How Fuzzy Comprehensive Evaluation Enhances Construction Worker Safety Psychology

Fuzzy Comprehensive Evaluation Method

Fuzzy comprehensive evaluation is a method based on fuzzy mathematics that converts qualitative assessments into quantitative ones using membership theory, providing clear, systematic results suitable for non‑deterministic problems.

The core elements are:

Factor set – collection of evaluation indicators

Evaluation set – collection of rating grades

Weight – quantitative importance of each indicator

Membership function – relationship between indicator values and rating grades

When these elements are defined, the fuzzy evaluation process can be applied. The article illustrates the method through a case study of construction worker safety‑psychology assessment, emphasizing the full research workflow.

Research Problem

Construction projects have long cycles, many high‑altitude tasks, frequent changes, and harsh environments. Workers face heavy manual labor and must possess fatigue resistance, logical thinking, coordination, and the ability to stay calm during accidents. Human unsafe behavior is the leading cause of construction accidents.

This study aims to build an assessment system and evaluation model for construction workers’ safety psychology.

Assessment System

Influencing Factors

Human attributes are divided into natural (individual) and social (collective) aspects. Individual aspects include psychological quality, ability, and moral character; social aspects reflect the person’s role in society.

Survey Questionnaire

Based on construction work characteristics, 20 workers from a Chongqing site were interviewed three times. Combining previous research on miners’ safety psychology and theories from psychology, philosophy, and sociology, a questionnaire with 48 items was designed to evaluate the importance of each factor.

After pilot testing and reliability‑validity checks, 120 questionnaires were distributed and 114 valid responses collected. SPSS V19.0 analysis identified 15 indicators with mean values above the threshold (see Table 1).

Experts added “interpersonal relationship”, “integrity”, and “achievement motivation”, resulting in an assessment system comprising 18 indicators across four dimensions: psychological quality, ability, moral character, and sociality.

Fuzzy Evaluation Model

Factor Set

The indicator system (Figure 1) contains 2 first‑level, 4 second‑level, and 18 third‑level indicators.

Evaluation Set

The study uses four rating grades: Poor, Medium, Good, Excellent.

Weight Set

Indicator weights were determined by the Delphi method (see Table 2).

Membership Functions

Based on the 18 assessment items, a safety‑psychology questionnaire (II) was created. Using the normal distribution of human intelligence as a reference, standard points for each indicator were derived (Table 3), and corresponding membership functions were defined.

Evaluation Example

A worker’s questionnaire scores were processed through the fuzzy evaluation steps. The first‑level evaluation matrix was normalized using the standard points and membership functions, yielding intermediate results for each dimension. The second‑level matrix aggregated these results, and the final comprehensive rating was “Medium”.

The detailed results showed “Poor” for psychological quality, “Medium” for ability and moral character, and “Good” for sociality. Because the overall rating leaned toward “Poor”, the worker’s safety‑psychology level is only marginally qualified, suggesting targeted psychological training and monitoring.

The above demonstrates the complete process of building and applying a fuzzy evaluation model for construction worker safety psychology.

References:

【1】 MBA智库百科 模糊评价法

【2】 Liu Haoran, Chen Shaoqing, Liu Guangcai, Ran Guangjian. “Research on Safety‑Psychology Assessment Technology for Construction Workers Based on Fuzzy Mathematics,” China Safety Production Science & Technology, 2013, 9(06):91‑95.