THE DEVELOPMENT OF SAFETY BEHAVIOR MODEL BY INTEGRATING COMMUNICATION, SILENCE MOTIVE AND THE BEHAVIOR INTERVENTION FOR SMALL AND MEDIUM ENTERPRISES IN METAL MANUFACTURING

• Main Author: Ansori, Nachnul
• Format: Dissertations
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/69910
• Institution: Institut Teknologi Bandung

Working accidents occuring in many industries mostly result from low safety behavior. This study developed a model of safety behavior for SMEs and the interventions to improve its behavior. This research aimed to identify the influence of individual and organizational factors, modeling safety behavior, designing, and conducting the intervention in metal SMEs. The basic model of this study is Guo et al.’s (2018) reflecting the Indonesian SMEs. The intervention was implemented by experiments to confirm the effects. The developed model designed based on safety behavior factors that are relevant to SMEs. The study was conducted in four stages. The first is the evaluation of safety silence motive (SSM) and safety communication. The respondents were 67 workers from 29 SMEs. The second and third studies were the evaluation of the developed model of SME’s safety behavior and multigroup models (SE and ME). Two hundred and three respondents were invited from 54 SMEs. A multigroup analysis was applied to evaluate the different models between SE and ME. The forth study was the intervention design and implementation. A cross-sectional study was used for developing the model and a longitudinal study for the intervention. In both the first and second studies, the evaluation used partial least square-structural equation modeling (PLS-SEM). Third phase used multigroup based on the industrial scale (multigroup analysis/MGA-SEM). The fourth study conducted interventions based on the result of previous studies. The first results informed that; [1]. Safety communication directly influences safety participation (?=0,731, p<0,01) and safety compliance (?=0,709, p<0,01), [2]. Safety silence motive has a direct effect on safety communication (?=-0,287, p<0,05), [3]. Safety silence motive is reflected by SSM-relations (?=0,830, p<0,01), SSM-climate (?=0,811, p<0,01), SSM-issue (?=0,842, p<0,01) and SSMjob (?=0,521, p<0,01). Based on MGA-SEM regarding to the different influence between SE and ME, the second and third results (203 respondents; 54 SMEs consisting of 27 MEs/medium industries and 27 SEs/small industries) informed that there is an effect of social support on safety compliance (?SE-ME=0.503, p<0.05), production pressure on safety knowledge (?SE-ME=0.445, p<0.01), production pressure on safety participation (?SE-ME=0.290, p<0.05), production pressure on safety compliance (?SE-ME=0.547, p<0.01), SSM on safety communication (?SE-ME=0.355, p<0.05), SSM described by SSM-issue (?SE-ME=0.469, p<0.05), and SSM described by SSMjob (?SE-ME=0.779, p<0.01). The fourth phase involved designing and evaluating based on the use of personal protective equipment (PPE). The intervention consisted of two treatments/levels: benefits content intervention (level 1) and risk/harm content intervention (level 2). The media used videos designed by showing up the beneficial message of using PPE and the risks/dangers of not using PPE. The messages were delivered by WhatsApp application to three different welders in different locations. The effectiveness of the intervention was evaluated based on cognitive, affective, and conative reactions. The cognitive and affective instruments used a questionnaire measured before and after the intervention. The conative evaluation used direct observations randomly by closed circuit television (CCTV). The indicators of PPE evaluated are; PPE 1[welding helmet/hat], PPE 2 [google/glasses/welding cap], PPE 3 [apron (chest+hands)], PPE 4 [a pair of gloves], PPE 5 [welding mask], PPE 6 [safety shoes]. The content of the intervention was designed based on safety communication indicators. The benefit content intervention on cognitive reactions found no significant difference in both PPE use for benefit intervention (z=-1,000; p>0.05) and risk intervention (z=-1,000; p>0.05). Based on the affective reaction, there was no significant difference in the use of both PPE for benefit interventions (z=-1,000; p>0.05) and risk interventions (z=-1,000; p>0.05). Based on the conative reaction, there was a significant difference in the use of PPE for the benefit intervention (?=- 0.2094; p<0.05) but there was no significant difference in the use of PPE in the risk intervention (?=-0.0200; p>0, 05). It indicates that a benefit content intervention for a conative reaction is effective. The different results among cognitive, affective, and conative performance might occur because the efforts executed in each reaction were different. The conative reaction represents the real behavior/actions of the welder/participant rather than just knowledge (cognitive) and intention/desire (affective) in using PPE. The conative reaction is more dynamic than the cognitive and affective reactions. Therefore, an evaluation of the conative reaction is needed in the SME of metal processing in East Java to ensure the effectiveness of behavior change related to compliance with PPE.