Abstract
Background
A number of accidents have occurred in small and medium enterprises (SMEs). Efforts in reducing accidents have been undertaken through the implementation of safety behaviors. Unfortunately, few studies have examined motives behind unsafe behaviors, such as safety silence motives. This study aimed to observe the motives underlying safety behaviors, namely safety silence motive (SSM) (SSM-relation, SSM-climate, SSM-issue, and SSM-job) and to evaluate the effect of SSM and safety communication on safety participation in different industrial sectors and scales.
Materials and Methods
Eighty workers from two industrial sectors and scales of SMEs were involved. They were instructed to fill out a set of questionnaires. A five-Likert scale was used to respond. An independent t test was applied to find any significant differences. The partial least square-structural equation modeling for multigroup was used to develop a model on relations among the variables.
Results
The results showed that SSM scores were high in SMEs, and the scores were different across industrial sectors and scales. SSM had a negative influence on safety communication, and safety communication positively influenced safety participation.
Conclusion
The study of SSM, safety communication, and safety participation in different sectors and scales should be separated in SMEs.
Keywords: Safety communication, Safety participation, Safety silence motive, SMEs
1. Introduction
Previous studies have shown that small and medium enterprises (SMEs) are associated with high occupational safety risks. Compared to large-scale enterprises, SMEs seem to have higher occupational safety risks. A higher risk in SMEs might result from workers' low education, workers' lack of safety awareness, informal safety procedures, and poor implementation of safety management [1].
Although a higher occupational safety risk is associated with SMEs, unfortunately, lack of reports on accidents in SMEs is available [2]. This condition appears to be contrary to large-scale enterprises in which they have to apply safety management systems and comply with safety regulations [3].
There are several reasons for a high number of unreported accidents found in SMEs. Probst et al. [4] found that a high number of unreported accidents correlate with poor safety climates (defined as a set of perceptions by workers regarding the organizational safety aspects of the workplace). Other studies found that unreported accidents are due to the fear of negative consequences given by the management. This fear and unwillingness to report refer to safety silence [4,5].
Safety silence is defined as a type of silence when workers do not talk to supervisors about safety issues [6]. According to Manapragada and Bruk-Lee [6], safety silence might be triggered by some factors called safety silence motive (SSM), which refers to the motive of workers' safety silence to their working environments. SSM explains the reasons of why workers do not talk to their superiors about safety issues experienced in the workplaces. The SSM can be evaluated based on the dimensions of relations, climates, issues, and jobs. SSM of relations deals with the silence in regard to a good relationship between coworkers and superiors. SSM of climate refers to the silence due to organizational shared perceptions in safety. SSM of issues refers to the silence because of the evaluation risks of safety. Moreover, SSM of job relates to the silence concerning with the job characteristics.
Manapragada and Bruk-Lee [6] stated that SSM is negatively related to safety communication (Scom). Communication, both formal and informal, is a critical factor for enhancing organizational effectiveness [7]. Scom deals with the degree to which workers are open to convey to their superiors about safety issues, ideas, concerns, or perceptions of superiors as motivators, and in return supervisors accept workers' advice to improve work safety [8]. Good Scom is a must because it represents a worker's desire to actively participate in a communication aimed at improving workplace safety [9]. An increase in Scoms is expected to improve safety behavior.
Safety behavior can be indicated by safety participation. Safety participation is a set of activities related to helping coworkers and supporting safety programs, initiatives, and efforts to improve workplace safety [10]. In the end, safety participation can decrease the number of accidents in the workplace [11]. This is supported by Widyanti et al. [12] that the safety behavior approach can decrease work accident rates in the oil and gas company in Indonesia.
A number of previous studies have been conducted to investigate the effect of Scom on safety participation (SB-P). The research has been focused on both SMEs [13] and large-scale enterprises [14,15]. However, considering the influence of safety silence on Scom, only few studies have looked at these three factors as the whole. The exception includes a study by Manapragada and Bruk-Lee [6] who observed the effect of SSM on Scom of nurses in a large hospital enterprise.
A higher occupational safety risk and unreported accidents in SMEs are also found in Indonesia. Among the manufacturing sectors of Indonesian SMEs [refers to Indonesian Statistical Bureau (Badan Pusat Statistik/BPS in Indonesia [16])], the craft and metal are two enterprises suffering from high hazards and risk accidents (see Agustina et al. [17] and Harncharoen et al. [18] for examples of accident in batik and metal enterprises, respectively). In detail, most of the safety risks found in craft industries are low back pain due to the unergonomic work position [19] and injuries relate to material contact with the body such skin irritation due to chemical exposure [17,20], whereas in metal industries, the most common injuries are related to musculoskeletal disorders because of the awkward posture while operating the equipment [21], material fraction, and electrical shortcut especially for grinding and welding processes [22,23].
Limited studies have reported a high number of accidents that happen in metal industries and craft industries. In metal industries, for example, Ansori et al. [21] observed 45% of accidents experienced by 150 workers. In addition, Suprianto and Evendi [23] reported 66.7% of accidents experienced by the workers in metal workshops. In craft industries, several studies found low safety performance in craft industries in Madura Island [20] and high safety risk in those industries [24]. Interestingly, a special attention has been paid by the Indonesian government to both craft and metal enterprises. A craft enterprise—batik—is acknowledged by the United Nations of Educational, Scientific, and Cultural Organization as Indonesian heritage [25] and has contributed to the national economy especially in persisting the global economic crisis in 1997 [26]. Meanwhile, metal SMEs have economically been growing dramatically in Indonesia up to 11.97% in 2016 [27].
Indonesian Statistical Bureau [28] defines small enterprises (SEs) as industries that employ 5 up to 19 workers, whereas medium enterprises (MEs) employ 20 up to 99 workers. However, SEs and MEs have different styles in managing safety. The safety standards, such as formal operation and safety practices, in SEs seem to be worse than MEs [29]. Besides, Legg et al. [2] stated that human resources in SEs are worse than MEs such as work divisions and support professions.
This study aimed to observe the SSM, Scoms, and SB-P in two industrial sectors (craft and metal) and two scales (SEs and MEs) in Indonesia. In addition, this study investigates relationships among these three factors as seen in Fig. 1. The two important sectors are observed in this study because they are giving great national economic supports for Indonesia and, simultaneously, have high risks in terms of accidents. Meanwhile, the reason to examine the two scales of enterprises is due to different characteristics between them [21,30].
Fig. 1.
The conceptual model of safety behavior.
2. Materials and methods
2.1. Sample
In this study, a survey was conducted in two industrial sectors, namely craft and metal enterprises. The craft enterprise in this present study refers to a batik industry (patterned fabric industry having a certain character which is made specifically by writing or applying wax to the fabric and processed in a certain way by using chemicals). Twelve SEs and four MEs of Indonesian craft enterprises were involved in this study. The enterprises are located in Madura Island as the center of batik as a creative industry in East Java, Indonesia. It should be noted that the average number of employees in each SME in Indonesia is limited (small enterprise: 5–19 workers; medium enterprise: 20–99 workers, according to Indonesian Statistical Bureau/BPS [16]). Representing those SEs and MEs, a total of 25 respondents of SEs and 15 respondents of MEs (mean age = 40.88 years, SD = 10.26 years, average experience = 9.10 years for SEs and mean age = 37.07 years, SD = 13.73 years, average experience = 7.90 years for MEs) participated in this study. Meanwhile, fifteen SEs and three MEs of metal in Gresik (East Java of Indonesia) were engaged in the study, with a total of 27 respondents of SEs and 13 respondents of MEs (mean age = 40.37 years, SD = 9.70 years, average experience = 10.67 years for SEs and mean age = 34.85 years, SD = 7.74 years, average experience = 6.92 years for MEs). The metal's SMEs in Gresik were chosen because of the high development of metal industries. The metal enterprise in this present study included cutting, welding, bending, drilling, and machining metal materials. Both industries and the workers were selected based on the convenience sampling method.
2.2. Measure
SSM was measured using a set of questionnaires developed by Manapragada and Bruk-Lee [6]. SSM consists of four dimensions, namely SSM-relation (SSM-R), SSM-climate (SSM-C), SSM-issue (SSM-I), and SSM-job (SSM-J). In total, the SSM questionnaires consist of twenty-six items. Scom was measured with four items developed by Vinodkumar and Bhasi [31]. SB-P was observed with three items [32]. In this study, all items were measured using a Likert scale, starting from 1 (strongly disagree) to 5 (strongly agree). The items can be seen in Table 1.
Table 1.
The items of the study (in Bahasa Indonesia)
| Constructs and its related items | Code | |
|---|---|---|
| Semua pertanyaan SSM diawali dengan pernyataan “Saya tidak akan berbicara perihal keselamatan dengan atasan saya jika …” | ||
| SSM-relation | SSM-R | |
| 1 | … Hal tersebut dapat menimbulkan persepsi negatif terhadap saya | SSM-R1 |
| 2 | … Hal tersebut dapat menimbulkan perselisihan antar teman kerja | SSM-R2 |
| 3 | … Hal tersebut dapat menyebabkan teman kerja tidak menghormati saya | SSM-R3 |
| 4 | … Dapat menimbulkan kesalahpahaman pada saya | SSM-R4 |
| 5 | … Akan menyulitkan hubungan dalam bekerja sama dengan rekan kerja | SSM-R5 |
| 6 | … Dapat menyakiti perasaan rekan kerja | SSM-R6 |
| 7 | … Tidak ingin orang lain berpikir bahwa saya mengganggu | SSM-R7 |
| 8 | … Dapat menyebabkan rekan kerja saya menjadi tertekan | SSM-R8 |
| SSM-climate | SSM-C | |
| 1 | … Atasan saya tidak terbuka untuk mendengarkan perihal keselamatan kerja | SSM-C1 |
| 2 | … Atasan saya tidak memprioritaskan keselamatan kerja | SSM-C2 |
| 3 | … Atasan saya tidak akan mengambil tindakan terkait keselamatan kerja | SSM-C3 |
| 4 | … Perusahaan tempat kerja saya tidak menjadikan keselamatan sebagai prioritas | SSM-C4 |
| 5 | … Saya merasa tidak dapat berbicara dengan jujur dan terbuka terkait keselamatan kerja di perusahaan tempat kerja saya | SSM-C5 |
| 6 | … Tidak ada panduan kerja yang jelas untuk melaporkan perihal keselamatan di tempat kerja saya | SSM-C6 |
| 7 | … Atasan saya tidak menjalankan fungsinya berkaitan dengan keselamatan kerja | SSM-C7 |
| 8 | … Saya merasa kurang nyaman dengan atasan saya dalam hal keselamatan kerja | SSM-C8 |
| SSM-issue | SSM-I | |
| 1 | … Aktivitas keselamatan tidak menyebabkan risiko kerja | SSM-I1 |
| 2 | … Aktivitas keselamatan tidak membahayakan siapapun | SSM-I2 |
| 3 | … Aktivitas keselamatan tidak memengaruhi keselamatan kerja orang lain | SSM-I3 |
| 4 | … Tidak ada dampak negatif dari permasalahan keselamatan | SSM-I4 |
| 5 | … Tidak ada hasil kerja yang buruk akibat aktivitas keselamatan | SSM-I5 |
| 6 | … Aktivitas keselamatan tidak membebani keberlangsungan pekerjaan | SSM-I6 |
| SSM-job | SSM-J | |
| 1 | … Saya memiliki beban kerja yang berlebih | SSM-J1 |
| 2 | … Kesibukan kerja saya menjadikan tidak ada waktu untuk berbicara tentang keselamatan | SSM-J2 |
| 3 | … Saya bekerja dengan batasan waktu yang ketat | SSM-J3 |
| 4 | … Saya tidak merasa keselamatan kerja merupakan bagian pekerjaan yang harus saya lakukan | SSM-J4 |
| Safety communication | Scom | |
| 1 | Perusahaan menjalankan kebijakan perihal keselamatan kerja secara terbuka | Scom1 |
| 2 | Ada kesempatan untuk mendiskusikan dan memutuskan perihal keselamatan kerja dalam pertemuan | Scom2 |
| 3 | Target dan tujuan kinerja keselamatan di perusahaan saya jelas bagi pekerja | Scom3 |
| 4 | Terdapat komunikasi yang terbuka terkait keselamatan di tempat kerja | Scom4 |
| Safety participation | SB-P | |
| 1 | Saya mendukung program keselamatan dalam perusahaan tempat kerja | SB-P1 |
| 2 | Saya berusaha lebih untuk meningkatkan keselamatan kerja di tempat kerja | SB-P2 |
| 3 | Saya secara sukarela mengerjakan tugas atau aktivitas yang dapat membantu dalam memperbaiki keselamatan tempat kerja | SB-P3 |
SSM, safety silence motive.
2.3. Procedure
Workers in craft and metal enterprises in both SEs and MEs were asked to fill out questionnaires. If they found any difficulties, the surveyor would help to fill out the questionnaire on behalf of the workers. The permission to conduct the research was granted by the owner of the SEs and MEs. The workers filled out the questionnaires during rest breaks.
2.4. Data analysis
A t test was used to evaluate the differences in mean perceptions of workers based on the sectors and scales. The possible relationships among variables were assessed using the partial least square-structural equation modeling (PLS-SEM) algorithm, while the multigroup analysis (MGA) was observed by the procedure of measurement invariance of composite models (MICOM).
3. Results
3.1. Demographic data of respondents
The demographic data of respondents as a function of different sectors of industries (craft and metal enterprises) and different industry scales (SEs and MEs) can be seen in Table 2.
Table 2.
Demographic data of workers in two industrial sectors and two industrial scales
| Industrial sectors and industrial scales | Craft |
Metal |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SEs |
MEs |
Total |
SEs |
MEs |
Total |
|||||||
| N | % | N | % | N | % | N | % | N | % | N | % | |
| Number of subjects | 25 | (100) | 15 | (100) | 40 | (100) | 27 | (100) | 13 | (100) | 40 | (100) |
| Gender | ||||||||||||
| Male | 5 | (20) | 0 | (0) | 5 | (12) | 27 | (100) | 13 | (100) | 40 | (100) |
| Female | 20 | (80) | 15 | (100) | 35 | (88) | 0 | (0) | 0 | (0) | 0 | (0) |
| Age group (year) | ||||||||||||
| 16–29 | 4 | (16) | 7 | (47) | 11 | (28) | 3 | (11) | 4 | (31) | 7 | (17) |
| 30–39 | 6 | (24) | 1 | (7) | 7 | (17) | 12 | (44) | 4 | (31) | 16 | (40) |
| 40–49 | 8 | (32) | 4 | (27) | 12 | (30) | 7 | (26) | 5 | (38) | 12 | (30) |
| 50–59 | 6 | (24) | 2 | (12) | 8 | (20) | 4 | (15) | 0 | (0) | 4 | (10) |
| 60–69 | 1 | (4) | 1 | (7) | 2 | (5) | 1 | (4) | 0 | (0) | 1 | (3) |
| Work Experience (year) | ||||||||||||
| Less than 3 | 2 | (8) | 2 | (13) | 4 | (10) | 0 | (0) | 2 | (16) | 2 | (5) |
| 3 to 7 | 2 | (8) | 6 | (40) | 8 | (20) | 8 | (30) | 6 | (46) | 14 | (35) |
| More than 7 | 21 | (84) | 7 | (47) | 28 | (70) | 19 | (70) | 5 | (38) | 24 | (60) |
| Education | ||||||||||||
| No formal education | 0 | (0) | 1 | (7) | 1 | (3) | 2 | (6) | 0 | (0) | 2 | (5) |
| Elementary school | 19 | (76) | 10 | (66) | 29 | (72) | 1 | (4) | 0 | (0) | 1 | (3) |
| Junior high school | 5 | (20) | 4 | (27) | 9 | (22) | 5 | (19) | 4 | (31) | 9 | (22) |
| Senior high school | 1 | (4) | 0 | (0) | 1 | (3) | 18 | (67) | 8 | (61) | 26 | (65) |
| College/university | 0 | (0) | 0 | (0) | 0 | (0) | 1 | (4) | 1 | (8) | 2 | (5) |
| Social relation | ||||||||||||
| Family | 17 | (68) | 4 | (27) | 21 | (52) | 14 | (51) | 0 | (0) | 14 | (35) |
| Friend | 1 | (4) | 0 | (0) | 1 | (3) | 5 | (19) | 3 | (23) | 8 | (20) |
| Neighbor | 5 | (20) | 6 | (40) | 11 | (28) | 1 | (4) | 0 | (0) | 1 | (3) |
| Other (no relation) | 2 | (8) | 5 | (33) | 7 | (17) | 7 | (26) | 10 | (77) | 17 | (42) |
MEs, medium enterprises; SEs, small enterprises.
3.2. The value of constructs
The results of data collection in both sectors and scales are shown in Table 3. Meanwhile, the statistical values of SSM (SSM-R, SSM-C, SSM-I, and SSM-J), Scom, and SB-P can be seen in Table 4. Independent t test was applied to observe the possible different values of SSM, Scom, and SB-P between different industrial sectors and scales. Based on the sectors, SSM-R, SSM-C, SSM-I, and Scom were significantly different. Meanwhile, based on the scales, the only SSM-I was significantly different.
Table 3.
Result of data collection
| Construct/associated items | Industrial sectors |
Industrial scales |
||||||
|---|---|---|---|---|---|---|---|---|
| Craft |
Metal |
SEs |
MEs |
|||||
| Mean | Standard deviation | Mean | Standard deviation | Mean | Standard deviation | Mean | Standard deviation | |
| SSM-R | 4.16 | 0.81 | 3.28 | 1.04 | 3.68 | 1.10 | 3.80 | 0.96 |
| SSM-R1 | 4.75 | 0.44 | 3.25 | 1.13 | 3.90 | 1.22 | 4.18 | 0.94 |
| SSM-R2 | 4.35 | 0.70 | 3.48 | 1.13 | 3.94 | 1.07 | 3.86 | 0.97 |
| SSM-R3 | 4.15 | 0.86 | 2.93 | 0.97 | 3.48 | 1.15 | 3.64 | 1.03 |
| SSM-R4 | 3.75 | 0.78 | 3.40 | 1.17 | 3.60 | 1.07 | 3.54 | 0.88 |
| SSM-R5 | 4.00 | 0.75 | 3.75 | 1.06 | 3.94 | 0.94 | 3.75 | 0.89 |
| SSM-R6 | 4.33 | 1.02 | 3.58 | 1.06 | 3.88 | 1.10 | 4.07 | 1.12 |
| SSM-R7 | 3.85 | 1.03 | 3.10 | 0.90 | 3.37 | 1.12 | 3.68 | 0.82 |
| SSM-R8 | 4.13 | 0.91 | 2.80 | 0.88 | 3.33 | 1.13 | 3.71 | 1.05 |
| SSM-C | 3.23 | 1.05 | 3.84 | 0.97 | 3.50 | 1.09 | 3.61 | 1.03 |
| SSM-C1 | 3.15 | 1.12 | 3.45 | 0.99 | 3.25 | 1.10 | 3.39 | 0.99 |
| SSM-C2 | 2.95 | 1.22 | 3.85 | 1.00 | 3.38 | 1.19 | 3.43 | 1.23 |
| SSM-C3 | 2.90 | 0.96 | 4.03 | 1.19 | 3.48 | 1.21 | 3.43 | 1.23 |
| SSM-C4 | 3.08 | 0.92 | 3.98 | 0.83 | 3.54 | 0.94 | 3.50 | 1.07 |
| SSM-C5 | 3.35 | 0.86 | 3.60 | 1.03 | 3.40 | 0.98 | 3.61 | 0.92 |
| SSM-C6 | 3.78 | 0.77 | 3.93 | 0.92 | 3.79 | 0.87 | 3.96 | 0.79 |
| SSM-C7 | 2.98 | 1.05 | 4.05 | 0.78 | 3.56 | 1.09 | 3.43 | 1.03 |
| SSM-C8 | 3.68 | 1.53 | 3.83 | 0.98 | 3.56 | 1.38 | 4.11 | 0.99 |
| SSM-I | 2.93 | 1.40 | 3.66 | 1.04 | 3.49 | 1.21 | 2.94 | 1.33 |
| SSM-I1 | 3.23 | 1.48 | 3.85 | 0.95 | 3.69 | 1.20 | 3.25 | 1.38 |
| SSM-I2 | 3.38 | 1.53 | 3.90 | 1.17 | 3.81 | 1.30 | 3.32 | 1.49 |
| SSM-I3 | 3.00 | 1.30 | 3.75 | 1.08 | 3.63 | 1.24 | 2.89 | 1.13 |
| SSM-I4 | 2.63 | 1.48 | 3.53 | 0.96 | 3.35 | 1.25 | 2.57 | 1.32 |
| SSM-I5 | 2.75 | 1.48 | 3.58 | 0.98 | 3.40 | 1.22 | 2.71 | 1.38 |
| SSM-I6 | 2.63 | 1.10 | 3.38 | 1.08 | 3.06 | 1.07 | 2.89 | 1.29 |
| SSM-J | 3.28 | 1.32 | 3.05 | 0.97 | 3.11 | 1.17 | 3.27 | 1.14 |
| SSM-J1 | 3.15 | 1.29 | 3.03 | 0.86 | 3.17 | 1.12 | 2.93 | 1.05 |
| SSM-J2 | 2.85 | 1.35 | 2.90 | 1.01 | 2.81 | 1.16 | 3.00 | 1.25 |
| SSM-J3 | 3.10 | 1.37 | 2.70 | 0.97 | 2.73 | 1.25 | 3.21 | 1.03 |
| SSM-J4 | 4.03 | 1.27 | 3.58 | 1.03 | 3.73 | 1.14 | 3.93 | 1.25 |
| Scom | 2.46 | 0.99 | 3.01 | 0.91 | 2.67 | 1.12 | 2.84 | 0.94 |
| Scom1 | 2.70 | 1.20 | 3.00 | 0.91 | 2.67 | 1.08 | 3.11 | 0.99 |
| Scom2 | 1.88 | 0.72 | 3.03 | 0.89 | 2.38 | 1.01 | 2.57 | 0.96 |
| Scom3 | 3.20 | 1.07 | 2.55 | 0.99 | 2.98 | 1.20 | 2.68 | 0.77 |
| Scom4 | 2.05 | 0.96 | 3.48 | 0.85 | 2.63 | 1.19 | 3.00 | 1.05 |
| SB-P | 2.88 | 1.12 | 3.10 | 0.86 | 2.94 | 0.99 | 3.10 | 1.06 |
| SB-P1 | 2.65 | 1.12 | 3.03 | 0.92 | 2.77 | 1.00 | 2.96 | 1.10 |
| SB-P2 | 3.10 | 1.30 | 2.85 | 0.89 | 2.87 | 1.17 | 3.18 | 0.98 |
| SB-P3 | 2.90 | 0.96 | 3.43 | 0.78 | 3.17 | 0.81 | 3.14 | 1.08 |
MEs, medium enterprises; SEs, small enterprises.
Table 4.
The value of SSM, safety communication, and safety participation both industrial sectors and scales
| Safety construct | Sectors |
Scales |
Independent t test |
|||
|---|---|---|---|---|---|---|
| Craft | Metal | SEs | MEs | Based on sectors | Based on scales | |
| SSM-R | Mean = 4.17 (SD = 0.51) | Mean = 3.29 (SD = 0.76) | Mean = 3.68 (SD = 0.82) | Mean = 3.81 (SD = 0.72) | 6.063∗∗ | -0.671 |
| SSM-C | Mean = 3.23 (SD = 0.59) | Mean = 3.84 (SD = 0.69) | Mean = 3.50 (SD = 0.70) | Mean = 3.61 (SD = 0.72) | -4.220∗∗ | -0.673 |
| SSM-I | Mean = 2.93 (SD = 1.05) | Mean = 3.66 (SD = 0.79) | Mean = 3.49 (SD = 0.91) | Mean = 2.94 (SD = 1.05) | -3.523∗ | 2.445∗ |
| SSM-J | Mean = 3.28 (SD = 1.11) | Mean = 3.05 (SD = 0.73) | Mean = 3.11 (SD = 0.98) | Mean = 3.27 (SD = 0.86) | 1.102 | -0.712 |
| Scom | Mean = 2.44 (SD = 0.46) | Mean = 3.01 (SD = 0.67) | Mean = 2.67 (SD = 0.65) | Mean = 2.84 (SD = 0.61) | -4.411∗∗ | -1.141 |
| SB-P | Mean = 2.88 (SD = 0.94) | Mean = 3.10 (SD = 0.73) | Mean = 2.94 (SD = 0.83) | Mean = 3.10 (SD = 0.87) | -1.154 | -0.807 |
∗p < 0.05, ∗∗p < 0.01.
MEs, medium enterprises; SEs, small enterprises; SSM, safety silence motive.
There were significant differences in SSM (i.e., SSM-R, SSM-C, and SSM-I) as well as Scom in different sectors (craft and metal) and SSM-I in different scales (SEs and MEs) as per independent t test in Table 4. Therefore, a MGA was proposed to evaluate the construct influences, and the multigroup evaluation was conducted based on both of industrial sectors and scales. This result was supported by Ansori et al. [21] that safety outcomes (i.e., injury, accident, and day off) between SEs and MEs were different; hence, safety outcomes were used to see how well safety behavior was performed [33].
3.3. Empirical model
The constructs evaluated in the measurement model were SSM-J (three indicators), SSM-R (five indicators), Scom (three indicators), and SB-P (three indicators). Meanwhile, the construct of SSM-C (all indicators), SSM-I (all indicators), one indicator of SSM-J (i.e., SSM-J2), three indicators of SSM-R (i.e., SSM-R4, SSM-R5, SSM-R8), and one indicator of Scom (i.e., Scom3) were removed from the model because all indicators had a loading factor less than 0.4. It was suggested by Chin [34] and Hair et al. [35] that loading below 0.4 was removed to increase the value of composite reliability (CR) and average variance extracted (AVE). The result of the measurement model can be seen in Table 5.
Table 5.
Results of the measurement model
| Construct/associated items | Based on sectors |
Based on scales |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Loading |
CR |
AVE |
Loading |
CR |
AVE |
|||||||
| Craft | Metal | Craft | Metal | Craft | Metal | SEs | MEs | SEs | MEs | SEs | MEs | |
| Safety silence motive (SSM) | 0.890 | 0.855 | 0.509 | 0.436 | 0.897 | 0.885 | 0.525 | 0.511 | ||||
| SSM-J1 | 0.627 | 0.566 | 0.702 | 0.187 | ||||||||
| SSM-J3 | 0.824 | 0.416 | 0.657 | 0.617 | ||||||||
| SSM-J4 | 0.733 | 0.575 | 0.631 | 0.748 | ||||||||
| SSM-R1 | 0.629 | 0.858 | 0.807 | 0.740 | ||||||||
| SSM-R2 | 0.556 | 0.720 | 0.678 | 0.816 | ||||||||
| SSM-R3 | 0.768 | 0.815 | 0.859 | 0.780 | ||||||||
| SSM-R6 | 0.872 | 0.708 | 0.799 | 0.853 | ||||||||
| SSM-R7 | 0.638 | 0.496 | 0.625 | 0.751 | ||||||||
| SSM-job (SSM-J) | 0.905 | 0.817 | 0.761 | 0.598 | 0.906 | 0.821 | 0.764 | 0.624 | ||||
| SSM-J1 | 0.800 | 0.788 | 0.891 | 0.446 | ||||||||
| SSM-J3 | 0.918 | 0.760 | 0.893 | 0.898 | ||||||||
| SSM-J4 | 0.895 | 0.772 | 0.836 | 0.930 | ||||||||
| SSM-relation (SSM-R) | 0.878 | 0.885 | 0.594 | 0.611 | 0.909 | 0.919 | 0.668 | 0.695 | ||||
| SSM-R1 | 0.744 | 0.880 | 0.864 | 0.870 | ||||||||
| SSM-R2 | 0.668 | 0.798 | 0.796 | 0.850 | ||||||||
| SSM-R3 | 0.861 | 0.851 | 0.903 | 0.855 | ||||||||
| SSM-R6 | 0.868 | 0.763 | 0.815 | 0.833 | ||||||||
| SSM-R7 | 0.690 | 0.580 | 0.691 | 0.755 | ||||||||
| Safety communication (Scom) | 0.850 | 0.892 | 0.654 | 0.733 | 0.885 | 0.882 | 0.719 | 0.715 | ||||
| Scom1 | 0.888 | 0.841 | 0.793 | 0.777 | ||||||||
| Scom2 | 0.730 | 0.876 | 0.867 | 0.895 | ||||||||
| Scom4 | 0.801 | 0.850 | 0.882 | 0.860 | ||||||||
| Safety participation (SB-P) | 0.871 | 0.878 | 0.695 | 0.707 | 0.870 | 0.859 | 0.692 | 0.673 | ||||
| SB-P1 | 0.942 | 0.872 | 0.916 | 0.921 | ||||||||
| SB-P2 | 0.805 | 0.865 | 0.741 | 0.709 | ||||||||
| SB-P3 | 0.742 | 0.783 | 0.829 | 0.816 | ||||||||
AVE, average variance extracted; CR, composite reliability; MEs, medium enterprises; SEs, small enterprises.
The measurement model showed that all indicators were valid in Table 5. The results of the measurement model based on both sectors and scales obtained that all loading factors for the entire construct consisted of SSM-J, SSM-R, Scom, and SB-P had a value of more than 0.4. Then, the construct had fulfilled convergent validity which had CR more than 0.7 and AVE more than 0.5 for both groups [36]. However, the AVE of SSM for metal based on the sector was lower than 0.5. It was still acceptable because the SSM was the second order [37], and its CR was more than 0.6 [38].
With multigroup (both industrial sectors and scales), the procedure of MGA was proposed. A procedure in evaluating MGA consisted of the Heterotrait–Monotrait (HTMT) and MICOM. The HTMT test aimed to assess discriminant validity, while MICOM was used to compare two groups whether the measurement model could determine the same attribute size under different conditions [39]. This was intended to assess configurated invariance, compositional invariance, and assessment of the composite equality means and variances needed to compare and interpret MGA group-specific differences.
The result of HTMT gained that all constructs both sectors and scales had HTMT values less than 0.9 that conformed to the HTMT requirement [36] as in Table 6. Then, the result of MICOM based on industrial sectors and scales as per Table 7, Table 8, respectively. Table 7 showed that the MICOM based on industrial sectors found that three constructs (i.e., SSM-J, Scom, and SB-P) fulfilled the compositional invariance. The assessment results informed that three constructs have fulfilled the partial measurement invariance based on the value of the equal mean assessment and equal variance assessment (i.e., SSM-J, SSM-R, and Scom), while one construct conformed to full measurement invariance (i.e., SB-P). Meanwhile, Table 8 showed the result based on industrial scales that SSM-J did not meet the compositional invariance; however, it still conformed to the equal mean assessment and equal variance assessment. The other constructs (i.e., SSM-R, Scom, and SB-P) were available for all invariance criteria measurements.
Table 6.
Heterotrait–Monotrait (HTMT)
| Constructs | Based sectors |
Based scales |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Craft |
Metal |
SEs |
MEs |
|||||||||
| SSM-J | SSM-R | Scom | SSM-J | SSM-R | Scom | SSM-J | SSM-R | Scom | SSM-J | SSM-R | Scom | |
| SSM-R | 0.624 | 0.476 | 0.531 | 0.556 | ||||||||
| Scom | 0.150 | 0.207 | 0.195 | 0.385 | 0.141 | 0.580 | 0.346 | 0.544 | ||||
| SB-P | 0.543 | 0.479 | 0.695 | 0.343 | 0.391 | 0.838 | 0.236 | 0.292 | 0.763 | 0.309 | 0.226 | 0.660 |
SB-P, safety participation; Scom, safety communication; SSM-J, SSM-job; SSM-R, SSM-relation; SSM, safety silence motive.
Table 7.
Invariance measurement testing using permutation based on industrial sectors
| Constructs | Compositional invariance (correlation = 1) |
Partial measurement invariance established | Equal mean assessment |
Equal variance assessment |
Full measurement invariance established | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| C = 1 | Confidence interval | Differences | Confidence interval | Equal | Differences | Confidence interval | Equal | |||
| SSM-J | 0.995 | [0.984, 1.000] | Yes | 0.344 | [-0.436, 0.453] | Yes | 0.864 | [-0.441, 0.452] | No | No |
| SSM-R | 0.996 | [0.997, 1.000] | No | 1.158 | [-0.438, 0.442] | No | -0.503 | [-0.510, 0.503] | Yes | No |
| Scom | 0.992 | [0.992, 1.000] | Yes | -1.100 | [-0.440, 0.439] | No | 0.032 | [-0.544, 0.511] | Yes | No |
| SB-P | 0.995 | [0.971, 1.000] | Yes | -0.359 | [-0.443, 0.443] | Yes | 0.470 | [-0.463, 0.486] | Yes | Yes |
SB-P, safety participation; Scom, safety communication; SSM-J, SSM-job; SSM-R, SSM-relation; SSM, safety silence motive.
Table 8.
Invariance measurement testing using permutation based on industrial scales
| Constructs | Compositional invariance (correlation = 1) |
Partial measurement invariance established | Equal mean assessment |
Equal variance assessment |
Full measurement invariance established | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| C = 1 | Confidence interval | Differences | Confidence interval | Equal | Differences | Confidence interval | Equal | |||
| SSM-J | 0.969 | [0.981, 1.000] | No | -0.162 | [-0.457, 0.475] | Yes | 0.297 | [-0.438, 0.516] | Yes | No |
| SSM-R | 0.999 | [0.998, 1.000] | Yes | -0.191 | [-0.457, 0.484] | Yes | 0.259 | [-0.481, 0.606] | Yes | Yes |
| Scom | 1.000 | [0.989, 1.000] | Yes | -0.355 | [-0.452, 0.463] | Yes | 0.192 | [-0.491, 0.608] | Yes | Yes |
| SB-P | 1.000 | [0.962, 1.000] | Yes | -0.160 | [-0.478, 0.440] | Yes | -0.180 | [-0.469, 0.581] | Yes | Yes |
SB-P, safety participation; Scom, safety communication; SSM-J, SSM-job; SSM-R, SSM-relation; SSM, safety silence motive.
Finally, the result of MGA as per hypothesis testing (refers to path coefficients) could be seen in Table 9. The results showed that there was a significant path coefficient difference in effect on the SSM described by the SSM-J–based sector. Then, in both industrial sectors, the results informed a significant influence of Scom on SB-P (hypothesis 2), and also SSM significantly reflected by SSM-J and SSM-R in both industrial sectors. Based on the industrial scale, SSM had a significant effect on Scom (hypothesis 1), and in turn Scom had a significant effect on SB-P (hypothesis 2) in both industrial scales. Besides, the SSM reflected by the SSM-J and SSM-R were also significant.
Table 9.
Results of hypothesis testing
| Hypothesis | Relationship | Based sectors |
Based scales |
||||||
|---|---|---|---|---|---|---|---|---|---|
| Path coefficient |
Supported based sectors | Path coefficient difference based sectors (craft–Metal) | Path coefficient |
Supported based scales | Path coefficient difference based scales (SEs–MEs) | ||||
| Craft | Metal | SEs | MEs | ||||||
| Hypothesis 1 | SSM → Scom | -0.027 | -0.300 | No | 0.273 | -0.401∗ | -0.455∗ | Yes | 0.054 |
| Hypothesis 2 | Scom → SB-P | 0.572∗∗ | 0.682∗∗ | Yes | 0.111 | 0.628∗∗ | 0.531∗∗ | Yes | 0.096 |
| — | SSM → SSM-J | 0.841∗∗ | 0.683∗∗ | Yes | 0.158∗ | 0.760∗∗ | 0.731∗∗ | Yes | 0.029 |
| — | SSM → SSM-R | 0.913∗∗ | 0.935∗∗ | Yes | 0.022 | 0.929∗∗ | 0.949∗∗ | Yes | 0.019 |
∗p < 0.05, ∗∗p < 0.01.
SB-P, safety participation; Scom, safety communication; SSM-J, SSM-job; SSM-R, SSM-relation; SSM, safety silence motive.
The results configuration of constructs influenced by industrial sectors and scales could be seen in Fig. 2, Fig. 3. It showed that the effect of Scom on SB-P was significant in both different sectors and scales. Meanwhile, the influence of SSM described by SSM-R and SSM-J affected Scom based on an industrial scale only. This informed that it is important to consider the effect of constructs based on industrial scale differences.
Fig. 2.
The structural model based on industrial sectors. MEs, medium enterprises; SEs, small enterprises; SSM, safety silence motive.
Fig. 3.
The structural model based on industrial scales. MEs, medium enterprises; SEs, small enterprises; SSM, safety silence motive.
4. Discussion
This study aimed to observe SSM in different industrial sectors (craft and metal industries) and different industrial scales (small and medium enterprises) in Indonesia and evaluate the effect of SSM on Scom and Scom on SB-P. The results showed that SSM in Indonesian's SMEs is high. In addition, SSM was found to be different based on industrial sectors and scales. In general, SSM generally affects Scom, and Scom influences SB-P.
The general finding of high SSM in Indonesian SMEs might be due to the characteristics of SMEs, such as low worker's education, a lack of worker safety consciousness, informal safety rules as well as procedures, and poor basic safety management [1]. These characteristics give consequences as workers feel less motivated to speak up or share safety issue–related information to either owners or managers.
The different values of SSM are found between different scales (small and medium enterprises) and between different sectors (craft and metal industries). The differences in SSM values between industrial scales might be due to better safety management of MEs than in SEs. Previous studies by Legg et al. [2] showed that management in MEs is more professional than in SEs. The differences in SSM between industrial sectors might result from the different characteristics of the owners, the workers, and the jobs. The workers in the craft are reluctant and unwilling to open to the owner/management [40] as the relationships between the owners and the workers are mostly in family relation. Speaking directly about a safety issue is considered to be impolite and may influence the relationship. On the contrary, in the metal enterprises, workers are more open by communicating their concerns around safety. The openness might relate to the professional relation (employees and employers) in the enterprises. The job characteristics in the enterprises imposing high risks to the workers, such as high spins on the machine and sparks from the welding machine enforce the workers to communicate the necessary safety issues. Lastly, the different results (i.e., craft and metal industries) are might be because of the absence of government regulation regarding the standardization of the implementation of work safety in SMEs. The Indonesian government set a safety regulation for big companies for some reasons such as to comply with the international standard and regulations. In contrast, the regulation cannot yet be applied to SMEs because of the large number of Indonesian SMEs and the lack of monitoring and evaluation process.
In general, SSM negatively affects Scom. Workers are silent to speak up about safety issues if they feel uncomfortable discussing their ideas and concerns about workplace safety with their owner-manager. Therefore, the high SSM value of workers indicates the low Scom to share their ideas and concerns about workplace safety with their owner-manager [8]. These results are in line with the research by Manapragada and Bruk-Lee [6] that SSM negatively affects Scom in a case study of nurses in a hospital.
Scom significantly influences SB-P in both industrial sectors and scales. As stated by Neal et al. [10], SB-P is an activity related to helping coworkers and supporting safety programs, initiatives as well as efforts to improve workplace safety. The characteristics of workers' SMEs in the form of high intensity of interaction make it easier for workers to engage in communication [2,41]. Therefore, Scom in SMEs will ensure that workers will reveal their initiatives and efforts to SB-P. This result is supported by Amponsah-Tawaih and Adu [42], Al-Haadir et al. [43], Shin et al. [14] and Seo et al. [15] that Scoms support workers' safety performance, particularly, in SB-P.
This study has some limitations. First, the present study has a limited number of samples because of restricted permits. Even the number of samples is limited; however, the sample is considered to represent the number of SMEs involved in the study. Therefore, further study is suggested to collect more samples. Second, this study only evaluates two sectors of industries. Because there are twenty-three sectors of industries in Indonesia [16], further study is expected to do similar research for other sectors to generalize the result. Third, the next study should involve accident data to show the safety outcomes of the safety constructs relation, especially the association between SB-P and accidents. This suggestion is in line with the result of Wallace [44] that SB-P, as a part of safety behavior, has a significantly negative relationship with accidents.
Despite its limitations, this study generally gives a valuable novel contribution in the safety field SMEs and Indonesian SMEs in particular because this study provides empirical data on SSM, Scom, SB-P, and the relationships among them. This empirical study is also the first step in further comprehensive studies as an effort to maximize safety behavior and safety in SMEs.
5. Conclusion
SSM in both sectors (craft and metal) and scales (SEs and MEs) are high. SSM's values are different in both industrial sectors and scales. Therefore, in the next research, different sectors and scales should be separately analyzed. In general, SSM influences Scom, and Scom influences SB-P.
Conflicts of interest
All authors have no conflicts of interest to declare.
Acknowledgments
The authors would like to thank The Indonesia Endowment Fund for Education (LPDP) - Ministry of Finance for funding research through doctoral program scholarship.
Contributor Information
Nachnul Ansori, Email: nachnulansori@students.itb.ac.id.
Ari Widyanti, Email: widyanti@mail.ti.itb.ac.id.
Yassierli, Email: yassierli@ti.itb.ac.id.
References
- 1.Masi D., Cagno E. Barriers to OHS interventions in small and medium-sized enterprises. Saf Sci. 2015;71:226–241. doi: 10.1080/10803548.2015.1117351. [DOI] [PubMed] [Google Scholar]
- 2.Legg S.J., Olsen K.B., Laird I.S., Hasle P. Managing safety in small and medium enterprises. Saf Sci. 2015;71:189–196. [Google Scholar]
- 3.Li Y., Guldenmund F.W. Safety management systems: a broad overview of the literature. Saf Sci. 2018;103:94–123. [Google Scholar]
- 4.Probst T.M., Brubaker T.L., Barsotti A. Organizational injury rate under reporting: the moderating effect of organizational safety climate. J Appl Psychol. 2008;93:1147–1154. doi: 10.1037/0021-9010.93.5.1147. [DOI] [PubMed] [Google Scholar]
- 5.Wedagama D.M.P., Wishart D. The relationship between self-reported traffic crashes and driver behavior in the road transportation of goods and freight in Bali. Int J Technol. 2018;3:558–567. [Google Scholar]
- 6.Manapragada A., Bruk-Lee V. Staying silent about safety issues: conceptualizing and measuring safety silence motives. Accid Anal Prev. 2016;91:144–156. doi: 10.1016/j.aap.2016.02.014. [DOI] [PubMed] [Google Scholar]
- 7.Verčič A.T., Verčič D., Sriramesh K. Internal communication: definition, parameters, and the future. Publ Relation Rev. 2012;38:223–230. [Google Scholar]
- 8.Hofmann D.A., Stetzer A. The role of safety climate and communication in accident interpretation: implications for learning from negative events. Acad Manag J. 1998;41:644–657. [Google Scholar]
- 9.Morrow K.J., Gustavson A.M., Jones J. Speaking up behaviours (safety voices) of healthcare workers: a metasynthesis of qualitative research studies. Int J Nurs Stud. 2016;64:42–51. doi: 10.1016/j.ijnurstu.2016.09.014. [DOI] [PubMed] [Google Scholar]
- 10.Neal A., Griffin M.A., Hart P.M. The impact of organizational climate on safety climate and individual behavior. Saf Sci. 2000;34:99–109. [Google Scholar]
- 11.Jiang L., Yu G., Li Y., Li F. Perceived Colleagues’ Safety Knowledge/behavior and safety performance: safety climate as a moderator in a multilevel study. Accid Anal Prev. 2010;42:1468–1476. doi: 10.1016/j.aap.2009.08.017. [DOI] [PubMed] [Google Scholar]
- 12.Widyanti A., Octaviana I., Yamin P. Safety climate, safety behavior, and accident experience: case of Indonesia oil and gas company. Ind Eng Manag Syst. 2018;17:128–135. [Google Scholar]
- 13.Saat M.Z.M., Subramaniam C., Shamsudin F.M. A proposed relationship between organizational safety practices and safety performance in the manufacturing of small and medium enterprises in Malaysia. Sains Humanika. 2016;8:91–97. [Google Scholar]
- 14.Shin D., Gwak H., Lee D. Modeling the predictors of safety behavior in construction workers. Int J Occup Saf Ergon. 2015;21:298–311. doi: 10.1080/10803548.2015.1085164. [DOI] [PubMed] [Google Scholar]
- 15.Seo H.C., Lee Y.S., Kim J.J., Jee N.Y. Analyzing safety behavior of temporary construction workers using structural equation modeling. Saf Sci. 2015;77:160–168. [Google Scholar]
- 16.Badan Pusat Statistik/BPS . Indonesian Statistical Bureau; 2015. Klasifikasi baku lapangan usaha Indonesia (standard classification of Indonesia's business fields) [Google Scholar]
- 17.Agustina F., Ansori N., Yuliatin An ergonomic intervention model by sampling inspection and personal protective equipment in SMEs batik Madura. Adv Sci Lett. 2017;23:12372–12376. [Google Scholar]
- 18.Harncharoen K., Isahak M., Kaewboonchoo O., Low W.Y., Ratanasiripong P. Workplace environment and quality of life of SME workers: a systematic review. Asia J Publ Health. 2016;7:64–81. [Google Scholar]
- 19.Agustina F., Maulana A. Analisis postur kerja dengan tinjauan ergonomi di industri batik madura. Jurnal Inovasi Dan Kewirausahaan. 2012;3:167–171. [Google Scholar]
- 20.Ansori N., Novianti T., Agustina F., Rakhmawati N. Safety performance index pada industri batik tulis berdasarkan kriteria majemuk. Jurnal Teknik Industri. 2015;17:105–110. [Google Scholar]
- 21.Ansori N., Sutalaksana I.Z., Widyanti A. Safety outcomes in small-size and medium-size metal enterprises in Indonesia: are they different? Ind Eng Eng Manage. 2018 (IEEM 2018), Thailand, 16-19 Desember 2018. [Google Scholar]
- 22.Saskia V.N., Kirana S., Susihono W. Implementasi pengendalian risiko kecelakaan kerja pada proses grinding dan welding. Jurnal Teknik Industri. 2013;1:206–211. [Google Scholar]
- 23.Suprianto R., Evendi A. Compliance use of personal protective equipment in las workers in Indramayu. Jurnal Kesehatan Masyarakat. 2015;1:14–18. [Google Scholar]
- 24.Agustina F., Ansori N., Novianti T., Farikha M. Kajian implementasi kesehatan dan keselamatan kerja dengan pendekatan behavior based safety. Jurnal Ilmiah Teknik Industri. 2016;15 [Google Scholar]
- 25.Ismail T., Wiyantoro L.S., Meutia Muchlish M. Strategy, interactive control system and national culture: a case study of batik industry in Indonesia, International Congress on Interdisciplinary Business and Social Sciences. Procedia - Soc Behav Sci. 2012;65:33–38. [Google Scholar]
- 26.Meutia Ismail T. vol. 65. 2012. The development of entrepreneurial social competence and business network to improve competitive advantage and business performance of small medium sized enterprises: a case study of batik industry in Indonesia; pp. 46–51. (International congress on interdisciplinary business and social sciences. Procedia - soc behav sci). [Google Scholar]
- 27.www.cnnindonesia.com/ekonomi/20171101145541-92-252731/pertumbuhan-industri-manufaktur-melejit-pada-kuartal-iii/
- 28.Badan Pusat Statistik/BPS Statistik Indonesia 2017 (Indonesian statistical 2017) Indonesian Statistical Bureau; 2017. [Google Scholar]
- 29.Wang Q., Mei Q., Liu S., Zhang J. Analysis of managing safety in small enterprises: dual-effects of employee prosocial safety behavior and government inspection. BioMed Res Int. 2018;2018 doi: 10.1155/2018/6482507. Article ID 6482507. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Ansori N., Sutalaksana I.Z., Widyanti A. International conference of occupational health and safety, Indonesia. 2017. Comparison between key success factors in safety behavior in small and medium sized enterprises (SMEs) and large industries, and development of a hypothetic model for safety behavior in Indonesian SMEs. [Google Scholar]
- 31.Vinodkumar M.N., Bhasi M. Safety management practices and safety behaviour: assessing the mediating role of safety knowledge and motivation. Accid Anal Prev. 2010;42:2082–2093. doi: 10.1016/j.aap.2010.06.021. [DOI] [PubMed] [Google Scholar]
- 32.Neal A., Griffin M.A. A study of the lagged relationships among safety climate, safety motivation, and accidents at the individual and group levels. J Appl Psychol. 2006;91:946–953. doi: 10.1037/0021-9010.91.4.946. [DOI] [PubMed] [Google Scholar]
- 33.Panuwatwanich K., Al-Haadir S., Stewart R.A. Influence of safety motivation and climate on safety behavior and outcomes: evidence form the Saudi Arabian Construction Industry. Int J Occup Saf Ergon. 2016;23:60–75. doi: 10.1080/10803548.2016.1235424. [DOI] [PubMed] [Google Scholar]
- 34.Chin W. How to write up and report PLS analyses. In: Vinzi V., Chin W., Henseler J., Wang H., editors. Handbook of partial least squares: concepts, methods and applications. Springer; Heidelberg: 2010. 655–90. [Google Scholar]
- 35.Hair J.F., Ringle C., Sarstedt M. PLS-SEM: indeed a silver bullet. J Mark Theory Pract. 2011;19:139–152. [Google Scholar]
- 36.Hair J.F., Hult G.T.M., Ringle C.M., Sarstedt M. 2nd ed. SAGE Publication; 2017. A primer on partial least squares structural equation modeling (PLS-SEM) [Google Scholar]
- 37.Becker J., Klein K., Wetzels M. Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long Range Plann. 2012;45:359–394. [Google Scholar]
- 38.Fornell C., Larcker D.F. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18:39–50. [Google Scholar]
- 39.Henseler J., Ringle C.M., Sarstedt M. Testing measurement invariance of composites using partial least squares. Int Mark Rev. 2016;33:405–431. [Google Scholar]
- 40.Fahmi F.Z., Koster S., Dijk J.V. The location of creative industries in a developing country: the case of Indonesia. Cities. 2016;59:66–79. [Google Scholar]
- 41.Rothenberg A.D., Gaduh A., Burger N.E., Chazali C., Tjandraningsih I., Radikun R., Sutera C., Weilant S. Rethinking Indonesia’s informal sector. World Dev. 2016;80:96–113. [Google Scholar]
- 42.Amponsah-Tawaih K., Adu M.A. Work pressure and safety behaviors among health workers in Ghana: the moderating role of management commitment to safety. Saf Health Work. 2016;7:340–346. doi: 10.1016/j.shaw.2016.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Al-Haadir S., Panuwatwanich K., Stewart R.A. The 19th CIB world building congress (Brisbane) 2013. Empirical analysis of the impact of safety motivation and safety climate on safety behavior. [Google Scholar]
- 44.Wallace J.C. Creating a safety conscious organization and workforce. Organ Dyn. 2016;45:305–312. [Google Scholar]