Quantitative Research Methods Seminar with Professor Detmar Straub

In this session, I discussed the chapter 7 from the following book:

Author information:

Dr. Eugene F. Stone-Romero Professor Department of Management College of Business The University of Texas at San Antonio Phone: 210.458.5901 Fax: 210.458.5783 E-mail: eugene.romero@utsa.edu	Book Title: Research Methods in Organizational Behavior.
http://faculty.business.utsa.edu/eromero/	Chapter 7: Empirical Research Strategies

Abstract:

This chapter is about the research strategies we can employ to understand and explain some phenomenon of interest. The strategies are contingent on research purpose. The research purpose can be different based on research settings (natural vs. simulated), generalizability (particular vs. general), control over independent and nuisance variable, artifacts such as subjective influence on the outcome of study, differing degree of contact between the researcher and the system being studied, strength and range of studied variable (e.g. higher in natural setup than contrived setting), and types of costs (high vs. low). Afterward, as shown in the following table, the chapter discusses comparison between different dimensions and research strategies, such as laboratory experiment, simulation, field experiment, field study, sample survey, and case study. Finally, suggests that the choice of research strategy should be guided by the purpose of the research, the resources available to the researcher, other considerations, such as internal and external validity, ethical and legal issues, etc.

Rated Dimension	Laboratory Experiment	Simulation	Field Experiment	Field Study	Sample Survey	Case Study
COST: Initial  Setup Marginal Cost per subject	M L	L-H L-H	M-H M	M-H M	H L-H	L-H L-H
VARIABLES: Strength of independent variable Range of variables Potential to manipulate independent variables	L L H	L-M M M-H	M M M	H H N	H H N	H L-H N
CONTROL: Potential for testing causal hypothesis Potential for study to change researcher Potential for controlling confounding variables	H L H	M-H L M-H	M M L-M	L M L	L L L	N H N
ARTIFACTS: Potential for experimenter expectancy effects Potential for demand characteristics Potential for evaluation apprehension	H H H	M M M-H	M-H M-H M-H	M M M	L L L	H H H
SETTING: Naturalness of setting Degree to which behavior is setting-dependent	L H	M-H L-M	H H	H H	H L	H H
GENERALIZABILITY: Applicability of study’s results to different populations	L-H	L-H	L	L	H	N

  N: None,         L: Low,            M: Moderate,              H: High

Critique of the material:

From the perspective of an interdisciplinary research area like ICT4D, I found it difficult to establish a causal relation, for instance, the relation of x (some technology) causes y (some kind of development) is elusive. The problem in ICT4D domain is a kind of circular loops. For instance, it is difficult to say whether x causes y or y causes x. Therefore, experimental studies seem less reliable for this kind of interdisciplinary and complex studies. In addition, it is very difficult to get an ideal condition for variable measurement. Generally, positivist approaches fall into New-Newtonian paradigm. Where, the phenomena under study are somehow controllable, predictable, and generalizable. On the contrary, realities of subject in real world are contextual, complex, diverse, dynamic, uncontrollable, and unpredictable (Robert Chambers, 2010), interfered by many nuisance variables. Therefore, it is difficult to affirm that some particular paradigm or methodology is dominant in interdisciplinary (ICT4D) research domain.

Having said that we cannot disregard the quantitative tradition, especially when funding institutions are more lured by numbers rather than descriptions. Again as chapter suggests trade-off is important. My personal experience with research strategies is that we cannot depend on single paradigm, theory, or methodology particularly in the context of interdisciplinary research. I believe in adaptive pluralism. The trade-off in the wider sense, including theories, methods, and techniques. For instance, survey can be used with qualitative case studies to better understand and explain the complex phenomena. Similarly, experimental studies with other complementary methods can be used to understand the student learning behavior before and after ICT intervention, for example.

In sum, I always found it bit lopsided to discuss either quantitative ‘OR’ qualitative methods, but instead of ‘AND’. There is a call for mixed method approaches; likewise, top journals should keep a positive outlook towards the mixed methods.

Key questions for discussions: 

·         As per this chapter, we always need to make compromises either with control of variables or naturalness of settings. Does this compromise mean that infidelity between research findings and the reality will always remain?

·   How to choose a better research strategy, considering the tension between resource constraints, such as time, funding, knowledge, supervision, publication, etc., and research interest?

·   How to justify our research strategy and findings in between these dilemmas of understanding, explaining, innovating, or predicting the phenomena?

·      What is the take for interdisciplinary research like ICT4D from this session? There is an epistemological challenge because the realities of subjects in the ICT4D researches are local, complex, diverse, dynamic, uncontrollable, and unpredictable.