Validity and reliability of case study method

A set of criteria is employed in order to gain the desired level of acceptable research validity and to achieve credibility (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001). The study‘s validity and reliability are evaluated on the ability of the researcher to abide by a number of key design checks and to adhere to good academic research practices (Amaratunga & Baldry, 2001). Although terms such as validity and reliability are derived from a quantitative and scientific research foundation, they can still be flexibly incorporated to evaluate the credibility of a qualitative research study striving for reliability (Carter, 1999). For the most part, validity and reliability are evaluated in accordance with Yin‘s (1994) proposed qualitative case study design tests of construct validity, internal validity, external validity and reliability to establish a level of research

quality needed to gain reliability and overall credibility, as seen in Table 3.5 (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001).

Table 3.5 Validity and reliability of case study research

Tests Case study tactics Phase of research in which

tactics occurs Construct validity Use multiple sources of evidence

and triangulate these sources Establish chain of evidence Ask key informants review draft Develop case study report

Data collection

Data collection Composition

Internal validity Perform within-case study analysis, then pattern matching

Perform explanation building, searching for the ‗why‘ behind the relationship

Conduct time-series analysis

Data analysis

Data analysis

Data analysis

External validity Use replication logic (not sampling) in multiple-case studies

Research design

Reliability Use case study protocol Develop case study database

Data collection Data collection

Source: adapted from Parkhe (1993) and Yin (1994)

Construct validity

The first quality measure is that of realism construct validity. This measurement is similar to construct validity of a positivism study, as it reviews the information within the construct of a particular theory. For this study, prior theory from parent disciplines including international marketing, growth, and Internet marketing literature is triangulated (Healy & Perry, 2000). However, no construct should be guaranteed in the development of a theory, as the researcher should attempt to leave behind any bias of preordained theoretical perspectives behind them (Eisenhardt, 1989). The researcher must identify and evaluate the possible important issues pertaining to the research problem. Therefore, the mindset of openness limits bias as much as is possible (Eisenhardt, 1989). To achieve this level of construct validity, the research establishes the appropriate operational measures for the pertinent issues within the study (Amaratunga & Baldry, 2001). These measures are produced by using multiple sources of information, establishing a chain of evidence through data collection, and triangulating the data (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001). This research project obtains construct validity by incorporating all evidence concerning international market

growth from secondary sources (literature) and from the analysis of primary sources (case studies interviews) then triangulating the evidence convergence through a Stage II structural equation modelling process (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001).

Internal validity

The second of the criteria for research quality is that of internal validity (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001). Internal validity verifies that a true and correct relationship has been established, rather than fake or untrue effects (Yin, 1994; Carter, 1999; Amaratunga & Baldry, 2001; Amaratunga, et al., 2002). If the research investigator draws incorrect conclusions about relationships that do not truly exist, then the built or constructed theory is inappropriate and flawed (Yin 1994). In case study methodology, however, this logic is not as important as in a quantifiable study. Exploratory studies such as case studies are not necessarily concerned with a causal statement (Yin, 1994; Amaratunga & Baldry, 2001). To address incorrect conclusions, this investigator will question the correct influences, consider rival explanations and possibilities, and converge all evidence with a high level of precision (Yin, 1994; Amaratunga & Baldry, 2001). Questions of low internal validity are overcome by the tactics of data analysis pattern matching and explanation building, which will essentially weed out weak explanation, as illustrated in Table 3.5 (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001).

External validity

The third measure of quality in this Stage I is external validity, which concerns itself with the ability of the research to be generalisable and applicable to an external environment (Parkhe, 1993; Yin, 1994; Carter, 1999). Therefore, the findings from this study may be applicable to other settings and situations. External validity can be achieved by identifying theoretical relationships (Amaratunga, et al., 2002). It is not the argued that theoretical generalisability can be applied to all international marketing situations; however, applications may be generalisable to Internet international growth decisions.

Higher external validity is achieved by using the research tactic of replication logic in multiple-case study data collection (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001). Replication logic includes both literal replication (predictions of similar results) and theoretical replication (predicted contrasting results for predicted reasons) (Parkhe, 1993; Yin, 1994; Healy & Perry, 2000).

These factors aid in giving analytical generalisability to the study over that of statistical generalisability objectives. A selection criteria is used to conform to the replication logic ideology which in turn ensures better external validity and greater analytical generalisability. Cases were chosen using standard criteria. These criteria included:

 companies with the same product orientation  companies with the same customer orientation and  companies of the same size.

Reliability

The final measure of quality in social science research in the study‘s reliability (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001; Amaratunga, et al., 2002). The reliability of the research is measured by the dependability of the findings. That is, all questions from the protocol about the Internet and international market growth are used to focus the study, whilst allowing relevant unanticipated issues to be drawn from the interviews (Carter, 1999). Thus, the study has a level of reliability if, in similar circumstances the same results and conclusions would have been found by another investigator (Amaratunga & Baldry, 2001). Further, a certain level of saturation is needed to draw out all issues from respondents about the research problem (Gummesson, 2004). As many cases as needed are used to gain redundancy. That is, redundant constructs are identified at the point of saturation, whereby any more cases would yield little or no better understanding (Gummesson, 2004). This research overcomes these reliability issues by using a case study protocol for the in-depth interviews and by developing a database of information in the data collection stage, as outlined in Table 3.5 (Parkhe, 1993; Yin, 1994; Amaratunga & Baldry, 2001).

With appropriate levels of appropriate validity and reliability established it is essential to elaborate and expand on the case study design chosen for this research study Section 3.3.7 outlines further case selection criteria used in this research.