ROUTE #1: Process
ROUTE #1: Chapter-by-Chapter

Route C


In many respects, extension is more than just replication because the changes you make to the original study's research design, constructs/variables and data analysis approach adds a great deal more originality and independent thought to the traditional replication routes (i.e., compared with Route A: Duplication and Route B: Generalisation). This is why you often see journal articles that involve extension in addition to replication including both words in their titles (see below for examples):

Example titles
How salespeople build quality relationships: A replication and extension (Boles et al., 2000)

Behind make or buy decisions in export strategy: A replication and extension of Trabold (Peng et al., 2006)

The effects of age at drinking onset and stressful life events on alcohol use in adulthood: A replication and extension using a population-based twin sample (Lee et al., 2011)

Sociocultural adjustment among sojourning Malaysian students in Britain: A replication and path analytic extension (Swami et al., 2010)

Before we discuss the different types of extension that you can follow in your replication-based dissertation, it is important that you have a very basic understanding of constructs and variables. This is because (a) quantitative research involves the study of constructs and the measurement of variables, (b) the original study you choose to replicate will involve such constructs and variables, and (c) the different types of extension involve the addition, modification, or omission of constructs and variables compared with the original study.

Constructs and variables

Constructs are mental abstractions that we use to express the ideas, people, organisations, events and/or objects/things that we are interested in. The table below provides some examples of these different types of constructs:

Types of constructsExamples
IdeasAgeism, sexism, racism, self-esteem, poverty, social capital, trust, philanthropy, affluence, morality, tolerance, air pollution, genetic engineering, euthanasia, marriage, taboos
PeopleAge, gender, ethnicity, height, obesity, morbidity, energy, muscle soreness, fatigue
OrganisationsFinancial performance, corporate social responsibility, firm survival, organisational culture, service quality, corporate governance, outsourcing, alliances
EventsArmageddon, famine, urban regeneration, Jihad, secularism
Objects / Things Sun, hurricanes, tsunamis, trees, flowers, amino acids, stem cells

We often refer to constructs as mental abstractions because seldom are constructs directly observable (e.g., we cannot directly observe depression, even though we may associate depression with signs such as a person that often cries, engages in self-harm, has mood swings, etc.). Instead, we use variables to operationalize (i.e., measure) the constructs we are interested in. Sometimes a construct is measured using a single variable, such that the construct name and the variable name are the same (e.g., the construct and variable, sex). In other cases, more complex constructs (e.g., normative commitment) are measured using multiple variables (e.g., you will see questionnaires used to measure normative commitment requiring respondents to answer multiple questions, each measuring a different aspect of normative commitment).

In the next section, you see how this basic knowledge of constructs and variables is important when it comes to making choices over the type of extension to make; that is, how you will choose to extend the original study are interested in.

Types of extension

There are many ways to extend an existing study, including adding constructs and variables, looking at new measures and methods, making changes to the research design, and even using new analysis techniques. We briefly discuss two types of extension in the sections that following: population and context-driven extensions and method and measurement-driven extensions.

Population and context-driven extension: The role of constructs and variables

There are a number of reasons why you may choose to add, modify or omit certain constructs and/or variables from the original study. To highlight some of these reasons, let's look at Study #2 below:

Study #2
How salespeople build quality relationships by Boles, Johnson, & Barksdale (2000)

Boles et al. (2000) replicated a study by Crosby et al. (1990) that examined the factors that affected relationship quality between a business customer and a salesperson, as well as the impact of such relationship quality (i.e., the antecedents and consequences of the buyer-seller relationship quality). However, Crosby et al.'s (1990) original study focused on retailer customers, not business customers. Therefore, whilst replicating much of their study, Boles et al. (2000) added another construct, equity, which they felt would affect relationship quality in a business context, as opposed to a retail/consumer context. In the event, Boles et al. (2000) used three variables, previously developed by Oliver and Swan (1989) in another study to measure equity.

This highlights that if you are choosing to extend the original study by applying it to a new population or context/setting, you may need to add new constructs/variables. Sometimes you can draw on previous studies to do this. Other times you will have to create them from scratch (NOTE: We show you how to do this later). Sometimes, it will not be a desire to apply the original study to a new population or context/setting, but the publication of new research that suggests that other constructs/variables play a role in explaining the phenomenon you are interested in. However, if no research has examined the role that these constructs/variables play within the context of the original study, you have a chance to extend the theoretical model that is being investigated by adding new constructs/variables.

Study #2 (continued)

Bowles et al. (2000) also found that they needed to modify some of the existing variables that were used by Crosby et al. (1990) to measure the constructs that were being studied. In other words, the constructs were the same, but the variables used to measure these constructs had to be changed in order to they were applicable to the new audience (i.e., in practical terms, the questions in the survey had to be re-worded so that they were appropriate in a business context). Furthermore, the change in context meant that some variables were no longer relevant, so these were simply omitted from the survey (i.e., these questions were deleted from the survey).

In the case of Study #2, variables were modified or omitted compared to the original study because they were no longer relevant in the next population/context to which the authors wanted to make generalisations. However, such modifications may also have to be made because constructs, and the variables that are used to measure them, are constantly changing. This is because new research regularly emerges that suggests, for example, that a single construct (e.g., organisational commitment) is now thought to be made up of three broader constructs (e.g., normative commitment, continuance commitment and affective commitment); or new research provides a better (i.e., more reliable) way to measure a given construct (i.e., more reliable variables to measure a given construct emerge from other research). As a result, whilst maintaining many aspects of the original study, you may need to change some of the constructs/variables that were originally used, even if these original constructs were thought to be reliable at the time.

The decision to add new constructs and variables to the original study, but also modify and delete them, can lead your replication-based dissertation to make a really interested contribution to the literature. In this sense, Route C: Extension, can be considered a more original contribution.

1 2 3 4 5 6 7 8 9