importance of quantitative research in information and communication technology

Behavior Research Methods, 43(3), 679-690. the term "technology" is an important issue in many fields including education. Gigerenzer, G. (2004). One of the most common issues in QtPR papers is mistaking data collection for method(s). Methods of Psychological Research, 7(1), 1-20. A treatment is a manipulation of the real world that an experimenter administers to the subjects (also known as experimental units) so that the experimenter can observe a response. Miller, I., & Miller, M. (2012). Organizational Research Methods, 13(4), 668-689. They also list the different tests available to examine reliability in all its forms. Researchers use quantitative methods to observe situations or events that affect people. PLS-SEM: Indeed a Silver Bullet. There are numerous excellent works on this topic, including the book by Hedges and Olkin (1985), which still stands as a good starter text, especially for theoretical development. Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). The world is experiencing a digital revolution and the Philippines have the opportunity to play an enormous role in it. Reliability is important to the scientific principle of replicability because reliability implies that the operations of a study can be repeated in equal settings with the same results. Edwards, J. R., & Berry, J. W. (2010). Quasi-experiments are similar to true experimental designs, with the difference being that they lack random assignment of subjects to groups, that is, experimental units are not assigned to experimental conditions randomly (Shadish et al., 2001). Experiments can take place in the laboratory (lab experiments) or in reality (field experiments). While modus tollens is logically correct, problems in its application can still arise. Management Science, 29(5), 530-545. This reasoning hinges on power among other things. This resource seeks to address the needs of quantitative, positivist researchers in IS research in particular those just beginning to learn to use these methods. Cronbach, L. J., & Meehl, P. E. (1955). Journal of Consumer Research, 30(2), 199-218. Most businesses rely on information and communications technology (ICT) to grow and improve their operations. Lauren Slater provides some wonderful examples in her book about experiments in psychology (Slater, 2005). (1935). And it is possible using the many forms of scaling available to associate this construct with market uncertainty falling between these end points. They are: (1) content validity, (2) construct validity, (3) reliability, and (4) manipulation validity (see also Figure 4). Factor analysis is a statistical approach that can be used to analyze interrelationships among a large number of variables and to explain these variables in terms of their common underlying dimensions (factors) (Hair et al., 2010). Poppers contribution to thought specifically, that theories should be falsifiable is still held in high esteem, but modern scientists are more skeptical that one conflicting case can disprove a whole theory, at least when gauged by which scholarly practices seem to be most prevalent. Another debate in QtPR is about the choice of analysis approaches and toolsets. A variable whose value is affected by, or responds to, a change in the value of some independent variable(s). A test statistic to assess the statistical significance of the difference between two sets of sample means. The whole point is justifying what was done, not who did it. Information sharing - How quickly & easily information can be shared across the globe. Quantitative research can justify findings in Social research, though requirements could be verified/validated it could not deliver output expected for engineering. A Guide To Becoming a Medical and Health Services Manager, 3300 West Camelback Road - Phoenix, AZ 85017, Criminal Justice, Government & Public Administration, Key Elements of a Research Proposal Quantitative Design, 15 Reasons To Choose Quantitative Over Qualitative Research. Zeitschrift fr Physik, 43(3-4), 172-198. To observe situations or events that affect people, researchers use quantitative methods. Latent Variable Modeling of Differences and Changes with Longitudinal Data. The theory would have been discredited had the stars not appeared to move during the eclipse because of the Suns gravity. We note that these are our own, short-handed descriptions of views that have been, and continue to be, debated at length in ongoing philosophy of science discourses. 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. Statistical Conclusion Validity: Some Common Threats and Simple Remedies. Straub, Gefen, and Boudreau (2004) describe the ins and outs for assessing instrumentation validity. Case Study Research: Design and Methods (4th ed.). John Wiley and Sons. We typically have multiple reviewers of such thesis to approximate an objective grade through inter-subjective rating until we reach an agreement. Cambridge University Press. The most commonly used methodologies are experiments, surveys, content analysis, and meta-analysis. thank you thank you thanks Thanks po The omega test has been made available in recent versions of SPSS; it is also available in other statistical software packages. One other caveat is that the alpha protection level can vary. MIS Quarterly, 13(3), 319-340. Journal of Information Technology, 37(3), 288300. Therefore, experimentation covers all three Shadish et al. This is because in experiments the researchers deliberately impose some treatment to one or more groups of respondents (the one or more treatment groups) but not to another group (the control group) while also maintaining control over other potential confounding factors in order to observe responses. Haller, H., & Kraus, S. (2002). The most pertinent danger in experiments is a flaw in the design that makes it impossible to rule out rival hypotheses (potential alternative theories that contradict the suggested theory). What is to be included in revenues, for example, is impacted by decisions about whether booked revenues can or should be coded as current period revenues. Science achieved this through the scientific method and through empiricism, which depended on measures that could pierce the veil of reality. Kline, R. B. MacKenzie et al. Aguirre-Urreta, M. I., & Marakas, G. M. (2012). An issue of shared meaning could occur if, for instance, you are attempting to measure compassion. How do you know that you are measuring compassion and not, say, empathy, which is a socially constructed concept that to many has a similar meaning? The first cornerstone is an emphasis on quantitative data. Assessing Representation Theory with a Framework for Pursuing Success and Failure. The American Statistician, 59(2), 121-126. For example, their method could have been some form of an experiment that used a survey questionnaire to gather data before, during, or after the experiment. f importance of quantitative research across fields research findings can affect people's lives, ways of doing things, laws, rules and regulations, as well as policies, 130 Information Technology Research Topics And Quick Writing Prompts. Journal of Socio-Economics, 33(5), 587-606. Data analysis concerns the examination of quantitative data in a number of ways. It helps prepare different learning concepts to enhance the impact of teaching, learning, and research criteria. Data that was already collected for some other purpose is called secondary data. But the effective labelling of the construct itself can go a long way toward making theoretical models more intuitively appealing. We intend to provide basic information about the methods and techniques associated with QtPR and to offer the visitor references to other useful resources and to seminal works. Psychonomic Bulletin & Review, 16(4), 617-640. Straub, D. W., Gefen, D., & Boudreau, M.-C. (2005). Predictive validity (Cronbach & Meehl, 1955) assesses the extent to which a measure successfully predicts a future outcome that is theoretically expected and practically meaningful. Management Science, 62(6), 1707-1718. Fisher introduced the idea of significance testing involving the probability p to quantify the chance of a certain event or state occurring, while Neyman and Pearson introduced the idea of accepting a hypothesis based on critical rejection regions. This form of validity is discussed in greater detail, including stats for assessing it, in Straub, Boudreau, and Gefen (2004). In general terms, SEM is a statistical method for testing and estimating assumed causal relationships using a combination of statistical data and qualitative causal assumptions. The term research instrument is neutral and does not imply a methodology. Walsham, G. (1995). In the classic Hawthorne experiments, for example, one group received better lighting than another group. A third form of randomization (random item inclusion) relates to how well a constructs measures capture the content of a construct and is therefore an aspect of content validity (Straub et al. Researchers use these studies to test theories about how or why certain events occur by finding evidence that supports or disproves the theories. (2001). Jreskog, K. G., & Srbom, D. (2001). They could, of course, err on the side of inclusion or exclusion. Specifying Formative Constructs in IS Research. Even the measurement of a purely physical attribute, such as temperature, depends on the theory of how materials expand in heat. King, W. R., & He, J. Statistical control variables are added to models to demonstrate that there is little-to-no explained variance associated with the designated statistical controls. These technologies all deal with the transmission and reception of information of some kind. (2021). Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). In E. Mumford, R. Hirschheim, & A. T. Wood-Harper (Eds. Nowadays, when schools are increasingly transforming themselves into smart schools, the importance of educational technology also increases. Controlling for Lexical Closeness in Survey Research: A Demonstration on the Technology Acceptance Model. This idea introduced the notions of control of error rates, and of critical intervals. To achieve this goal, companies and employees must use technology wisely. 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. We do this in a systematic scientific way so the studies can be replicated by someone else. Sage. Obtaining such a standard might be hard at times in experiments but even more so in other forms of QtPR research; however, researchers should at least acknowledge it as a limitation if they do not actually test it, by using, for example, a Kolmogorov-Smirnoff test of the normality of the data or an Anderson-Darling test (Corder & Foreman, 2014). The purpose of quantitative research is to attain greater knowledge and understanding of the social world. What is the importance of quantitative research in communication? 3. Basically, there are four types of scientific validity with respect to instrumentation. It needs to be noted that positing null hypotheses of no effect remains a convention in some disciplines; but generally speaking, QtPR practice favors stipulating certain directional effects and certain signs, expressed in hypotheses (Edwards & Berry, 2010). Interrater reliability is important when several subjects, researchers, raters, or judges code the same data(Goodwin, 2001). Journal of Marketing Research, 16(1), 64-73. (Logik der Forschung, Vienna, 1935). Field, A. A repository of theories that have been used in information systems and many other social science theories can be found at: https://guides.lib.byu.edu/c.php?g=216417&p=1686139. 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. Elsevier. Without instrumentation validity, it is really not possible to assess internal validity. Any sources cited were Different treatments thus constitute different levels or values of the construct that is the independent variable. In other words, many of the items may not be highly interchangeable, highly correlated, reflective items (Jarvis et al., 2003), but this will not be obvious to researchers unless they examine the impact of removing items one-by-one from the construct. Guo, W., Straub, D. W., & Zhang, P. (2014). Psychological Bulletin, 52(4), 281-302. Coombs, C. H. (1976). Some of them relate to the issue of shared meaning and others to the issue of accuracy. Goodwin, L. D. (2001). Lawrence Erlbaum Associates. Surveys then allow obtaining correlations between observations that are assessed to evaluate whether the correlations fit with the expected cause and effect linkages. (2005). Sira Vegas and colleagues (Vegas et al., 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. 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). If your instrumentation is not acceptable at a minimal level, then the findings from the study will be perfectly meaningless. QtPR is also not design research, in which innovative IS artifacts are designed and evaluated as contributions to scientific knowledge. There is a vast literature discussing this question and we will not embark on any kind of exegesis on this topic. Reliable quantitative research requires the knowledge and skills to scrutinize your findings thoroughly. In this context, loading refers to the correlation coefficient between each measurement item and its latent factor. (1979). Surveys thus involve collecting data about a large number of units of observation from a sample of subjects in field settings through questionnaire-type instruments that contain sets of printed or written questions with a choice of answers, and which can be distributed and completed via mail, online, telephone, or, less frequently, through structured interviewing. The p-value below .05 is there because when Mr. Pearson (of the Pearson correlation) was asked what he thought an appropriate threshold should be, and he said one in twenty would be reasonable. 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). 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. Importance of ICT Information and Communication Technology (ICT) is a blanket term encompassing all the technologies and services involved in computing, data management, telecommunications provision, and the internet. In fact, IT is really about innovation. In effect, one group (say, the treatment group) may differ from another group in key characteristics; for example, a post-graduate class possesses higher levels of domain knowledge than an under-graduate class. ICTs stand for information and communication technologies and are defined, for the purposes of this primer, as a "diverse set of technological tools and resources used to communicate, and to create, disseminate, store, and manage information.". Grand Canyon University offers a wide variety of quantitative doctoral degrees to help you get started in your field. Another problem with Cronbachs alpha is that a higher alpha can most often be obtained simply by adding more construct items in that alpha is a function of k items. Therefore, QtPR can involve different techniques for data collection and analysis, just as qualitative research can involve different techniques for data collection (such as focus groups, case study, or interviews) and data analysis (such as content analysis, discourse analysis, or network analysis). Straub, D. W., Boudreau, M.-C., & Gefen, D. (2004). necessarily reflect the official policy or position of Grand Canyon University. Bollen, K. A. ), The Handbook of Information Systems Research (pp. This methodology is primarily concerned with the examination of historical documents. Manipulation validity is used in experiments to assess whether an experimental group (but not the control group) is faithfully manipulated and we can thus reasonably trust that any observed group differences are in fact attributable to the experimental manipulation. One form of randomization (random assignment) relates to the use of treatments or manipulations (in experiments, most often) and is therefore an aspect of internal validity (Trochim et al., 2016). But Communication Methods and Measures (14,1), 1-24. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. McNutt, M. (2016). However, critical judgment is important in this process because not all published measurement instruments have in fact been thoroughly developed or validated; moreover, standards and knowledge about measurement instrument development and assessment themselves evolve with time. Lawrence Erlbaum Associates. It can include also cross-correlations with other covariates. John Wiley & Sons. Flourishing for a brief period in the early 1900s, logical positivism, which argued that all natural laws could be reduced to the mathematics of logic, was one culmination of a deterministic positivism, but these ideas came out of a long tradition of thinking of the world as an objective reality best described by philosophical determinism. The number of such previous error terms determines the order of the moving average. Quantitative research is focused specifically on numerical information. 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). Shadish et al. Communications of the Association for Information Systems, 13(24), 380-427. Construct Validity in Psychological Tests. Gefen, D., Ben-Assuli, O., Stehr, M., Rosen, B., & Denekamp, Y. 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