Case Definition and Sample Selection

The importance of defining and bounding the case is a crucial component in any research design (Miles & Huberman, 1994; Yin, 2003). In this study, each case was defined as a decision of arts sponsorship between a company and a non-profit arts organisation. As noted, all cases involved decisions which were in favour of engaging in the sponsorship.

The cases were bounded in terms of time, by the start of the decision (asking informants when the process began), to the time just following the decision by the company to make

6 Narayandas and Rangan (2004) used clinical field research over one year, to investigate buyer-seller relationships in mature industrial markets; they used a purposive sample of three dyads; within each relationship 5 - 18 managers were interviewed. Drumwright (1994) considered socially responsible buying (environmental concerns), and used an embedded multiple-case research design; the purposive sample included 10 organisations, with 21 buying processes studied in depth via 40 individuals interviewed. Gilly and Wolfinbarger (1998), in a grounded theory approach, studied 4 organisations within their purposive sample through group depth interviews (in total interviewing 40 individuals).

78

an investment. The unit of analysis within each case was the group of individuals involved in the decision, who agreed to be interviewed.

The case definition proposed here, first relates to the fundamental research question:

How do companies make arts sponsorship decisions? As Yin (2003) points out, “each case study and unit of analysis either should be similar to those previously studied by others or should innovate in clear, operationally defined ways” (p.26). This case and unit of analysis is similar to that proposed in organizational buying behaviour, but offers a point of difference to existing CCI literature.

In an early OBB paper, Wind and Thomas (1980) note the importance of selecting an appropriate unit of analysis, and propose that using an individual respondent is not enough:

The central sampling problem in research on organisational buying behaviour is the inability to select an individual respondent as an independent unit. It is necessary to select the individual in reference to the organisational structure.” (p.257)

There appears to be general agreement in OBB that single-informant studies are a

sampling concern and studies should ideally use multiple informants (Bunn, 1993; Silk &

Kalwani, 1982). Furthermore, a number of studies in OBB are noted as having used multiple informants (Drumwright, 1994; Ghingold & Wilson, 1998; Narayandas &

Rangan, 2004; Park & Stoel, 2005). The case and unit of analysis definition here is viewed as similar to and following on from these studies.

In the CCI literature also, the use of multiple informants is not common, with reliance on single informants recognised as a limitation. Philanthropy literature is also more oriented to single-informant studies and the use of existing databases (Brammer & Millington, 2004b; Dunn, 2004; Navarro, 1986; Wang & Coffey, 1992). In sponsorship there are more multiple informant studies, especially in research considering the relationship aspect of sponsorship (Farrelly & Quester, 2003a; Farrelly, Quester, & Smolianov, 1998;

Ryan & Fahy, 2003). However the identification of these informants has not obviously employed a snowballing technique nor linked the informants with the roles they undertake in a decision.

79 4.3.1 Case Selection

Two key questions determined the design with respect to case selection: the question of whether a single-case or multiple-case study should be employed, and the question of which cases to select.

In this study, multiple-case sampling was chosen over single case. The reasons for this relate to the research question and the desire to find a variety of processes which

companies undergo. This could only be achieved through investigation into a number of relationships. Multiple-case sampling is also chosen in order to strengthen the study, providing greater confidence, reliability and stability in the findings (Miles & Huberman, 1994; Yin, 2003).

In qualitative theory-building studies, authors are in agreement that the selection of cases should not be random, but purposive, and should consider following a replication logic whereby cases are “likely to replicate or extend the emergent theory” (Eisenhardt, 1989, p. 537). Yin (2003) proposes a replication logic whereby each case is selected “so that it either (a) predicts similar results (a literal replication) or (b) predicts contrasting results but for predictable reasons (a theoretical replication)” (p.47). Following this method, as Eisenhardt and Graebner (2007) note, the case study is like a laboratory experiment:

just as laboratory experiments are not randomly sampled from a population of experiments, but rather, chosen for the likelihood that they will offer theoretical insight, so too are cases sampled for theoretical reasons, such as revelation of an unusual phenomenon, replication of findings from other cases, contrary replication, elimination of alternative explanations, and elaboration of the emergent theory (p.27).

Yin goes on to note that achieving both literal and theoretical replication is the ideal situation. Therefore, cases were sought out which met certain criteria (a criterion

sampling strategy (Miles & Huberman, 1994)), which replicated findings within a group, and/or presented contrasting findings across groups.

80

To guide this strategy, the CCI and OBB literature offered potential directions.

Specifically, it has been noted that there are factors which are likely to influence the giving levels of the firm, including the industry (Brammer & Millington, 2004b; Seifert et al., 2004), the buyclass – or specifically whether it is a “rebuy” or a new buy

(Anderson et al., 1987), and the ownership of a firm (Atkinson & Galaskiewicz, 1988).

Cases were therefore sought in a number of industries; for both new and renewal situations, and for variation in ownership on the sponsoring company side of the equation.

Some characteristics were also sought in terms of the arts organisations studied. Similar to countries around the world, there are a variety of arts organisations in New Zealand.

Some are professional, some are more community-based; some operate on a for-profit basis, while most operate as not-for-profits. Within not-for-profits there are also a range of funding levels, with some organisations receiving a large proportion of funding from the government, others from the private sector and others from audience support. In addition there are a range of genres of arts, including theatre, opera, orchestras, music ensemble groups, popular bands, visual arts, dance as well as festivals (be they multi-arts festivals or a single genre festival). As noted, the cases included in this study were all with not-for-profit companies, who actively seek sponsorship; in addition, some variety of genre was sought.

With this strategy, it is also possible to turn to other questions to guide further case selection. Such additional questions included whether decisions were similar within a single company (hence multiple decisions within two companies are present), or similar as related to a single arts organisation (hence multiple decisions surrounding two arts organisations are present).

To identify cases, a purposive sampling strategy using expert informants and snowballing or chain sampling was employed. Expert informants were used to identify information rich cases (Miles & Huberman, 1994). As cases were studied, additional cases were selected according to the criteria noted above and replication logic. Embedded within this was snowballing or “circular sampling” (Wind & Thomas, 1980) within cases, to identify multiple informants. These strategies worked together to allow for cases which both met the criteria necessary and which were likely to be information rich.

81

The total number of cases considered in this study is ten, with the information for each case primarily made up of responses from between 2 and 6 informed individuals. The results and analysis are largely based on these ten cases. However, in addition to this, ten individuals were identified as experts, and their responses served as a point of

comparison for the findings. This number of cases examined is not dissimilar to other theory-building studies (e.g. Drumwright, 1994; Graebner, 2004).

It is important to consider the question of the number of cases deemed sufficient, in light of theory-building. As Eisenhardt and Graebner (2007) point out, when developing rather than testing theory, the cases need not be “representative” and theoretical sampling is appropriate. Similarly, Miles & Huberman (1994) propose that this question should not be answered with statistics, but rather by considering how many cases will give the researcher confidence of analytic generalisations, and how in-depth each case is studied.

Similarly Richards (2005) states:

Well-designed qualitative research projects are usually small, the data detailed and the techniques designed to discover meaning through fine attention to content of texts or images. These techniques take time and do not need large samples. (p.20)

In order to arrive at the final ten, as well as experts, a total of 31 individuals were

interviewed in sessions ranging from 1 – 2 ½ hours, all of which were digitally recorded and transcribed. This allowed for the initial identification of 21 cases. Cases were then eliminated if information was only gathered from one side of the dyad and/or if the information was deemed insufficient. In total, 24 interviews contributed to 10 case studies. Each case study had responses from both sides of the dyad, with a minimum of two respondents, and a maximum of six respondents.

As noted earlier, ten interviews were further included as a panel of “experts.” These interviews were from individuals who had considerable experience in the sponsorship field, working for a number of organisations over the years either in the role of senior management or as a board member. These interviews were distinguished by the range of examples of sponsorships, and insight into the decision-making process within multiple companies. The responses from this group of experts was used as a further but secondary level of analysis.

82

A summary of the characteristics of the ten cases is provided in Table 4.1. As noted, there is representation of a number of industries, ownership structures, and decision statuses. In addition to these characteristics cases were sought in order to gather

comparisons within companies and within arts organisations. In other words, some cases involved different sponsorship decisions within the same company, allowing for

comparison to be made while keeping the company constant. Also some cases involved different companies making decisions on the same arts organisation, allowing for comparison to be made while keeping the arts organisation constant. Further details on each case will be provided in chapter 5.

Table 4.1 Case Study Characteristics

Characteristics Number

of cases

Industry classifications* for sponsoring companies

Electricity, gas, water & waste services (Division D) 2

Transport, Postal and Warehousing ( Div I) 3

Manufacturing (Div C) 3

Professional, Scientific & Technical Srvcs (Div M) 1

Construction (E) 1

Status of Decision (new or renewing)

New 8

Renewing 2

* Industry categorisation is taken from the Australian and New Zealand Standard Industrial Classification, 2006 (Trewin & Pink, 2006).

7 State-owned Enterprises or “SOEs” were established in New Zealand from the mid 1980‟s as the country adopted free-market reforms, and the government saw advantages in the for-profit mode of operation.

With this structure, government-owned services were „corporatized.‟ These companies have CEOs and Boards of Directors installed, and are required to conduct arms-length management decision making (vs.

political control). In addition to responsibilities later noted in this document, SOEs are required to pay tax, return a dividend to their sole shareholder (the NZ Government) and produce audited annual reports.

83