A Hybrid Multiple-Attribute Decision-Making Model with Modified PROMETHEE for Identifying Optimal Performance-Improvement Strategies for Sustainable Development of a Better Life

Abstract

Governments worldwide are cognizant of the deficiencies of measuring quality of life according to gross domestic product; consequently, they have created indicators of citizen well-being that can be applied in governmental policy. To improve citizens’ lives, governments should create an environment with maximal quality of life, ideal material living conditions, and sustainable well-being and determine the true needs of citizens. This paper proposes a hybrid multiple-attribute decision-making model with a modified PROMETHEE method that can identify practical performance-improvement strategies for the sustainable development of a better life by accounting for the complex dependencies among the indicators. In the proposed model, an influential network relation map is first obtained using the DEMATEL method to delineate the interrelationships among the indicators. Second, to address the feedback and dependence concerns associated with interrelationships among criteria, the influence weights are identified through the DANP method. Finally, the degree of preference is determined through the modified PROMETHEE method and combined with the influence weights to calculate flow indicators, which facilitate attaining the aspiration level. The aspiration level is set and an aspiration alternative is identified as an improvement benchmark to facilitate continual melioration and sustainable development of a better life. This model uses the OECD well-being indicators consisting of 11 dimensions and 24 criteria to measure material living conditions (namely housing, income, jobs) and quality of life (namely civic engagement, community, education, environment, health, life satisfaction, safety, and work–life balance). An empirical case study was performed to illustrate the feasibility and effectiveness of the proposed model by using questionnaire data of six cities in Taiwan. Our results prove that the proposed model (aspired-worst as benchmark) outperforms the traditional model (max–min as benchmark) and that it can obtain more realistic net flows and an improvement benchmark to conduct ranking, selection, and continual improvement for facilitating sustainable development of a better life.