The Use of Factorial Surveys in Leisure Research

By Shooter, Wynn; Galloway, Shayne | Journal of Leisure Research, Fall 2010 | Go to article overview

The Use of Factorial Surveys in Leisure Research


Shooter, Wynn, Galloway, Shayne, Journal of Leisure Research


Investigators have used factorial survey approaches (FSA) in leisure research to predict decision-making in naturalistic outdoor recreation and education environments (Galloway, 2007; Shooter, Paisley, & Sibthorp, 2009), to determine preferred resource management strategies at outdoor recreation sites (Oh & Ditton, 2006), to identify ideal leadership characteristics of youth camp leaders (Ward & Ellis, 2008), and to determine the conditions that promote loyalty to community recreation centers (Haas, Ellis, & Wells, 2009). These studies exemplify the types of projects that can benefit from utilizing a factorial survey method. The common theme among these studies is that the authors tested the influence of specific predictors on decision-making by using a research method that combines features of experimental design with traditional survey research (Dulmer, 2007; Herzog, 2003; Ludwick & Zeller, 2001). Likewise, each of these studies would have faced insurmountable challenges to conducting actual field-based experiments or else the theoretical development of the phenomenon of interest was not developed to the degree that the researchers were prepared to launch a full-scale, field-based experiment. Therefore, they relied on FSA.

Leisure researchers who wish to pursue questions that are difficult to investigate through field-based experiments for logistical, practical, financial, risk-based, and ethical reasons, among others, might consider the value of the factorial survey approach (Thurman, Lain, & Rossi, 1988). Such challenges to the ability to conduct empirical, experimental research as those listed above remain an impediment to the advancement of the field because many important problems and phenomena remain unexplored or underexplored due to the difficulties associated with study design and implementation. Therefore, this paper will provide examples of studies within the leisure research that have made use of factorial survey approaches to overcome many of the challenges listed above; will consider closely related types of factorial survey designs; and will introduce issues and recommendations related to the design and implementation of factorial surveys in leisure research.

Factorial surveys allow researchers to explore the significant correlates between the factors believed to influence decision-making, the antecedent characteristics of the respondent, and the decisions of interest (Jasso, 2006; Wallander, 2009). Factorial surveys capture real life decision-making by providing opportunities for people to express their values, beliefs, attitudes, and opinions as they evaluate and judge specific sets of circumstances (Rossi & Anderson, 1982; Taylor, 2006). Such sets of circumstances are constructed in response to theoretically derived, empirically driven questions about what is believed to influence the decision of interest.

Practically speaking, FSA utilizes survey research methodology to determine the impact of predictor variables on one or more dependent variables by having respondents read and respond to written scenarios. The scenarios, or vignettes, communicate realistic but hypothetical situations (Ludwick, O'Toole, O'Toole, & Webster, 1999; Rossi & Nock, 1982; Taylor, 2006). Each vignette contains a number of factors that most often vary within and between vignettes (Dulmer, 2007; Sniderman & Grob, 1996). Through the vignettes, which are the units of analysis, a variety of realistic situations are created to which participants respond. The responses are most commonly measured as normative judgments, beliefs, attitudes, and/or intentions (Wallander, 2009).

Each vignette consists of three elements: the factors and dimensions, the textual framework, and the rating task (Dulmer, 2007; Sniderman & Grob, 1996). Taken in turn, each element forms a critical and integral component of the method. The factors and dimensions chosen for a particular study represent the independent variables of interest (e.

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