importance of quantitative research in information and communication technology
Organizational Research Methods, 17(2), 182-209. Aguirre-Urreta, M. I., & Marakas, G. M. (2012). The data has to be very close to being totally random for a weak effect not to be statistically significant at an N of 15,000. This is because measurement provides the fundamental connection between empirical observation and the theoretical and mathematical expression of quantitative relationships. It is also important to regularly check for methodological advances in journal articles, such as (Baruch & Holtom, 2008; Kaplowitz et al., 2004; King & He, 2005). The speed and efficiency of the quantitative method are attractive to many researchers. Vegas and colleagues (2016) discuss advantages and disadvantages between a wide range of experiment designs, such as independent measures, repeated measures, crossover, matched-pairs, and different mixed designs. Since the assignment to treatment or control is random, it effectively rules out almost any other possible explanation of the effect. We do this in a systematic scientific way so the studies can be replicated by someone else. the estimated effect size, whereas invalid measurement means youre not measuring what you wanted to measure. In other words, data can differ across individuals (a between-variation) at the same point in time but also internally across time (a within-variation). QtPR researchers historically assumed that reality is objectively given and can be discovered by a researcher and described by measurable properties independent of the observer (researcher) and their instruments. A procedure for the analysis of LInear Structural RELations among one or more sets of variables and variates. Elden, M., & Chisholm, R. F. (1993). Survey Response Rate Levels and Trends in Organizational Research. Problems with construct validity occur in three major ways. Many great examples exist as templates that can guide the writing of QtPR papers. To avoid these problems, two key requirements must be met to avoid problems of shared meaning and accuracy and to ensure high quality of measurement: Together, validity and reliability are the benchmarks against which the adequacy and accuracy (and ultimately the quality) of QtPR are evaluated. It helps prepare different learning concepts to enhance the impact of teaching, learning, and research criteria. As a conceptual labeling, this is superior in that one can readily conceive of a relatively quiet marketplace where risks were, on the whole, low. This is why we argue in more detail in Section 3 below that modern QtPR scientists have really adopted a post-positivist perspective. MIS Quarterly, 41(4), 1307-1333. Providing a strong conceptual orientation to techniques and procedures that range from the "moderately basic" to . In the vast majority of cases, researchers are not privy to the process so that they could reasonably assess this. The last forty years have seen significant growth in the area of research in science education in Brazil. For example, one way to analyze time-series data is by means of the Auto-Regressive Integrated Moving Average (ARIMA) technique, that captures how previous observations in a data series determine the current observation. This website does not fully support Internet Explorer. If they omit measures, the error is one of exclusion. There are three main steps in deduction (Levallet et al. A sample application of ARIMA in IS research is modeling the usage levels of a health information environments over time and how quasi-experimental events related to governmental policy changed it (Gefen et al., 2019). So communication of the nature of the abstractions is critical. To achieve this goal, companies and employees must use technology wisely. (2020). An example would be the correlation between salary increases and job satisfaction. Typically, QtPR starts with developing a theory that offers a hopefully insightful and novel conceptualization of some important real-world phenomena. For example, if one had a treatment in the form of three different user-interface-designs for an e-commerce website, in a between-subject design three groups of people would each evaluate one of these designs. For example, construct validity issues occur when some of the questionnaire items, the verbiage in the interview script, or the task descriptions in an experiment are ambiguous and are giving the participants the impression that they mean something different from what was intended. Researchers use these studies to test theories about how or why certain events occur by finding evidence that supports or disproves the theories. 3. Malignant Side Effects of Null-hypothesis Significance Testing. The Effect of Statistical Training on the Evaluation of Evidence. Quantitative studies are often fast, focused, scientific and relatable.4. Knowledge is acquired through both deduction and induction. Quantitative Research in Communication is ideal for courses in Quantitative Methods in Communication, Statistical Methods in Communication, Advanced Research Methods (undergraduate), and. Empirical testing aimed at falsifying the theory with data. Lee, A. S., Mohajeri, K., & Hubona, G. S. (2017). It is out of tradition and reverence to Mr. Pearson that it remains so. QtPR is a set of methods and techniques that allows IS researchers to answer research questions about the interaction of humans and digital information and communication technologies within the sociotechnical systems of which they are comprised. And, yet both uncertainty (e.g., about true population parameters) and assumed probabilities (pre-existent correlations between any set of variables) are at the core of NHST as it is applied in the social sciences especially when used in single research designs, such as one field study or one experiment (Falk & Greenbaum, 1995). Misinterpretations of Significance: A Problem Students Share with Their Teachers? The content domain of an abstract theoretical construct specifies the nature of that construct and its conceptual theme in unambiguous terms and as clear and concise as possible (MacKenzie et al., 2011). Causality: Models, Reasoning, and Inference (2nd ed.). The original inspiration for this approach to science came from the scientific epistemology of logical positivism during the 1920s and 1930s as developed by the Vienna Circle of Positivists, primarily Karl Popper,. Orne, M. T. (1962). It is by no means optional. Many studies have pointed out the measurement validation flaws in published research, see, for example (Boudreau et al., 2001). Quantitative Research is generally used in the field of community health, marketing, sociology,economics, psychology, demographics, gender studies, political science. Aldine Publishing Company. Finally, there is a perennial debate in QtPR about null hypothesis significance testing (Branch, 2014; Cohen, 1994; Pernet, 2016; Schwab et al., 2011; Szucs & Ioannidis, 2017; Wasserstein & Lazar, 2016; Wasserstein et al., 2019). Communications of the Association for Information Systems, 16(45), 880-894. 4. The convention is thus that we do not want to recommend that new medicines be taken unless there is a substantial and strong reason to believe that this can be generalized to the population (a low alpha). Organization files and library holdings are the most frequently used secondary sources of data. (2007). Data computing equipment makes it possible to process and analyze data quickly, even with large sample sizes. The point here is not whether the results of this field experiment were interesting (they were, in fact, counter-intuitive). Historically, internal validity was established through the use of statistical control variables. Unless the persons weight actually changes in the times between stepping repeatedly on to the scale, the scale should consistently, within measurement error, give you the same results. Other popular ways to analyze time-series data are latent variable models such as latent growth curve models, latent change score models, or bivariate latent difference score models (Bollen & Curran, 2006; McArdle, 2009). MIS Quarterly, 34(2), 345-366. Reinhart, A. Selection bias means that individuals, groups, or other data has been collected without achieving proper randomization, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. Federation for American Immigration Reform. Interpretive Case Studies in IS Research: Nature and Method. And, crucially, inferring temporal precedence, i.e., establishing that the cause came before the effect, in a one-point in time survey is at best related to self-reporting by the subject. Pearson Education. More discussion on how to test endogeneity is available in Greene (2012). Measurement for the Social Sciences: The C-OAR-SE Method and Why It Must Replace Psychometrics. Imagine a situation where you carry out a series of statistical tests and find terrific indications for statistical significance. The objective of multiple regression analysis is to predict the changes in the dependent variable in response to the changes in the several independent variables (Hair et al., 2010). Cohens (1960) coefficient Kappa is the most commonly used test. How does this ultimately play out in modern social science methodologies? The same conclusion would hold if the experiment was not about preexisting knowledge of some phenomenon. Gefen, D., Straub, D. W., & Boudreau, M.-C. (2000). With the caveat offered above that in scholarly praxis, null hypotheses are tested today only in certain disciplines, the underlying testing principles of NHST remain the dominant statistical approach in science today (Gigerenzer, 2004). In addition to situations where the above advantages apply, quantitative research is helpful when you collect data from a large group of diverse respondents. Hackett. There are several good illustrations in the literature to exemplify how this works (e.g., Doll & Torkzadeh, 1998; MacKenzie et al., 2011; Moore & Benbasat, 1991). Figure 9 shows how to prioritize the assessment of measurement during data analysis. The researcher controls or manipulates an independent variable to measure its effect on one or more dependent variables. Similarly, 1-p is not the probability of replicating an effect (Cohen, 1994). A correlation between two variables merely confirms that the changes in variable levels behave in particular way upon changing another; but it cannot make a statement about which factor causes the change in variables (it is not unidirectional). Rand McNally College Publishing Company. Schwab, A., Abrahamson, E., Starbuck, W. H., & Fidler, F. (2011). The autoregressive part of ARIMA regresses the current value of the series against its previous values. What are theories? QtPR is also not design research, in which innovative IS artifacts are designed and evaluated as contributions to scientific knowledge. The standard value for betas has historically been set at .80 (Cohen 1988). Diamantopoulos, Adamantios and Heidi M. Winklhofer, Index Construction with Formative Indicators: An Alternative to Scale Development, Journal of Marketing Research, 38, 2, (2001), 269-277. In any case, the researcher is motivated by the numerical outputs and how to imbue them with meaning. In fact, there are several ratings that we can glean from the platform and these we will combine to create an aggregate score. John Wiley and Sons. Quantitative research has the goal of gaining a better understanding of the social world. Linear probability models accommodate all types of independent variables (metric and non-metric) and do not require the assumption of multivariate normality (Hair et al., 2010). "Nice examples of researcher webpages. Wilks Lambda: One of the four principal statistics for testing the null hypothesis in MANOVA. Psychonomic Bulletin & Review, 16(4), 617-640. B., Stern, H., Dunson, D. B., Vehtari, A., & Rubin, D. B. Therefore, experimentation covers all three Shadish et al. Streiner, D. L. (2003). Since no change in the status quo is being promoted, scholars are granted a larger latitude to make a mistake in whether this inference can be generalized to the population. Overall, modern social scientists favor theorizing models with expressed causal linkages and predictions of correlational signs. Before reviewing the literature and the most important quantitative techniques we need to give our own working definition of FTA. Gelman, A., & Stern, H. (2006). ber den anschaulichen Inhalt der quantentheoretischen Kinematik und Mechanik (in German). Researchers who are permitted access to transactional data from, say, a firm like Amazon, are assuming, moreover, that the data they have been given is accurate, complete, and representative of a targeted population. 91-132). (2015) propose to evaluate heterotrait-monotrait correlation ratios instead of the traditional Fornell-Larcker criterion and the examination of cross-loadings when evaluating discriminant validity of measures. Importance of quantitative research. The Presence of Something or the Absence of Nothing: Increasing Theoretical Precision in Management Research. Information and Communications Technology (ICT) is an important part in the country's development. B. Woszczynski (Eds. Applied Multivariate Statistics for the Social Sciences (4th ed.). Following the MAP (Methods, Approaches, Perspectives) in Information Systems Research. In other words, QtPR researchers are generally inclined to hypothesize that a certain set of antecedents predicts one or more outcomes, co-varying either positively or negatively. Gray, P. H., & Cooper, W. H. (2010). (1979). It can include also cross-correlations with other covariates. Journal of the Royal Statistical Society, 98(1), 39-82. However, with this methodology, events and their timing are determined by both the researcher and the behavior of the human subject (Jenkins, 1985; Fromkin and Streufert, 1976). This means that there are variables you have not included that explain even more variance than your model does. the role and importance of information communication in science and technology are following: it has enabled to predict and forecast weather conditions by studying meteors. Centefelli, R. T., & Bassellier, G. (2009). Irwin. Quantitative research is structured around the scientific method. Gelman, A. Masson, M. E. (2011). Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). (2009). Journal of the Association for Information Systems, 21(4), 1072-1102. Low power thus means that a statistical test only has a small chance of detecting a true effect or that the results are likely to be distorted by random and systematic error. QtPR has historically relied on null hypothesis significance testing (NHST), a technique of statistical inference by which a hypothesized value (such as a specific value of a mean, a difference between means, correlations, ratios, variances, or other statistics) is tested against a hypothesis of no effect or relationship on basis of empirical observations (Pernet, 2016). However, "states of knowledge surveys" are still rarely found in the field of science education. Q-sorting consists of a modified rank-ordering procedure in which stimuli are placed in an order that is significant from the standpoint of a person operating under specified conditions. A Tutorial on a Practical Bayesian Alternative to Null-Hypothesis Significance Testing. MANOVA is useful when the researcher designs an experimental situation (manipulation of several non-metric treatment variables) to test hypotheses concerning the variance in group responses on two or more metric dependent variables (Hair et al., 2010). (2017). Such data, however, is often not perfectly suitable for gauging cause and effect relationships due to potential confounding factors that may exist beyond the data that is collected. Sentences can also be transformed from active voice that utilizes the personal pronoun in many other ways. In the latter case, the researcher is not looking to confirm any relationships specified prior to the analysis, but instead allows the method and the data to explore and then define the nature of the relationships as manifested in the data. Mertens, W., Pugliese, A., & Recker, J. Field studies tend to be high on external validity, but low on internal validity. In contrast, according to Popper, is Freuds theory of psychoanalysis which can never be disproven because the theory is sufficiently imprecise to allow for convenient explanations and the addition of ad hoc hypotheses to explain observations that contradict the theory. This methodological discussion is an important one and affects all QtPR researchers in their efforts. Next we did the other thing Such sentences stress the actions and activities of the researcher(s) rather than the purposes of these actions. It measures whether several measurement items that propose to measure the same general construct produce similar scores. Too Big to Fail: Large Samples and the p-Value Problem. Here is what a researcher might have originally written: To measure the knowledge of the subjects, we use ratings offered through the platform. Journal of the Association for Information Systems, 12(9), 632-661. So if either the posited independent variable or the confound (a rival variable) is poorly measured, then you cannot know with any certainty whether one or the other variable is the true cause. Harcourt Brace College Publishers. MacKenzie et al. Written for communication students, Quantitative Research in Communication provides practical, user-friendly coverage of how to use statistics, how to interpret SPSS printouts, how to write results, and how to assess whether the assumptions of various procedures have been met . Central to understanding this principle is the recognition that there is no such thing as a pure observation. For example, QlPR scholars might interpret some quantitative data as do QtPR scholars. 2021): Whereas seeking to falsify theories is the idealistic and historical norm, in practice many scholars in IS and other social sciences are, in practice, seeking confirmation of their carefully argued theoretical models (Gray & Cooper, 2010; Burton-Jones et al., 2017). As in experimental research, the focus is the effect of an independent variable on a dependent variable. Cohen, J. Eventually, businesses are prone to several uncertainties. Diamantopoulos, A., & Siguaw, J. Starting at the Beginning: An Introduction to Coefficient Alpha and Internal Consistency. Often, we approximate objective data through inter-subjective measures in which a range of individuals (multiple study subjects or multiple researchers, for example) all rate the same observation and we look to get consistent, consensual results. Cronbach, L. J. Figure 2 also points to two key challenges in QtPR. Unfortunately, though, based on observations of hundreds of educational technology projects over the past decade, it is pretty clear to me that, in too many cases, investments in educational technologies remain a largely faith-based initiative in many places around the world. Hair et al. Observation means looking at people and listening to them talk. Science, 348(6242), 1422-1425. The purpose of research involving survey instruments for description is to find out about the situations, events, attitudes, opinions, processes, or behaviors that are occurring in a population. European Journal of Information Systems, 4, 74-81. Selection bias in turn diminishing internal validity. This methodology employs a closed simulation model to mirror a segment of the realworld. Human subjects are exposed to this model and their responses are recorded. Historically, QtPR scholars in IS research often relied on methodologies for measurement instrument development that build on the work by Churchill in the field of marketing (Churchill, 1979). So, essentially, we are testing whether our obtained data fits previously established causal models of the phenomenon including prior suggested classifications of constructs (e.g., as independent, dependent, mediating, or moderating). Accordingly, a scientific theory is, at most, extensively corroborated, which can render it socially acceptable until proven otherwise. All measures in social sciences, thus, are social constructions that can only approximate a true, underlying reality. QtPR scholars sometime wonder why the thresholds for protection against Type I and Type II errors are so divergent. Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. For example, in Linear Regression the dependent variable Y may be the polynomial combination of aX1+bX2+e, where it is assumed that X1 and X2 each has a normal distribution. This value means that researchers assume a 20% risk (1.0 .80) that they are correct in their inference. Random assignment is about randomly manipulating the instrumentation so that there is a very unlikely connection between the group assignments (in an experimental block design) and the experimental outcomes. What matters here is that qualitative research can be positivist (e.g., Yin, 2009; Clark, 1972; Glaser & Strauss, 1967) or interpretive (e.g., Walsham, 1995; Elden & Chisholm, 1993; Gasson, 2004). SEM has become increasingly popular amongst researchers for purposes such as measurement validation and the testing of linkages between constructs. ANOVA in Complex Experimental Designs. Secondary data also extend the time and space range, for example, collection of past data or data about foreign countries (Emory, 1980). A common problem at this stage is that researchers assume that labelling a construct with a name is equivalent to defining it and specifying its content domains: It is not. Sage Publications. Many choose their profession to be a statistician or a quantitative researcher consultant. Classic statistics involve mean, median, variance, or standard deviation. It is also important to recognize, there are many useful and important additions to the content of this online resource in terms of QtPR processes and challenges available outside of the IS field. What Is This Thing Called Science? Most likely, researchers will receive different answers from different persons (and perhaps even different answers from the same person if asked repeatedly). Several viewpoints pertaining to this debate are available (Aguirre-Urreta & Marakas, 2012; Centefelli & Bassellier, 2009; Diamantopoulos, 2001; Diamantopoulos & Siguaw, 2006; Diamantopoulos & Winklhofer, 2001; Kim et al., 2010; Petter et al., 2007). Out the measurement validation flaws in published research, see, for,... Experimental research, see, for example ( Boudreau et al., 2001 ), 1-p is not the of. Or disproves the theories interesting ( they were, in which innovative artifacts... It effectively rules out almost any other possible explanation of the Royal statistical Society, 98 ( 1,... 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