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ERP summary
Summary about empirical research methods
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EMPIRICAL RESEARCH PROJECTLECTURES AND TUTORIALS
WEEK 1
LITERATURE
G. Tomas M. Hult, David J. Ketchen Jr., David A. Griffith, Brian R. Chabowski, Mary K. Hamman, Bernadine Johnson
Dykes, Wesley A. Pollitte and S. Tamer Cavusgil (2008). An assessment of the measurement of performance in
international business research, Journal of International Business Studies, 39(6), 1064-1080.
http://www.jstor.org/stable/25483322
ABSTRACT
IB research is devoted to building knowledge about the determinants of organizational performance. A precursor to
accurate diagnose the reason some organizations succeed in the international marketplace while others struggle is
operationalizing performance. The findings reveal that most studies do not measure performance in a manner that
captures the multifaceted nature of the construct. We describe the implications of these results and offer
suggestions for improving future practice.
INTRO
The specific purpose of the paper is first assessing the measurement of performance in IB research relative to 3
dimensions : sort of data sources (primer or secondar) – sort of measure (financial or operational and the
effectiveness) – level of analysis (firm level – strategic business unit (SBU) level – or interorganizational level) and
second we offer guidelines for future research that are intended to assist the field in maximizing its potential for
building knowledge regarding the reason some firms outperform others in the global arena.
METHODOLOGIES
To asses performance research in the IB literature parameters were established to set the boundaries for the
research undertaken in this paper. To select the journals to be included parameters were used for selecting top-
rated journals. The data collection proceeded in accordance with content guidelines. Each article was categorized
with sorts of performance measure and articles were also coded based on data source.
RESULTS
Sorts of data source
Of the 96 studies examined two studies used both sorts of data sources. Each of the remaining studies used either
primer measures or secondar measures (primer data refers to subjective data and secondar data refers to
objective data). To further assess the data sources used in IB research the data were examined across time periods.
The findings of the time segmentation indicates that the proportion of studies in the overall sample that used
primer data to measure performance was 62.1 percent during 1995-1999 and 54.2 percent during 2000-2005.
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, Sorts of measure
Findings related to the sorts of measure used (financial – operational – and effectiveness) indicate that 0.07
percent of the studies used all three sorts of performance measurement. The use of two sorts of performance
measure was more common but these studies constituted sole 32.2 percent of performance research over the 11
annum period. In addition a measurement over time indicates that the number of studies using performance
measures of a single sort was 59.5 percent during the first 5 annums and 59.3 percent during the remaining 6
annums.
Level of analysis
Given the interrelated nature of the three performance dimensions investigated the level of investigation issues
were examined in relation both to sort of data source and to sorts of performance measure. The data indicated
that studies focusing on IB issues have relied to a greater degree on primer rather than secondar measures. Four of
the five studies of inter-organizational unit performance using secondar data used financial measures although the
actual measures varies across studies both for studies using primer data and for studies using secondar data.
The most common SBU performance measures were sales based : 66 percent of SBU performance studies using
primer data and 75 percent of those using secondar data used sales based measures. Examining the data
longitudinal studies of firm and financial performance were 38.5 percent during 1995-1999 and 30 percent during
2000-2005 whereas studies of SBU and financial performance were 75 percent during 1995-1999 and 63.6 percent
during 2000-2005.
Sole 0.01 percent of the studies measured performance at all three levels – 6.3 percent of studies measured
performance at two levels – and 92.7 percent of studies measured performance at one level. These results suggest
a lack of breadth in relation to performance measurement across units of investigation.
The measures most often used for financial performance regardless of level of investigation were sales based. The
dominance of measuring financial performance at the firm level was consistent throughout the 11 annum period
covered in the studies. The proportion of studies using financial measures was 70.3 percent during the first period
and 72.9 percent in the second period. Additional the proportion of studies using firm performance measures was
48.6 percent in the first period and 61 percent in the second period.
IMPLICATIONS
The findings indicate that five broad issues related to IB performance measurement should be considered in future
IB research. We view the following issues as an action plan for improving the measurement of performance within
the IB field. IB researchers should attempt to incorporate as much action items as possible into their research while
balancing research rigor with practical relevance.
Overcome reliabilities issues with primer and secondar data sources
Researchers might be suspicious of the validities of primer data sources but performance research in international
context indicated that primer data measuring performance can be more reliable than secondar data in certain
contexts. In situations where firms are hesitant to provide secondar performance data collecting primer data
provides IB researchers with better abilities to understand the values that a manager might place on specific
financial – operational – and overall effectiveness performance measures. Some researchers content that given the
different goals inherent across firms secondar measures can be misleading as to the firm focus on the performance
measures thus making primer measures more realistic than secondar ones in certain cases.
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, Improve IB research through measuring multiple sorts of performance
To advance knowledge of how performance is generated in international context and to generate normative
conclusions for practitioner use research should be based on specified measures of sort of performance to
minimize misleading results. The use of a single performance metric might help determine the drivers of a specific
aspect of performance in relation to a specified research question. As knowledge in the IB field deepens it is
important to use multiple sorts of performance measures to gain a more complete view of the nature of
performance.
Make valid causal inferences with proper longitudinal measures of performance
Longitudinal data should be used to assess the influence of a predictor variable on the criterion variable. The
appropriate time lag is of particular importance when using longitudinal research. Although longitudinal data is
preferred for establishing causalities limit data is available and the expense and difficulties of data collection make
longitudinal studies rare in IB research. To overcome the limitations researchers can use various methodological
solutions and researchers should consider using SUR models – SEM models – dynamic regression models – or
granger causalities testing to enhance causal inferences.
Improve inferential specificities in relation to level of analysis
IB research varies in the level of analysis in which performance is measured which creates both empirical and
theoretical concerns for the advancement of the field. Empirical inconsistencies in levels of analysis across studies
could explain the contradictories in IB literature. Examination of the unit of analysis when comparing empirical
findings across studies therefore becomes an important concern for drawing appropriate inferences. Theoretical
because arguments made at one level of analysis are not automatic generalizable to other levels of analysis. It is
therefore suggested to careful examine the level of analysis used in the theoretical development of hypotheses and
empirical generalization in relation to IB research focused on performance.
Resolve concerns with endogeneity and selection
Endogeneity and selection are important problems for IB performance researchers. Although IB research might be
limited through data availabilities statistical tools can often be used to address complications related to
endogeneity and selection. As a value-added element IB researchers should consider and report issues of
endogeneity and selection in their studies to allow future research the possibilities to more explore such issues.
LIMITATIONS AND CONCLUSION
Improving the effective measurement of performance is central to advancing the IB literature. Although limited
with its scope the studies provides an assessment of sorts of data – sorts of measure – and level of analysis of
performance measurement in the IB literature. The assessment revealed that performance has been studies in a
manner that often overlooks its multidimensional and multilevel nature. While these issues are often mentioned as
limitations within the extant literature we suggest that researchers move toward more effective measurement of
performance and greater specification and justification of its measurement. To this aim we offer a set of guidelines
for the advancement of effective performance measurement. It is important to note that the primer driver of the
measurement of performance is the basic research question posed and so our prescriptions for strengthening IB
research should be viewed as foundational guidelines and not as the specified standards to be applied to all IB
studies.
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, LECTURE
DATA AND MEASUREMENT
The research process :
- The research question (example : is there a positive association between number of lectures and tutorials
that students participate and their exam mark)
- Literature : with literature we can design a hypothesis
- Hypothesis : specific statement of prediction that is testable (example : the more lectures and tutorials a
student participates in the higher grades the student obtains). The number of lectures and tutorials a
student participates is the independent variable and the grade the student obtains is the dependent
variable.
- Collect data : measure the variables
- Analyze data : graphical or descriptive or through fitting a model or both
- Conclude : is the hypothesis true or not
Measurement is the relationship between the numbers and what is being measured : the information that is
provided with numbers. An example is age can be measured in months – weeks – hours but also in intervals such as
11-20 – 21-20 – 21-30 and so on or measure in child – adolescent – senior). Another example is education which
can be measured in average time of schooling – percentage of population that has completed a degree in education
– PISA test scores – or adult literacies. The basic issues in measurement are :
Validity is the extent to which a measure correct represents the concept of studies
o Internal validity is how well the studies was executed
o External validity is the extent in which the studies generalize results to other situations
Accuracy is the measure close to actual value and getting the right answer on average.
Reliability is the extent to which a variable is consistent in what it is intended to measure (would it gain the
same results in a second time).
Data can be organized :
- Cross-sectional : observations (households – firms – countries) at a given point in time for several
individuals
- Time series (see statistics II) : data-set that tracks an individual over time (GDP of the Netherlands since
1950)
- Panel (longitudinal) : observations (households – firms – countries) over a period of time
ARTICLE
The main question in IB literature is the reason some firms outperform others.
The main literature :
- Performance : important variable (often a dependent variable)
- Inconclusive results about determinants of performance
- Conclusions depend on the measurement of performance
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