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Arditi, D and Ongkasuwan, D (2009) Duties and Responsibilities of Construction Managers: Perceptions of Parties Involved in Construction. Journal of Construction Engineering and Management, 135(12), 1370–4.

Bayraktar, M E and Hastak, M (2009) Bayesian Belief Network Model for Decision Making in Highway Maintenance: Case Studies. Journal of Construction Engineering and Management, 135(12), 1357–69.

Braimah, N and Ndekugri, I (2009) Consultants’ Perceptions on Construction Delay Analysis Methodologies. Journal of Construction Engineering and Management, 135(12), 1279–88.

Davis, K A and Songer, A D (2009) Resistance to IT Change in the AEC Industry: Are the Stereotypes True?. Journal of Construction Engineering and Management, 135(12), 1324–33.

  • Type: Journal Article
  • Keywords: Change management; Information technology (IT); Construction industry;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000108
  • Abstract:
    Information technology (IT) change is difficult to implement successfully. Cultural (people) issues are a major barrier to IT implementation in the architecture, engineering, and construction (AEC) industry and existing change models have limitations, particularly with respect to cultural issues, which directly affect the ability of companies within the AEC industry to successfully implement IT change. This paper discusses research exploring the relationships between a resistance to change index (RTCI) and the demographics of individuals to understand different AEC participants’ resistance to IT change. Identifying individuals that exhibit different intensities of resistance to IT change efforts and their attendant demographics provides benchmark data to organizations. The ability to identify potential resistors is the first step in helping ensure that new technology implementations succeed. Data was collected from a 156-person sample of the AEC population to determine the relationships among different demographic groups within the AEC population and differences in their RTCI. The data analysis found several demographic groups that were different in their likelihood of resistance, including profession, gender, computer understanding and experience, and awareness of past or future changes occurring in their company. Age and education level were expected to have relationships with RTCI, based on industry stereotypes. The data analysis found that these stereotypes have no scientific basis. Two other stereotypes, gender and computer understanding and experience, were supported by the data analysis.

Fong, P S W and Kwok, C W C (2009) Organizational Culture and Knowledge Management Success at Project and Organizational Levels in Contracting Firms. Journal of Construction Engineering and Management, 135(12), 1348–56.

Hallowell, M R and Gambatese, J A (2009) Construction Safety Risk Mitigation. Journal of Construction Engineering and Management, 135(12), 1316–23.

Lee, H, Shin, J, Park, M and Ryu, H (2009) Probabilistic Duration Estimation Model for High-Rise Structural Work. Journal of Construction Engineering and Management, 135(12), 1289–98.

Sacks, R, Treckmann, M and Rozenfeld, O (2009) Visualization of work flow to support lean construction. Journal of Construction Engineering and Management, 135(12), 1307–15.

Tuuli, M M and Rowlinson, S (2009) Performance Consequences of Psychological Empowerment. Journal of Construction Engineering and Management, 135(12), 1334–47.

Williams, R C, Hildreth, J C and Vorster, M C (2009) Highway Construction Data Collection and Treatment in Preparation for Statistical Regression Analysis. Journal of Construction Engineering and Management, 135(12), 1299–306.