Dynamic Performance Measurement

As mentioned in the literature review, evaluating the performance of an organisation entails considerable ambiguity and tends to attract methodological critiques (Amburgey et al., 1993). However the study of the performance consequences of change is increasing in popularity, and it plays a central role in a variety of theoretical approaches to organizations (Greve, 1999). As we mentioned, the dynamic time effect of performance is ignored in previous studies. Those who study change should examine historical and time varying information, as well as external variation (Sorensen, 2002, Clement, 1994).

Considering the methodological suggestions in prior researches, in order to measure the dynamic change effect on performance to test Proposition 3 and Proposition 4, the financial data records from company documents for change events were traced from 1994 to 2009. The evaluations for the effect of change on performance were obtained from interviews to further validate the results from financial data in this study. The time of change events was presented in months in this thesis. Yin (2009) recommends tracing events over time, which is the major strength of case studies. It supplies a good evidence for testing the propositions, such as the ability to track the dynamic performance before and after a change, and the possibility to check whether a predicted time matches an actual time.

Following the suggestions in Boeker (1997), Greve (1999), Haveman (1992) Miller and Chen (1994) and Singh et al., (1986), as we mentioned earlier, this study uses two financial variables to measure performance: turnover and net profit. Performance is measured at the level of the branch where the event took place. Moreover, considering the high speed of development research context, the growth rate of the branch where the change took place in the year of change was compared to the mean growth rate of the branch. As discussed in the introduction, China is one of ZRUOG¶V IDVWHVW JURZLQJ economies. Research validity would be lacking if the researcher ignored this specific

UHVHDUFKFRQWH[W&KLQD¶V*'3growth rate was also compared to the growth rate of the branch of the case organisation to account for the rate of general economic development and inflation in China.

Following the work of Haveman (1992), the changes were assessed over six-month periods for Propositions 3 and 4. As we discussed earlier, the financial data for change effects were assessed four times: 7±12 months before change, 1±6 months before change, 1±6 months after change, and 7±12 months after change (Eisenhardt, 1989, Haveman, 1992). The financial records were available semi-annually in the branches of the case organization, and all changes were assessed over six-month periods between June 1994 and June 2009.

For example, if a change was initiated in March 2002, the performance consequences will be assessed by turnover and net profits of that branch recorded in June 2002 (3 months after change) and December 200225 (9 months after change) as the instant performance consequence and the long term change consequence respectively. The pre-change performance will be assessed by the financial records in December 2001 (3 months before change) and June 2001 (9 months before change). And if the change case took place in August 2002, the effect of change will be assessed against the data of December 2002 (4 months after change) and June 2003 (10 months after change) as instant and long term effect; the pre-change condition will be measured by the financial record of June 2002 (2 month before change) compared with the data of December 2001 (8 months before change). Hence, for the data constructed for the analysis of financial performance, some first assessments of performance in selection to a change may be three months long (March, 2002 to June, 2002), while some are four months long (Aug 2002 to Dec, 2002); because it is unlikely to precisely identify the finishing points of each single change. This will not influence the validity of the results of the study as it is assumed that the changes do not consume equally spaced time periods, as indicated by Haveman (1992).

25 _{The original financial data in each December was annual, the data of each December showed in this study that the}

annual financial record took away the financial record of January±June of those years, which means the financial performance for second half of year (July±December).

In this way, to test Proposition 3, the dynamic change consequences on performance were evaluated by examining the instant change effect (1±6 months after change) and the long-term change effect (7±12 months after change) to capture the dynamic performance variation. Furthermore, the financial data assessments model for change consequences on performance were validated by the evaluation from manager informants who experienced the changes and had knowledge of the change effects at every step. Then the frequency counting technique was used to get the mean effect for the instant change effect and the ORQJWHUP FKDQJHHIIHFWIURPWKHPDQDJHUV¶SRLQWRI view.

To examine the first part of Proposition 4 - the role of pre-change conditions in change initiation, the trends of branch turnover and branch net profit in 1±6 months before a change were compared with the data of 7±12 months before a change. Branch growth rate was further used, for this part of testing, branch growth rate is the percent growth in turnover for the branch in the year ahead of change. This percentage increase in then compared with the average annual rate of growth in turnover for the branch of the case organization. Then it can be observed whether the speed of development in a year ahead of change was higher or lower than the average development speed. Poor pre-change performance is defined in this study as when at least one of two financial variables were lower than before (comparing the financial data of 1±6 months before change, with 7±12 months before change), and the growth rate in a year ahead of the change event was lower than average.

To examine the last part of Proposition 4, the reverse relation between pre-change condition and after change performance was assessed. It was measured by the trends of the two financial variables in the branch where the change took place, and the growth rate before the change with that after the change. The trends of two financial variables before the change were defined by comparing the data in 1±6 months ahead of change with the data in 7±12 months ahead of change, in order to capture whether it was increasing or decreasing before the change. The trends of two financial variables after

the change were concluded by comparing the data in 1±6 months after the change with those in 7±12 months after the change, to check whether it was an increasing or decreasing trend. Consequently, two trends before and after change were both defined by a one year lag, and then they can be compared to check whether there was a reverse situation.

Similarly, branch growth rate in the year of change took place was also used. The percent growth in turnover for the branch in the year the change took place was obtained, this percentage was then compared with the average annual rate of growth in turnover for the branch of the case organization. Then it was observed whether the speed of development in a year of change was higher or lower than the average development speed. We know whether the growth rate one year ahead of change was higher or lower than average from the results of the first part of Proposition 4, and so we can assess if the growth rate in the year of change was higher or lower than average, now we can compare these two trends to check whether there was a reverse situation or not before and after change indicated by the branch growth rate.

Eventually, according to regression toward the organisational unique mean, the performance reverse situation predicted in Proposition 4 and can be checked by comparing the trends of branch turnover, branch net profit and branch growth rate before change with those after change. The details examples will be supplied with the numbers explanation. Also the results by this model of assessment were validated by the results of the interview responses.

Finally, by following this operational strategy and the procedures in analysing the qualitative data of this research, any differences were contrasted, comparisons to rival explanations were made, and threats to internal validity were checked within each individual case. A replication logic was applied to the 15 change cases. Consequently, pattern matching could be achieved in relation to the results of the 15 change events, and significant explanations for the outcomes can be developed in this study (Yin, 2009).

The next section will discusses the results from the empirical data regarding the effect of previous change experiences on the likelihood of re-adopting the same type of