructed by Brewer (2007a) that will be used to gauge psychic distance between New Zealand and the 25 selected export markets. Data was obtained from various sources and collated into tables to provide an objective measure of distance for each indicator. The individual measures are then aggregated to produce an overall measure of psychic distance2.

Table 7: Psychic Distance Index: Replication of Brewer’s Study (2007a)

Primary Indicators Item Measures Data Type Data Source

Commercial Ties 1. Two Way Trade Variable Statistics NZ

2. Stock of Foreign Investment Variable Statistics NZ

Political Ties 3. Trade Arrangements Variable Statistics NZ

4. Value of Aid Programmes Variable MFAT 5. Trade Representation Offices Variable NZTE/MFAT

Historic Ties 6. Colonial Relationship Fixed Historical

7. Shared Wars Fixed Historical

Geographic Ties 8. Geographic Proximity Fixed World Atlas/Google

Social Ties 9. Cultural Similarities Fixed Fletcher & Bohn (1998)

10. Sport Preferences Fixed Top 4 H&A sports 11. Language Similarities Fixed Direct comparison

Country Information Stock 12. Secondary Information Availability Variable Massey University

13. Immigration Numbers Variable Statistics NZ

Level of Development 14. Level of Development of the Foreign Country Variable WTO Stats

15. Level of Corruption of the Foreign Country Variable TPI

2 _{Cultural Distance measures were also used as a benchmark in comparing Hofstede’s model for New} Zealand and each of the 25 countries (see Section 9.1). It was noted that many of the researchers have used scales based on Sethi’s (1971) clustering of world markets or Hofstede’s (1980) cultural difference dimensions as surrogate indicators.

69 Dow (2000) used a background in studies employing key informant based scales as a means of justification for the group of Trade Commissioners used in the gathering of information (i.e. Single- item instrument: applied to an independent panel as used by (Vahlne & Nordstrom, 1992). The distance between countries was estimated with a single-item scale administered to the independent panel of trade commissioners. Each of the participants was given a description of psychological distance adapted from Carlson’s (1974), Johanson and Weidersheim-Paul’s (1975) and Johanson and Vahlne’s (1977) work and were asked to rate on a ten point scale the psychological distance from Australia of 25 countries. The questionnaires were completed independently. This study will use the same methodology through interviewing NZTE personnel based in New Zealand with a focus on the F&B Sector.

3.6.2 Measuring Export Stimulation

Table 8 summarises the export stimuli categories from Leonidou (1998). This table formed the basis of assessment into the stimulating factors that are driving New Zealand F&B SMEs to export. As discovered in Section 2 it is anticipated that many SMEs initiate exporting in a reactive manner and

this in turn will influence the methods they use for sourcing and selecting channel partners – particularly in emerging markets. Data from interviews with the expert panel was collected through a request to rate the three most common forms of export stimulation that they witnessed for the New Zealand F&B SMEs based on their experiences. The relevant data was collected in table 29. The

interviewees were also asked to provide comments on the major stimulating factors. The responses

70 Table 8: Internal& External Stimuli Categorised (Leonidou , 1998)

Internal Stimuli

Proactive Achievement of economies of scale

Special managerial interest/urge/aspirations Products with unique qualities

Possession of a special competitive advantage Potential for extra sales/profits

Need to achieve corporate growth

Reactive Offsetting sales of a seasonal product

Utilisation of idle operating capacity Stagnation/decline in domestic sales/profits Reducing dependence on/risk of domestic business

External Stimuli

Proactive Encouragement by external agents/organizations

Identification of attractive foreign opportunities Exclusive information on foreign markets Government export assistance/incentives Contacts after participating in trade fairs/missions

Reactive Initiation of exports by domestic competitors

Competitive pressures in the domestic market Favourable foreign exchange rates

Saturation/shrinkage of domestic market Receipt of unsolicited orders from abroad

3.6.3 Determining Perceived Initiation Methods of Channel Partner Relationships

The method of measuring channel partner relationship initiations also includes perception based responses from the expert panel. Each panel member was asked to rate the proportion of firms in their respective markets who had commenced new channel partnerships via one of five methods as identified by Ellis (2000). A summary of the number of F&B SMEs exporting to the market was provided and the interviewee estimated the percentage of initiations under each of the five headings based on their experiences in their own market as well as that of markets within the region they operated in (e.g. Oceania, Asia, North America). The data will be collected in a tabulated format as per the example in Table 9. A weighted formula is used to establish the level of proactive behaviour from the seller’s perspective.

71 Table 9: Exchange Partner Initiation (Ellis & Pecotich, Social Factors Influencing Export Initiation in Small and Medium-Sized Enterprises, 2001a) – example table:

Export Market # of F&B SMEs Seller Initiated Buyer Initiated Social Ties &Networks Third Party Initiated

Trade Fair TOTAL

Australia 526 x% x% x% x% x% 100% China 310 x% x% x% x% x% 100% Taiwan 170 x% x% x% x% x% 100% Hong Kong 360 x% x% x% x% x% 100% India 70 x% x% x% x% x% 100% Singapore 320 x% x% x% x% x% 100% Malaysia 180 x% x% x% x% x% 100% Indonesia 80 x% x% x% x% x% 100%

3.7 Method of Data Collection