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The purpose of this paper is to investigate a survey on critical success factor for the maintenance of local public buildings and how reported score values and factor rankings depend on characteristics (contingencies) of the local governments that participated.

The authors use data from a large-scale survey of Norwegian local governments that covered 66 per cent of all local governments and 80 per cent of the population. The authors combine these data with contingent information from public registers on demographics, fiscal, political and geographical characteristics. The authors run regressions to determine whether contingencies affect survey results. They further study how score values vary with a key contingent factor.

The main result of this paper is that the reported importance of critical success factors is contingent on local government population levels. A comparison of importance rankings based on population quartiles shows that ranking orders change, both between quartiles and from the overall ranking, and that certain factors show systematic changes. Further, the authors find that when controlling for sampling error, groups of factors should be considered as equally important. This result holds both for the full sample ranking and for rankings within population quartiles.

The results of this paper have implications for all survey-based investigations of critical success factors where contingent information on respondents are available. Contingencies need to be taken into consideration, both when assessing rankings according to some criteria and when comparing actual score values.

The purpose of this paper is to discuss rankings of critical success factors (CSFs) from survey data, both with respect to what information such rankings should be based on and how to evaluate and interpret uncertainty from sampling errors.

The authors conducted a survey on CSFs in public facilities management. The survey data set covers two-thirds of all Norwegian local governments and 80 per cent of the Norwegian population. The authors analyze the data using basic statistics and bootstrap sampling techniques.

Rankings of CSFs are sensitive to the information one chooses to collect in the survey. With the survey data, the authors show that the typical approach of inquiring about importance of various factors leads to a different ranking of factors than if one inquires about cost efficiency. The authors further consider a ranking that reflects all information in the data; the authors look in particular at a ranking with equal weights to importance and cost efficiency. The authors also find that many factors, when controlling for sampling error, should be ranked equally, and that further considerations need to be consulted when priorities are decided.

The authors demonstrate the effect of cost efficiency and uncertainty considerations on rankings of CSFs for facilities management. The study paves the way for a broader and more comprehensive perspective on CSFs and what these factors should and could reflect.