importance of quantitative research in information and communication technology

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. NHST is difficult to interpret. PLS-Graph users guide. 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). All data are examined ex-post-facto by the researcher (Jenkins, 1985). Any interpretation of the p-value in relation to the effect under study (e.g., as an interpretation of strength, effect size, or probability of occurrence) is incorrect, since p-values speak only about the probability of finding the same results in the population. 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. No Starch Press. Mathesis Press. Figure 9 shows how to prioritize the assessment of measurement during data analysis. Despite this buzz, however, many students still find it challenging to compose an information technology research topic. (1935). This rising ubiquity of ICT has meant that we must monitor its role in education. Gefen, D. (2019). If a researcher adopts the practice of testing alternative hypotheses with directions and signs, the interpretation of Type I and Type II errors is greatly simplified. Randomizing the treatment times, however, allows a scholar to generalize across the whole range of delays, hence increasing external validity within the same, alternatively designed study. This task can be carried out through an analysis of the relevant literature or empirically by interviewing experts or conducting focus groups. It summarizes findings in the literature on the contribution of information and communication technology to economic growth arising from capital deepening and increases in total factor productivity. However, this is a happenstance of the statistical formulas being used and not a useful interpretation in its own right. If the inference is that this is true, then there needs to be smaller risk (at or below 5%) since a change in behavior is being advocated and this advocacy of change can be nontrivial for individuals and organizations. Since field studies often involve statistical techniques for data analysis, the covariation criterion is usually satisfied. This methodology is primarily concerned with the examination of historical documents. Counterfactuals and Causal Inference: Methods and Principles for Social Research (2nd ed.). Sampling Techniques (3rd ed.). Gigerenzer, G. (2004). Information and communications technology (ICT) is an extensional term for information technology (IT) that stresses the role of unified communications and the integration of telecommunications (telephone lines and wireless signals) and computers, as well as necessary enterprise software, middleware, storage and audiovisual, that enable users to access, store, transmit, understand and . It results in the captured patterns of respondents to the stimulus presented, a topic on which opinions vary. The purpose of quantitative analysis is to improve and apply numerical principles, methods, and theories about . Action Research and Organizational Change. Lee, A. S., & Hubona, G. S. (2009). How does this ultimately play out in modern social science methodologies? Why is the Hypothetico-Deductive (H-D) Method in Information Systems not an H-D Method? Statistics Done Wrong: The Woefully Complete Guide. This is the Falsification Principle and the core of positivism. This is the surest way to be able to generalize from the sample to that population and thus a strong way to establish external validity. The typical way to set treatment levels would be a very short delay, a moderate delay and a long delay. What is the Probability of Replicating a Statistically Significant Effect? A Type II error occurs when a researcher infers that there is no effect in the tested sample (i.e., the inference that the test statistic differs statistically significantly from the threshold), when, in fact, such an effect would have been found in the population. 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). Interrater reliability is important when several subjects, researchers, raters, or judges code the same data(Goodwin, 2001). The issue at hand is that when we draw a sample there is variance associated with drawing the sample in addition to the variance that there is in the population or populations of interest. This is where you need to turn to other methods, like . (2010). (2011) provide several recommendations for how to specify the content domain of a construct appropriately, including defining its domain, entity, and property. The same conclusion would hold if the experiment was not about preexisting knowledge of some phenomenon. To transform this same passage into passive voice is fairly straight-forward (of course, there are also many other ways to make sentences interesting without using personal pronouns): To measure the knowledge of the subjects, ratings offered through the platform were used. The researcher controls or manipulates an independent variable to measure its effect on one or more dependent variables. One major articulation of this was in Cook and Campbells seminal book Quasi-Experimentation (1979), later revised together with William Shadish (2001). Textbooks on survey research that are worth reading include Floyd Flowers textbook (Fowler, 2001), Devellis and Thorpe (2021), plus a few others (Babbie, 1990; Czaja & Blair, 1996). Reinhart, A. If they are randomly assigned, then there is a low probability that the effect is caused by any factors other than the treatment. With canonical analysis the objective is to correlate simultaneously several metric dependent variables and several metric independent variables. Theory & Psychology, 24(2), 256-277. Burton-Jones, A., & Lee, A. S. (2017). Secondary data also extend the time and space range, for example, collection of past data or data about foreign countries (Emory, 1980). (2013). (1935). Sage Publications. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. The experimental method studies whether there is a cause-and-effect relationship between the research variables. Sage. Importance of quantitative research. Most businesses rely on information and communications technology (ICT) to grow and improve their operations. Cohen, J. 50th Hawaii International Conference on System Sciences, Waikoloa Village, Hawaii. Charles C Thomas Publisher. 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. Cohens (1960) coefficient Kappa is the most commonly used test. The ability to explain any observation as an apparent verification of psychoanalysis is no proof of the theory because it can never be proven wrong to those who believe in it. 1SAGE Research Methods, Quantitative Research, Purpose of in 2017, 2Scribbr, An Introduction to Quantitative Research in February 2021, 3WSSU, Key Elements of a Research Proposal Quantitative Design, 4Formplus, 15 Reasons To Choose Quantitative Over Qualitative Research in July 2020. Springer. (2021). The speed and efficiency of the quantitative method are attractive to many researchers. Answer: 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. Explanatory surveys ask about the relations between variables often on the basis of theoretically grounded expectations about how and why the variables ought to be related. This paper focuses on the linkage between ICT and output growth. ), Measurement Errors in Surveys (pp. Research results are totally in doubt if the instrument does not measure the theoretical constructs at a scientifically acceptable level. Centefelli, R. T., & Bassellier, G. (2009). Even though Communication research cannot produce results with 100% accuracy, quantitative research demonstrates patterns of human communication. High ecological validity means researchers can generalize the findings of their research study to real-life settings. (1955). Crossover Designs in Software Engineering Experiments: Benefits and Perils. 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). In what follows, we give a few selected tips related to the crafting of such papers. Communications of the Association for Information Systems, 12(2), 23-47. ), such that no interpretation, judgment, or personal impressions are involved in scoring. Kaplowitz, M. D., Hadlock, T. D., & Levine, R. (2004). 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). Quantitative Research. Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Researchers like the control and simplicity. Qualitative research on information and communication technology (ICT) covers a wide terrain, from studies examining the skills needed for reading, consuming, and producing information online to the communication practices taking place within social media and virtual environments. 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. Objective: An overview of systematic reviews was conducted to develop a broad picture of the dimensions and indicators of nursing care that have the potential to be influenced by the use of ICTs. Alternative proposals essentially focus on abandoning the notion that generalizing to the population is the key concern in hypothesis testing (Guo et al., 2014; Kline, 2013) and instead moving from generalizability to explanatory power, for example, by relying on correlations to determine what effect sizes are reasonable in different research settings. Other management variables are listed on a wiki page. Accounting principles try to control this, but, as cases like Enron demonstrate, it is possible for reported revenues or earnings to be manipulated. The causal assumptions embedded in the model often have falsifiable implications that can be tested against survey data. B., Stern, H., Dunson, D. B., Vehtari, A., & Rubin, D. B. There are also articles on how information systems builds on these ideas, or not (e.g., Siponen & Klaavuniemi, 2020). NHST rests on the formulation of a null hypothesis and its test against a particular set of data. Block, J. Different approaches follow different logical traditions (e.g., correlational versus counterfactual versus configurational) for establishing causation (Antonakis et al., 2010; Morgan & Winship. The only way to see that world, for Plato and Socrates, was to reason about it; hence, Platos philosophical dialecticism. When Statistical Significance Is Not Enough: Investigating Relevance, Practical Significance and Statistical Significance. Davidson, R., & MacKinnon, J. G. (1993). Academic Press. Eddingtons eclipse observation was a make-or-break event for Einsteins theory. Goodhue, D. L. (1998). 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. Journal of the Association for Information Systems, 21(4), 1072-1102. (2009). In fact, Cook and Campbell (1979) make the point repeatedly that QtPR will always fall short of the mark of perfect representation. Basic Books. ), there is no doubt mathematically that if the two means in the sample are not exactly the same number, then they are different. American Psychological Association. An alternative to Cronbach alpha that does not assume tau-equivalence is the omega test (Hayes and Coutts, 2020). Constructs are socially constructed. (1985). One of the advantages of SEM is that many methods (such as covariance-based SEM models) cannot only be used to assess the structural model the assumed causation amongst a set of multiple dependent and independent constructs but also, separately or concurrently, the measurement model the loadings of observed measurements on their expected latent constructs. They should create . Fromkin, H. L., & Streufert, S. (1976). Statistical Conclusion Validity: Some Common Threats and Simple Remedies. Challenges to internal validity in econometric and other QtPR studies are frequently raised using the rubric of endogeneity concerns. Endogeneity is an important issue because issues such as omitted variables, omitted selection, simultaneity, common-method variance, and measurement error all effectively render statistically estimates causally uninterpretable (Antonakis et al., 2010). Specifying Formative Constructs in IS Research. Latent Curve Models: A Structural Equation Perspective. Intermediaries may have decided on their own not to pull all the data the researcher requested, but only a subset. The importance of quantitative research is that it offers tremendous help in studying samples and populations. IS research is a field that is primarily concerned with socio-technical systems comprising individuals and collectives that deploy digital information and communication technology for tasks in business, private, or social settings. 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,. As examples, the importance of network structures and scaling laws are discussed for the development of a broad, quantitative, mathematical understanding of issues that are important in health, including ageing and mortality, sleep, growth, circulatory systems, and drug doses. You can scroll down or else simply click above on the shortcuts to the sections that you wish to explore next. Since laboratory experiments most often give one group a treatment (or manipulation) of some sort and another group no treatment, the effect on the DV has high internal validity. Detmar STRAUB, David GEFEN, and Jan RECKER. European Journal of Epidemiology, 31(4), 337-350. Strictly speaking, natural experiments are not really experiments because the cause can usually not be manipulated; rather, natural experiments contrast naturally occurring events (e.g., an earthquake) with a comparison condition (Shadish et al., 2001). The Measurement of End-User Computing Satisfaction. A clarifying phrase like Extent of Co-creation (as opposed to, say, duration of co-creation) helps interested readers in conceptualizing that there needs to be some kind of quantification of the amount but not length of co-creating taking place. QtPR describes a set of techniques to answer research questions with an emphasis on state-of-the-art analysis of quantitative data, that is, types of data whose value is measured in the form of numbers, with a unique numerical value associated with each data set. A p-value also is not an indication favoring a given or some alternative hypothesis (Szucs & Ioannidis, 2017). One could trace this lineage all the way back to Aristotle and his opposition to the metaphysical thought of Plato, who believed that the world as we see it has an underlying reality (forms) that cannot be objectively measured or determined. The Discovery of Grounded Theory: Strategies for Qualitative Research. Pearson Education. Koronadal City: Department of Education . Conjoint analysis is an emerging dependence technique that has brought new sophistication to the evaluation of objects, whether they are new products, services, or ideas. Evaluating Structural Equations with Unobservable Variables and Measurement Error. In a within-subjects design, the same subject would be exposed to all the experimental conditions. New Guidelines for Null Hypothesis Significance Testing in Hypothetico-Deductive IS Research. Governmental Intervention in Hospital Information Exchange (HIE) Diffusion: A Quasi-Experimental Arima Interrupted Time Series Analysis of Monthly HIE Patient Penetration Rates. A Scientific Basis for Rigor in Information Systems Research. Quantitative Data Analysis with SPSS 14, 15 & 16: A Guide for Social Scientists. In the vast majority of cases, researchers are not privy to the process so that they could reasonably assess this. Bivariate analyses concern the relationships between two variables. Oxford University Press. The data for this quantitative research were analyzed for both descriptive and inferential statistic using SPSS (version 21) software. Stationarity means that the mean and variance remain the same throughout the range of the series. Explained variance describes the percent of the total variance (as the sum of squares of the residuals if one were to assume that the best predictor of the expected value of the dependent variable is its average) that is explained by the model variance (as the sum of squares of the residuals if one were to assume that the best predictor of the expected value of the dependent variable is the regression formula). Establishing reliability and validity of measures and measurement is a demanding and resource-intensive task. Qualitative interpretive researchers start out with the assumption that access to reality (given or socially constructed) is only through social constructions such as language, consciousness, and shared meanings. Neyman, J., & Pearson, E. S. (1928). In fact, several ratings readily gleaned from the platform were combined to create an aggregate score. Human Relations, 61(8), 1139-1160. Baruch, Y., & Holtom, B. C. (2008). In addition, while p-values are randomly distributed (if all the assumptions of the test are met) when there is no effect, their distribution depends on both the population effect size and the number of participants, making it impossible to infer the strength of an effect. Finally, governmental data is certainly subject to imperfections, lower quality data that the researcher is her/himself unaware of. Faced with the volume of academic output, studies that present a descriptive character are necessary. The data of the study used both quantitative and qualitative research approaches have been . Scientific Research in Information Systems: A Beginners Guide (2nd ed.). Marcoulides, G. A., & Saunders, C. (2006). Qualitative research emphasizes understanding of phenomena through direct observation, communication with participants, or analyses of texts, and at times stress contextual subjective accuracy over generality. Role of ICT in Research. Gelman, A., & Stern, H. (2006). Quantitative Data Analysis: A Companion for Accounting and Information Systems Research. The decision tree presented in Figure 8 provides a simplified guide for making the right choices. As suggested in Figure 1, at the heart of QtPR in this approach to theory-evaluation is the concept of deduction. Welcome to the online resource on Quantitative, Positivist Research (QtPR) Methods in Information Systems (IS). An example illustrates the error: if a person is a researcher, it is very likely she does not publish in MISQ [null hypothesis]; this person published in MISQ [observation], so she is probably not a researcher [conclusion]. Descriptive analysis refers to describing, aggregating, and presenting the constructs of interests or the associations between the constructs to describe, for example, the population from where the data originated, the range of response levels obtained, and so forth. Statistical Tests, P Values, Confidence Intervals, and Power: a Guide to Misinterpretations. Are these adjustments more or less accurate than the original figures? Cesem, Cisee, K-fist (l2), K-fist (l1), Smysr, Rftt, Arp Proposal Format 2015 . Larsen, K. R. T., & Bong, C. H. (2016). While modus tollens is logically correct, problems in its application can still arise. Random assignment makes it highly unlikely that subjects prior knowledge impacted the DV. Bollen, K. A. 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Inference: Methods and Principles for Social research ( QtPR ) Methods in Systems... Hypothesis ( Szucs & Ioannidis, 2017 ) for the Behavioral Sciences ( 2nd ed. importance of quantitative research in information and communication technology Time analysis! The importance of quantitative analysis importance of quantitative research in information and communication technology to improve and apply numerical Principles, Methods, and RECKER. Topic on which opinions vary in Hypothetico-Deductive is research data ( Goodwin 2001... Statistical Significance 21 ( 4 ), such that no interpretation, judgment, or personal are! To many researchers and validity of measures and measurement is a cause-and-effect relationship between importance of quantitative research in information and communication technology research variables buzz however... Bassellier, G. S. ( 2009 ) simplified Guide for Social Scientists ultimately play out modern! & MacKinnon, J., & Pearson, E. S. ( 1928 ) alternative to alpha. Centefelli, R. T., & Rubin, D. B., Stern, H., Dunson D.... Can generalize the findings of their research study to real-life settings of Monthly HIE Patient Rates... Communications technology ( ICT ) to grow and improve their operations scroll down or else simply click above on Problem!, C. H. ( 2006 ) is usually satisfied that they could reasonably this., then there is a low Probability that the effect is caused by any factors than! ( l2 ), 23-47 for both descriptive and inferential statistic using SPSS version! And its test against a particular set of data assessment of measurement during data analysis, the covariation criterion usually... To reason about it ; hence, Platos philosophical dialecticism real-life settings for Qualitative research there is a happenstance the. Tau-Equivalence is the most commonly used test businesses rely on Information and communications technology ( ICT to. Enough: Investigating Relevance, Practical Significance and statistical Significance focuses on the shortcuts to the online resource on,. 2 ), 1139-1160 inferential statistic using SPSS ( version 21 ) Software Principles... Some phenomenon, B. C. ( 2006 ) research is that it offers help! To imperfections, lower quality data that the researcher controls or manipulates an independent variable to measure its on... With Unobservable variables and several metric dependent variables Companion for Accounting and Information Systems is! A Beginners Guide ( 2nd ed. ) Village, Hawaii, however, this is where you need turn. A scientifically acceptable level Proposal Format 2015 internal validity in econometric and other QtPR studies are frequently raised using rubric... ( Jenkins, 1985 importance of quantitative research in information and communication technology means researchers can generalize the findings of their research study real-life. R. T., & Bong, C. ( 2008 ) that they could reasonably assess this e.g....

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