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Exploratory vs Confirmatory Research
Abstract
Exploratory research is the stage of the research process that aims at connecting ideas as to unveil the “why”s of potential cause/effect relationships. This occurs when researchers get started at understanding what they are actually “observing” when in the process of building cause/effect models.
Confirmatory research (a.k.a. hypothesis testing) is where researchers have a pretty good idea of what's going on. That is, researcher has a theory (or several theories), and the objective is to find out if the theory is supported by the facts.
The essence of all this is that exploratory and confirmatory research are two complementary components of the same goal: to discover relevant findings in the most efficient, reliable, replicable, applicable manner.
... In confirmatory (also called hypothesis-testing) research, the researcher has a specific idea about the relationship between the variables under investigation and is trying to see if hypotheses are supported by data (Butler, 2014). In this case, a SEM is a confirmatory factor analysis model (CFA). ...
... Thus, this study is a structural equation model study. Confirmatory research is a study in which researchers hold a certain hypothesis or idea about the research questions, which includes the relations or differences between constructs (Butler, 2014). The present study proposed and examined a measurement model with CFA, focused on exploring single simple or multiple linear regression (Nachtigall et al., 2003). ...
A variety of studies have attempted to explain the dispositions of imagination; notably, imagination engages and develops an individual’s creativity. In the present study, we propose that three types of imagination dispositions (i.e., epistemic, sensory, and future imagination) serve as cognitive mechanisms for the ability to efficiently generate new ideas relevant to imagination with-making and imagination without-making. The correlates between imagination disposition and imagination with-making and imagination without-making were subjected to confirmatory factor analysis and structural equation modeling. The results showed that epistemic imagination was positively related to imagination with-making, but not to imagination without-making; future imagination was positively related to imagination without-making but was not related to imagination with-making; and sensory imagination was positively related to both imagination with-making and imagination without-making. Moreover, imagination without-making was positively related to imagination with-making. The results of this study offer a practical model for understanding imaginative disposition and ability, and provide a framework for future studies to explore imagination disposition and ability in various areas, such as craft creation.
... Consequently, I assumed the positivism paradigm that advocates for organised methods to discover and confirm a set of probabilistic causal laws useful in predicting patterns of human activity through precise empirical observations of individual behaviour (Neuman, 2007). In view of this positivist position, the study adopted the confirmatory research design that is covariance based and focuses on the explanation of relationships among variables (Butler, 2014). ...
... Results of the Cronbach's alpha reliability test presented in Table 3 indicate that all the questionnaire items developed for measuring the constructs in question had reliability coefficients above the recommended value of 0.7 (Butler, 2014). This indicates that the items were consistent in measuring the constructs. ...
The role of networking in the sharing of knowledge and information is well documented. What is not clear, however, are the facets of networks that best drive firm performance, and whether or not the nature of business is a factor. The purpose of this study was to examine the effect of networking dimensions on the performance of event management ventures in Kenya. The researcher conceptualised that performance of ventures was a function of networking dimensions such as network capability, network structure and network dynamics. The study adopted a covariance-based confirmatory research design that sought to confirm indicators of the four variables under study, and also to establish the causal link between networking dimensions and venture performance. A population of 313 ventures was targeted, from which a sample of 288 proprietors was drawn. Using Structural Equation Modelling as the principal analysis approach, the study established that networking dimensions positively and significantly predict events venture performance. Moreover, the measurement model confirmed that the customer and learning and growth perspectives were the main indicators of events venture performance.
... It provides information about learning performance. For the proposed model, the present study was proposed according to the specific notion from the literature review of the relations between several variables (Butler, 2014). Moreover, structural equation modeling (SEM) allows researchers to select latent variables, examine the observed variables, and explore the possible relations between constructs (Nachtigall et al., 2003). ...
By using information technology, science learning can be widely disseminated, including, for example, to rural schools. However, the implementation of inquirybased science learning with action-to-ground science concepts for rural learners needs to be explored. To address this purpose, the present study adopted "live stream" technology with a science inquiry model for rural students to learn four science concepts. Using different science knowledge representations, the predictdo/observe-quiz/discuss-explain-transform (P-D/O-Q/D-E-T) inquiry model was designed to be implemented via live streaming with local teachers' facilitation. Drawing on the cognitive-affective theory of multimedia learning and triadic reciprocal determinism, the present study focused on exploring how the live-streaming presence and external cognitive load can predict participants' flow and learning performance. A total of 45 participants completed the questionnaire, pre-test, and post-test, and structural equation modeling was adopted to test the hypotheses of this study. The results showed that live-streaming presence could positively predict flow, but external cognitive load can negatively predict flow, while flow can positively predict learning performance. This live-streaming method uses inexpensive and affordable educational technology that can be implemented at any rural elementary school to enable rural students to learn science remotely.
... It provides information about learning performance. For the proposed model, the present study was proposed according to the specific notion from the literature review of the relations between several variables (Butler, 2014). Moreover, structural equation modeling (SEM) allows researchers to select latent variables, examine the observed variables, and explore the possible relations between constructs (Nachtigall et al., 2003). ...
By using information technology, science learning can be widely disseminated, including, for example, to rural schools. However, the implementation of inquiry-based science learning with action-to-ground science concepts for rural learners needs to be explored. To address this purpose, the present study adopted “live stream” technology with a science inquiry model for rural students to learn four science concepts. Using different science knowledge representations, the predict-do/observe-quiz/discuss-explain-transform (P-D/O-Q/D-E-T) inquiry model was designed to be implemented via live streaming with local teachers’ facilitation. Drawing on the cognitive-affective theory of multimedia learning and triadic reciprocal determinism, the present study focused on exploring how the live-streaming presence and external cognitive load can predict participants’ flow and learning performance. A total of 45 participants completed the questionnaire, pre-test, and post-test, and structural equation modeling was adopted to test the hypotheses of this study. The results showed that live-streaming presence could positively predict flow, but external cognitive load can negatively predict flow, while flow can positively predict learning performance. This live-streaming method uses inexpensive and affordable educational technology that can be implemented at any rural elementary school to enable rural students to learn science remotely.
... In confirmatory (also called hypothesis-testing) research, the researcher holds a specific view about the relationship between the variables under investigation and is trying to see if hypotheses are supported by data (Butler, 2014). Based on the requirement of confirmatory research, after invalid questionnaires were excluded, 333 questionnaires were obtained, giving a useful response rate of 99.1%. ...
... This study is confirmatory since it seeks to endorse the relationships proposed by the researchers (Butler, 2014). The guidelines established by Hair et al. (2010) were observed in the development of the questionnaire. ...
Purpose
This article aims to examine the influence of emotional intelligence on cross-functional teams, the formation of interorganizational networks and the impact of all three dimensions on operational effectiveness.
Design/methodology/approach
The analysis was based on 250 valid questionnaires collected from organizations in the Valle del Cauca region in Colombia in the service sector. The variables were analyzed using structural equation modeling to identify their relationships.
Findings
The results suggest that emotional intelligence contributes to establishing cross-functional teams but does not impact the development of interorganizational networks, influencing operational effectiveness only indirectly through the cross-functional teams. Contrary to what the literature suggests, interorganizational networks do not influence the operational effectiveness of organizations. Hence, in the pursuit of competitive advantage, companies in the studied region should encourage the creation of cross-functional teams within their organizations to maximize the returns received through the optimization of operational effectiveness.
Practical implications
Organizations are comprised of individuals whose emotional intelligence competencies and abilities enable them to form effective cross-functional teams. Furthermore, cross-functional teams that effectively establish relationships with other organizations are frequently employed in global, interorganizational collaboration environments like joint ventures and alliances. Cross-functional teams that fulfill their aims have the potential to benefit the organization's performance by boosting operational effectiveness and, therefore, its competitiveness.
Originality/value
The value of this article lies in providing a better understanding of the capabilities and strategies of organizations in the construction of interorganizational networks intended to improve their competitiveness. However, before operational effectiveness and a sustainable competitive advantage can be achieved, the role of the individuals comprising the cross-functional teams should be managed through the appropriate application of the concepts of emotional intelligence.
... In confirmatory (also called hypothesis-testing) research, the researcher has a specific idea about the relationship between the variables under investigation and is trying to see if hypotheses are supported by data (Butler, 2014). Based on the requirement of confirmatory research, after invalid questionnaires were excluded, the present study tested the construct reliability and validity. ...
A great deal of attention has been focused on technological innovation, for example, face recognition, which has been used in some countries in various fields. Nonetheless, there has been little attention paid to parents’ acceptance of the use of face recognition systems on campus. To address this gap in the literature, this study examined how different degrees of technological innovativeness and dangerous beliefs in the virtual world (DBVW) influence parents’ perceived value of using and intention to continue supporting schools’ use of face recognition systems. This study adopted snowball sampling to collect data through questionnaires, and received 380 valid responses from parents living in Xuzhou, China. Confirmatory factor analysis and structural equation modeling were used to analyze the data, with results indicating that: (1) DBVW was negatively related to perceived value; (2) technological innovativeness was positively related to perceived value; and (3) perceived value was positively related to continuance intention to use face recognition systems. The results suggest that parents support the use of face recognition systems in elementary school; thus, such systems can be adopted by other elementary schools in other areas.
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