In academia, studies are conducted to investigate how variables are related. The researcher must select relevant data and make theoretical assumptions that connect with the research questions. Thus, the research question is the basis for any study. In their research, Long, Malhotra and Murnighan (2011, p. 2) investigated the effect of “economic education on greed”.
The aim of this paper is to analyse the research design used by the authors to test their hypotheses. Divided into seven parts, the paper analyses the hypotheses, assumptions, design, sampling, and methods used in the research. The paper concludes by discussing the contribution of the research to existing knowledge of the topic and to practice and policy.
Research questions, theoretical, and practical relevance
As stated in the previous section, the research investigated the influence of economic education on greed. Although the authors did not clearly state a research question, the study analysed how students’ academic backgrounds in economics influenced their greed. Long et al. (2011) developed two hypotheses for their study.
The first hypothesis posited that growth in economic training positively influenced greed and negatively influenced concerns for fairness, while the second suggested a positive perception of greed amongst economists (Long et al. 2011, p. 4).
The importance of the research cannot be overemphasised. Despite growth in economic courses in business academic curricula, a financial crisis was experienced between 2008 and 2010. The inevitable role of economists in the prediction and aversion of the economic crisis necessitates an investigation of the influence of curricula on financial behaviour.
Greed was one factor that contributed to the economic crisis. A wave of misappropriations and poor economic ethics crashed financial markets globally. The inherent behaviours of economists cannot be similar. The possibility that exposure to economic curricula influences the financial behaviour of people necessitated the research. Conducted in 2009 and published in 2011, the study was timely and shed light on the role of behavioural features on financial misappropriation and the global economic crisis.
The epistemological and ontological assumptions
Philosophical perspectives affect researchers’ assumptions and guide the design of the study. This section of the paper analyses the epistemological and ontological perspectives characteristic to the research being investigated.
Before identifying the type of ontology applied in the research, it is necessary to explain ontology. Crotty (2003, p. 10) describe ontology as the study of existence related to the type of scenario investigated, the form of existence, and the structure of realism. Ontological assumptions refer to the traditions that investigate what can be analysed or the nature of authenticity (Harvey 2006).
Long et al. (2011) colleagues adopted a realistic ontology for their research. The realistic ontology conforms to physical existence and the researcher assumes the world is based on causes and effects (Uriah 2011). In the research, the authors presume that realisms in the world may affect other entities. Realistic ontology is obvious in the purpose of the research.
The researcher investigation of the influence of economic curricula on greed satisfies the condition for realistic ontology. Realistic ontological assumptions define what has occurred, either to predict future activities or to relate the effects of realism on other factors (Pring 2004). This characteristic is obvious in the aim of the research targeted at analysing the influence of students’ exposure to academic curricula on their perception of greed.
Thus, the researchers investigated how students will behave if they were exposed to specific academic curricula. Their presumption, that an increase in students’ greed may be connected to their curricula, places their research in the sphere of realistic ontology.
Unlike ontology, epistemology is a method of identifying and describing how knowledge is achieved (Crotty 2003, p. 3). Epistemology provides a theoretical basis for determining the available forms of knowledge and the methods for ensuring the sufficiency and genuineness of information (Crotty 2003, p. 8).
Long et al. (2011) colleagues adopted an objectivist epistemology for their research. Crotty (2003, p.8) that knowledge, and therefore significant realism, exists beyond the functioning of any mindfulness (Wellington 2000). Thus, the researcher’s mind is perceived to be abstract and unaware of the explored subject. In the research, Long et al. (2011) detached themselves from the substances they were investigating.
They were investigating the influence of academic curricula on students’ greed. The researchers resolved that the students’ academic curricula affected their level of greed. At that point, the researcher asserted that they knew of how things existed and functioned (Pring 2004).
This section investigates the research design the researchers used. Research designs may be quantitative, qualitative, or mixed. Quantitative research designs draw conclusions by sourcing and analysing numerical data (Creswell 2012). Conversely, qualitative research designs draw conclusions by sourcing and analysing non-numerical data (Ader, Mellenbergh & Hand 2008).
The mixed research design integrates qualitative and quantitative methods. Long et al. (2011) used a mixed research design in their study. The mixed research design is a hybrid of the qualitative and quantitative research designs. The authors achieved this by dividing the research into three sub-studies.
A quantitative research design was used in the first sub-study and tested the first hypothesis. The participants’ behaviours were evaluated using the Dictator Game (Long et al. 2011). Only numerical data were derived from this method. A mixed research design was used in the second sub-study, which tested the results of the first sub-study and investigated the relationship between economics curricula and participants’ greed.
Qualitative and quantitative data were collected and used to analyse participants’ personal and general perceptions of greed. Similar to the second sub-study, the third research used a mixed design to collect and analyse participants’ responses. Through this multifaceted mixed research design, the researchers tested the hypotheses and successfully responded to the research question.
As earlier stated, quantitative research designs comprise hard statistics and verifiable data (Gorard 2013). Conversely, qualitative research designs comprise subjective data, typically comprising observation and elucidation of data through ethnography and individual conversations (Creswell 2012).
Current methods of research design comprise the integration of quantitative and qualitative designs, referred to as the mixed technique. The mixed research design is peculiar because it allows researchers to harness the advantages characteristic to qualitative and quantitative research designs (Guest 2013). Long et al. (2011) fully utilised the mixed method in the second sub-study.
The authors started their mixed research design with a qualitative design. The qualitative design enabled the researchers to offer elusive elements that defined the problem. This was followed by a Likert survey, which validated the findings of the previous stage. One disadvantage of the mixed research design in the study was that it downgraded qualitative examination of an investigative instrument (Morgan 2014).
Also, the mixed method failed to utilise quantitative examination to investigate and outline the issue and create possible results. Despite the disadvantage, using a qualitative or quantitative method may have enabled the researchers to only investigate the cause and effect of academic curricular on students’ greed. However, by using the mixed research design, Long et al. (2001) offered a wider understanding of the problem.
The quantitative analysis, via the Likert surveys, revealed information that was not clarified during the observations. Qualitative method also helped the researcher understand the participants’ perceptions of greed. Three researchers contributed to the study. Personalities differ and it is possible that the researchers had preferred research methods.
Practical researchers prefer definitive responses, such as those provided by quantitative studies. Conversely, flexible researchers are skilled in qualitative studies (Creswell 2012). The mixed research design used by Long et al. (2011) reduced the bias that may have emanated from the methodology.
The mixed research design influenced the data generated for the study, which indirectly improved the validity of the findings. Mixed research methods expand data sources beyond those of single methods (Creswell 2012). A combination of statistical examinations and qualitative observations made the study more inclusive. Although the mixed method offered provided broad data, different answers were generated, particularly through qualitative data.
The aim of the research was to investigate the influence of economic curricula on students’ greed however, qualitative research concentrated on several answers. Observations from qualitative observations provided valid, but varying information, yet valid.
Since the research was divided into three sub-studies, three sampling methods were used. This section appraises the sampling strategies used to select the sources of data for each sub-study. In the first sub-study, Long et al. (2011) used the stratified random sampling method.
In stratified random sampling, the researcher separates a specific model from the population and unsystematically chooses the participants for the research. Long et al. (2011) used the stratified random sampling method to select 112 participants for the first sub-study. The advantage of this sampling method is that is allows the researcher to generate primary data from a controlled group comprising individuals that should be investigated for the researcher.
Long et al. (2011, p. 13) selected “67 economic students and 45 education students from Midwestern University”. It was advantageous to use the random stratified sampling method since the researchers intended to identify the influence of economic curricula on students’.
For the second sub-study, the researchers used a simple random sampling to select 166 participants from Midwestern University (Long et al. 2011). The advantage of the simple random sampling method is that it allows the researcher to compare the perception of the target population to that of participants from other categories.
Although the researchers may have achieved in the previous study, the disadvantage is that economics and education students may have reported similar perceptions of greed. A simple random sample was necessary because it allowed the researchers differentiate participants’ perceptions of greed according to their course of study. According to Ling et al. (2011) reported that 34% of the participants were economics majors (p. 18).
The researchers used the stratified random sampling for the third sub-study. A sample of non-economics majors was separated from the population of Midwestern University and 92 participants were randomly selected. Long et al. (2011) used the random stratified sampling method for the third sub-study because it helped them investigate the perception of greed amongst non-economics majors.
Research methods for data analysis
Long et al. (2011) used different research methods to generate data from the selected participants. This section of the paper examines the methodologies used for data generation and their strengths and weaknesses in addressing the research questions or hypotheses. The first sub-study utilised a quantitative methodology to collect numerical data from the participants.
Long et al. (2011, p. 4) informed the participants that they would be allowed to make various decisions that comprised the “distribution of money between themselves and a randomly assigned counterpart”. Data collected reflected the sharing behaviours of the participants. Numerical data were derived by computing the average amount of money they kept when their distribution was either restricted or unrestricted.
In the second sub-study, Long et al (2011) used a hybrid of qualitative and quantitative methodologies to collect data. The participants were required to narrate two personal experiences, when they yielded and resisted greed respectively. They were asked to evaluate their behaviours using a 7-point Likert scale (Long et al. 2011).
An application of this methodology provided qualitative and quantitative primary data. Similar to the second sub-study, the research methodology provided the third sub-study with qualitative and quantitative data. Participants were exposed to narratives and asked to summarise what they had read.
Subsequently, they were required to provide their perceptions on a 7-point Likert scale. The mixed method was necessary for the second and third sub-studies because it provided the researchers apposite data to differentiate the perception and reaction of economic and non-economics majors to greed.
By applying the research methodologies described in the previous section, the researchers collected qualitative and quantitative data. The application of apposite analytical approaches helped the researchers to respond to test the hypotheses and draw their conclusions. Even though the researchers were exposed qualitative and quantitative data, they limited their analysis to numerical statistics.
Long et al. (2011) used the qualitative data as a basis for deriving quantitative data. In the first study, they tested the first hypothesis by statistically comparing the greed between economics and education majors. In the second sub-study, the researchers performed a correlation analysis between students’ majors and greed using Cronbach’s correlation.
Similarly, the researchers used Cronbach’s correlation analysis to investigate the general level of greed amongst non-economics majors. The researchers compared the findings of the three sub-studies to conclude that economics majors positively perceived greed when compared to their non-economic counterparts.
Quantitative analyses are performed using data generated from numbers. Although their research design generated qualitative and quantitative results, Long et al. (2011) used quantitative tests to analyse all data. Quantitative data analysis has strengths and weaknesses.
Since quantitative data are numerical, they are easier to analyse and allow simplified visual analysis (Popper 2004). Through visual analysis, quantitative data are simplified. Despite these strengths, quantitative data are not current. Long et al. (2011) based their analysis on students’ options on Likert scales. Likert questionnaires apply psychometric analysis to test perceptions and behaviours.
The participants were required to choose how much they supported or opposed each question. Using Likert scales has advantages and disadvantages. A significant strength of using Likert surveys is the universality of the methods, which make data easily understandable.
Quantitative data made it easy for Long et al. (2011) to test the correlation between students’ academic majors and their perception of greed. The Likert results forced the participants to be unbiased in their responses since they were restricted to limited options. Long et al. (2011) easily analysed the relationship between students offering economics and greed by correlating the mean values participants’ Likert responses.
Quantitative data enabled the researchers to collate and analyse the results in a short time since the responses were close-ended. The close-ended questions made it easy for the participants to answer to the questionnaire, which improved the response rate and enhanced the validity of the research.
Despite the advantages of numerical data generated, the single dimensional nature of Likert surveys reduced the researchers’ ability to identify other opinions of the participants. The participants were provided with specific options causing intermediate spacing between the responses.
Consequently, Long et al. (2011) failed to test participants’ actual perceptions. An initial question may inspire other questions. Restricting participants to specific questions prevents a wholesome representation of their perceptions (Burns & Burns 2008). The researchers failed to identify the inherent perceptions of the participants, which restricted the options and reduced the validity of the study.
Contribution of the Research
The possibility that exposure to economic curricula influenced the financial behaviour of people necessitated the research. The study contributes to practice and policy because it exposes the influence of curricula on economic students’ ethical behaviours. Economics majors were found to exhibit higher levels of greed than their counterparts, therefore exposing global financial markets to possible misappropriations.
The study contributes to academia by providing valid evidence of the need for an improved economic curriculum. Academia can modify policies and curricula that may reduce the influence of economic subjects on students’ greed. The findings of the research exposed the need for further study of the socio-psychological effects of students’ academic majors.
Greed is a socio-psychological feature of individuals. In their research, Long et al. (2011) investigated how exposure to historical and modern economic subjects and classroom discussions influenced students’ greed. The objective of their research exposed the need for educators to look beyond the academic effects of curricula and consider the social and psychological changes in students’ behaviours.
Although the research exposes the need for modifications in economics curricular, it is important for academia to cooperate with professionals when creating or modifying subjects. It will be futile for academic circles to discontinue basic economics subjects and principles to reduce students’ greed.
Professionals and academia should cooperate to expose economics majors to courses that propagate the ills of greed. By reducing the perception of greed among students, academia will securely expose students to economic principles. Thus, students acquire the knowledge apposite for economic professionals without necessarily becoming greedy.
In their research, Long et al. (2011, p. 2) examined the effect of “economic education on greed”. Increase in misappropriations and poor economic ethics crashed financial markets globally in 2009. The researchers exposed the need to select relevant data and make theoretical assumptions that connect with the research questions.
Thus, exposing the importance of the research question is in every study. The researchers concluded that exposure to economics curricula increase students’ greed. The research is important for future studies because it exposes effect of school curricula on students’ behaviours.
Ader, H, Mellenbergh, G, & Hand, J 2008, Advising on research methods: a consultant’s companion. Johannes van Kessel Publishing, Huizen.
Burns, A & Burns, R 2008, Basic Marketing Research, New Jersey, Pearson Education.
Creswell, J 2012, Educational research: Planning, conducting, and evaluating quantitative and qualitative research, Prentice Hall, Upper Saddle River, NJ.
Crotty, M 2003, The Foundations of Social Research: Meaning and Perspectives in the Research Process, Sage Publications, London.
Gorard, S 2013, Research Design: Robust approaches for the social sciences, SAGE, London.
Guest, G 2013, ‘Describing mixed methods research: An alternative to typologies’, Journal of Mixed Methods Research, vol. 7 no. 11, pp. 141-151.
Harvey, F 2006, Encyclopedia of Human Geography, SAGE Publications, Inc., Thousand Oaks, CA.
Long, W, Malhotra, D, & Murnighan, J 2011, ‘Economics Education and Greed’, Academy of Management Learning & Education, vol. 10 no. 4, pp. 643–660.
Morgan, D 2014, Integrating qualitative & quantitative methods: A pragmatic approach, Sage, Los Angeles, CA.
Popper, K 2004, The Logic of Scientific Discovery, London, Routledge.
Pring, R 2004, Philosophy of Educational Research, Continuum, London.
Uriah, K 2011, ‘Two defenses of common-sense ontology’, Dialectica, vol. 65 no. 2, pp. 177–204.
Wellington, J 2000, Educational Research: Contemporary Issues and Practical Approaches, London, Continuum.