Fatores de influência nas pessoas para a mudança de processos organizacionais: um estudo sobre sua identificação e importância

• Ano de defesa: 2014
• Autor(a) principal: Reys, Léa Simone Friedmann dos
• Orientador(a): Albertin, Alberto Luiz
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Gestão por processos; Reengenharia; Gestão da mudança; Fatores críticos de sucesso; Fatores de influência; Análise conjunta; Análise de preferência; Comunicação; Capacidade da organização; Justiça organizacional; Envolvimento da alta administração; Suporte da alta administração; Impacto da mudança; Treinamento; Visão; Alinhamento estratégico; Autonomia; Empowerment; Conjoint analysis; Metodologia; Reconhecimento e recompensa; Suporte emocional; Business process management; Gestão de mudanças
• Palavras-chave em Inglês: Adaptive conjoint analysis
• Link de acesso: https://hdl.handle.net/10438/11836

Process Management is identified as an effective strategy to achieve results in the organization. The achievement of desired changes requires changes to existing business processes. People are the only common element in process and change management. The achievement of expected benefits requires a focus on the efforts required to obtain the support of affected people. The literature review revealed over one hundred factors which affect change. These factors were classified in to four distinct groups, namely: Type I individual characteristics, Type II individual characteristics, organizational characteristics and influence factors. Influence factors have a direct impact on the individual. The factors identified were subsequently classified into the 15 factors or attributes used for the empirical study. The first qualitative study selected, from the 15 attributes, the 10 most important factors which influence individual change. These 10 factors were subsequently used for the internet study whose objective was to identify the relative importance of these factors. Two methods were used to estimate the importance of each factor for each individual participating in the study, namely: Adaptive Conjoint Analysis (ACA) and Ordering. The use of Cluster Analysis used similarity analysis to identify 2 to 10 groups together with resulting relative importance scores. These groupings were subsequently contrasted with control variables and whether the change, analyzed by the individual, was the result of a demand from Information Technology. For those groups formed through the use of ACA, there are indications that the control variables and the change driver have an impact on the behavior of the individual. For those groups identified though ordering analysis, the results obtained reveal, with minor exceptions, that neither the control variables nor the change driver have an impact on the behavior of the individual. The application of Friedman non parametric test and multiple comparisons of Dunn-Bonferroni for prioritizing the importance scores calculated through the ACA method, revealed the existence of two distinct groups. Ordering analysis revealed the existence of three groups with differing attribute or factor prioritization.