1 Introduction

ILO (1) estimates that on an annual basis an average 2.3 million workers die from occupational injuries and diseases corresponding to over 6,000 deaths every single day. These figures are not just statistics but represent an unpleasant global Occupational Safety and Health (OSH) performance that is responsible for great human loss and suffering. Concerns about the debilitating effects of OHS failure to the future of work birthed the realization of the irreplaceable importance of Occupational Safety and Health Management Systems (OSHMSs) in the equation to attain business sustainability (2, 3). The application of safety systems in the current work dispensation has increasingly gained traction as a promising strategy to harmonize OSH and business sustainability (3, 4, 94). The ILO Centenary Declaration for the future of Work adopted in June 2019 declared a systems approach to OSH management as an essential fundamental for decent work and securing the future of work. Several authors assert that the concept of sustainability in development becomes untrustworthy if it is not entangled with the prevention of occupational safety and health risks (5–7). Many studies into OSHMSs have demonstrated that implementation of an OHSMS breeds progressive positive impacts on corporate security performance, economic and financial performance, and corporate competitiveness (2, 3, 8). Despite the revealed benefits of OSH management systems’ implementation and their widespread promotion globally, uptake of OSHMSs has regrettably remained low at many workplaces in Africa (9, 10, 94).

Several studies elucidated several factors that influence either negatively or positively the establishment of OSH management systems in many industrial sectors (11–13). Studies conducted in Saudi Arabia, South Africa, Honduras, India, Hong Kong, Kuwait, Uganda, China, and Jordan, highlighted factors that affect implementation of OSH management systems that include extensive subcontracting, inadequate safety training, absence of safety officers on site, ineffective laws and lack of enforcement, lack of workers’ self-protection and awareness, inadequate work procedures, poor accident record-keeping and lack of management commitment to safety budget (14–16). A study conducted by Tejamaya et al. (17) revealed many negative factors that lead to lack of interest and motivation in OSHMSs implementation in many micro, small to medium enterprises (MSMEs) that include among others the perception that OSH risks are low in MSMEs, short term benefits that are not clear and not outweighing the huge initial investment costs involved. Authors (18–21) are agreed on lack of human resources, ineffective information and communication, low financial support and low advisory services as chief factors responsible for the subdued uptake of OSHMSs in MSMEs. There is general consensus amongst many researchers that key factors that influence the effective implementation of OSH management systems include the following: provision of adequate resources (17, 19–21), management commitment and support (11, 22, 23, 95), employee involvement (22–24), good safety culture (25, 26), training (11), allocation of authority and responsibility (27, 28), the need to comply with OSH legislative provisions (29, 30), institutional image and reputation (31, 32) and improved productivity and profitability (33–35).

The majority of studies that have been conducted globally to explore the factors that enhance OSHMSs implementation (17, 19–21) were focusing on workplaces in developed countries that have a different contextual environment to that of developing and least developed countries. Andowa et al. (94) study demonstrated lower implementation levels of OSHMSs in most developing and least developed countries than in developed countries which may suggest the existence of variation in the contextual factors driving implementation of OSHMSs between the workplaces in developing and developed countries. Andowa et al. (94) study cautioned about the risk of applying the ‘one size fits all approach’ to OSH management system implementation at workplaces without considering the peculiar compounding factors that are a direct result of the disparities in the political, socio-economic environmental context. The study placed a challenge on researchers to conduct further research that will explore the factors associated with implementation of OSH management systems contextualized to the environmental setting of developing and least developed countries thereby providing the basis for establishment of problem driven solutions to increase uptake of OSH management systems at workplaces.

It cannot therefore be ruled out that failure to have a thorough understanding of contextual factors that enhance OSH management systems implementation is an impediment to effective promotion of OSH management systems at workplaces. Against an assertion by Pritchett et al. (99) that advocates for problem driven solutions adaptable to the environmental context, it is imperative to have a deeper understanding of the contextual factors enhancing OSHMSs implementation so as to craft problem driven solutions to increase uptake of OSHMSs.

Few studies have been conducted to explicate factors that drive OSHMS implementation in Southern Africa (36, 37, 94). This research gap in Southern Africa precipitates an unsustainable situation where most workplaces in developing and least developed countries are constantly resorting to taking the risk of experiencing failure in OSH management systems implementation by duplicating OSH management system implementation interventions from studies conducted largely in developed countries that are not necessarily compatible with their local environmental conditions. Zimbabwe, like any other country in Southern Africa is not spared from occupational safety and health challenges confronting the generality of workplaces. According to Mutetwa (38), Zimbabwe has been suffering from economic loss of approximately US$44 million annually due to occupational injuries and diseases. A sector analysis of the occupational accidents statistics done by NSSA singled out the manufacturing sector in Zimbabwe as the second most contributor to the economic loss Zimbabwe is suffering coming after the mining sector with a contribution of 0,39% of the Gross Domestic Product (GDP) (38). NSSA is convinced that the bad OSH performance of the country is mainly influenced by non-implementation of OSHMSs at many workplaces in the country as evidenced by the low annual national average uptake rate of OSHMSs of 13% recorded over a period of ten years from 2010 to 2020 (38–40). This low uptake rate of OSHMSs in Zimbabwe is worrisome as it is achieved against concerted efforts by NSSA to promote implementation of OSHMSs at all workplaces in Zimbabwe (38, 41).

Mutare manufacturing industry is therefore not an exception to a myriad of problems affecting implementation of OSH management systems in many workplaces in Zimbabwe (NSSA OSH Division Report for 2021). In 2021, Mutare experienced an upsurge of 11, 4% in occupational accidents as compared to the same period in 2020 despite the subdued economic activity in Zimbabwe owing to the effects of COVID 19 pandemic (NSSA OSH Division Report for 2021). Mandowa (42) and Jerie (97) noted that the bad OSH performance associated with Mutare is largely influenced by the dominance of the highly hazardous timber based manufacturing factories that are generally characterized by heavy, dirty and dangerous work requiring un-ergonomic working postures and exposures to noise, dust and vibration. This unpleasant performance is a cause for concern as it is not reflective of the overall OSH burden owing to unaccounted statistics of the informal sector which according to Rodas and Alas (43) accounts for three quarters of Zimbabwe’s working population. Mandowa (42) study fumigated non implementation of OSHMSs in timber processing factories of Mutare as militating against successful safety and health management. It’s a reality that the continued entertainment of such a negative OSH performance trajectory by Mutare manufacturing industry has the propensity to curtail the decent work and sustainable development agendas for the country.

The research question that remains an unexplored dilemma is why Mutare manufacturing industry which is known for its hazardous trait and the propensity to cause serious occupational accidents remain seemingly reluctant to embrace a systems approach to OSH management yet according to Kineber et al. (44), the benefits of OSHMSs implementation were proven as far outweighing the costs of OSHMSs implementation. Currently, literature has shown that there is no research that has been conducted specifically to explore factors that enhance implementation of OSH management systems in the manufacturing industry of Mutare yet it is an industry that is progressively contributing towards the bad OSH performance of Zimbabwe. An understanding of the factors that enhance OSHMS implementation was therefore necessary in the development of a framework for promoting the factors that enhance implementation of OSHMSs at workplaces taking into consideration several limitations that confront small, medium and large enterprises such as low budget, limited technical knowledge, and shortage of specialized labour (18, 45).

The study sought to contribute to the body of knowledge by challenging the current knowledge on OSH management systems implementation in developing countries and generate new ideas and information that are critical in strengthening the business case for a systems approach to OSH management not only in the manufacturing industry of Mutare but in many industrial sectors globally that are a duplication of the Zimbabwe’s political, socio-economic environmental context. The objectives of the study were therefore to assess the factors enhancing implementation of OSH management systems in the manufacturing industry of Mutare and to develop a framework for propagating the factors that enhance OSH management systems implementation at enterprise level Against such a background, the study therefore sought to answer the following research questions

i. What are the contextual factors enhancing implementation of OSHMSs in manufacturing industry of Mutare?

ii. What framework is ideal to promote the factors that enhance OSHMSs implementation in the Manufacturing industry of Mutare.

2 Materials and methods 2.1 Study area

City of Mutare (Figure 1) is the capital of Manicaland Province and the fourth largest city in Zimbabwe. According to Manatsa (46), City of Mutare was founded in 1897 as a fort, about 8 km from the border with Mozambique to the East. The Zimbabwe 2022 census revealed that Mutare city council has a population of 224,802 of which 106,602 are males and 118,200 are females (47). Mutare earned the pseudonyms “Zimbabwe’s Gateway to the Sea” and ‘Gateway to Eastern Highlands’ because of its proximity to Mozambique’s Beira port and the Eastern Highlands, respectively (97). The city’s proximity to the sea makes it the most strategic location for import and export-oriented enterprises (48).

Figure 1. Map of the city of Mutare. Source: researchers.

The economy of Mutare is anchored by various business sectors that include forestry, agriculture, mining, tourism, manufacturing and informal sectors supported by a range of commercial and social services (49). Mutare economy is largely driven by manufacturing industry that is mainly located in the Nyakamete industrial area. Mutare city’s manufacturing industry is comprised of timber processing, food manufacturing and processing, engineering and other manufacturing factories. The manufacturing industry of Mutare is generally known for its hazardous trait (42) owing to the dominant timber based manufacturing factories that according to Jerie (96) are characterized by a host of occupational hazards that include among others engineering hazards of unguarded dangerous moving parts of machinery, physical hazards (such as exposure to excessive noise, dust and vibration) and ergonomic hazards (such as poor work postures, visual strain, poor workstation design). Most of the working population in Mutare is therefore formally employed in the timber based manufacturing factories, hence is increasingly vulnerable to occupational accidents and diseases owing to its exposure to highly hazardous work activities that characterize the generality of the dominant timber based manufacturing factories.

2.2 Method

King (50) regards a research design as a systematic procedure for data extraction, analysis, interpretation and reporting in research studies. Dube et al. (51), posits the need for a deep understanding of the philosophical underpinnings of the study to inform the study design. Relativism ontological approach which provides an understanding that adopts situation based evaluations rather than using absolute principles (52) was found ideal for this study based on a firm understanding that the reality about the factors that enhance OSH management systems’ implementation is subjective and will vary from person to person and from one organization to another. According to Hampson and McKinley (53), epistemological assumptions are concerned about knowledge gathering, creation and developing of new knowledge through a cocktail of methods of knowing. Perception experience (empiricism) and inference (rationalism) epistemological assumptions were adopted to acquire knowledge through perception experience and inference about the reality of the factors enhancing the implementation of OSHMSs in manufacturing industry of Mutare.

The underlying ontological and epistemological assumptions informed the methodological approach for this study of a descriptive cross-sectional study anchored on a mixed method research embracing both the quantitative and qualitative research paradigms. As noted by Cherry (54), a descriptive cross sectional study method provides the researcher with an opportunity to explore the conditions and potentially related characteristics of a given population at a specific point in time thereby allowing the researcher to extract data that is reflective of what is currently prevailing in the manufacturing industry of Mutare as far as the factors enhancing implementation of OSH management systems are concerned. According to Dube et al. (51), pragmatism is a pluralistic and practical approach which is viewed as the primary philosophical framework of mixed method research. Prasad (55) observed that pragmatism approach is handy to researchers in various fields, because of its inclination towards delivering results that are of practical significance. The choice of the mixed method study design was motivated by its ability to triangulate divergent viewpoints, opinions, perspectives, and standpoints (56) on the factors that enhance implementation of OSH management systems in Mutare manufacturing industry. Triangulation of the data was important in enhancing the veracity of the research findings thereby aiding the extrapolation of meaningful conclusions that generalize the factors enhancing implementation of OSH management systems in manufacturing industry of Mutare. Jafer et al. (57) affirmed the criticality of data triangulation as an enabler in the generation of data that gives the researcher more confidence about the validity of the research findings.

2.3 Population, sample size and methods of sampling

The study population consisted of 1,356 employees drawn from 30 manufacturing factories of Mutare that were registered by NSSA factories inspectorate as at 15 April 2022 and seven key OSH stakeholders that included Ministry of Public Service, Labour and Social Welfare (MPSLSW), The Academia (Mutare Poly Technical College), Employers’ Confederation of Zimbabwe (EMCOZ), Zimbabwe Congress of Trade Union (ZCTU), National Social Security Authority (NSSA), International Labour Organization (ILO) and Standards Association of Zimbabwe (SAZ). The rationale for the choice of key OSH stakeholders is as depicted in Table 1.

Table 1. Key OSH stakeholders and rationale for their selection.

According to the NSSA factories classification system, factories are stratified as follows: A (Large~100 and above employees), B (Medium~51–99 employees) and C (Small~1–50 employees) as shown in Table 2.

Table 2. Distribution of manufacturing companies according to the NSSA factories classification system.

A sample size of 309 employees was determined by applying the Slovin’s formula at an error margin of 0.05 according to the formula below;

n=N/1+Ne2

Where;

n: sample size.

N: proportion of the population.

e: margin of error = 0.05.

n = 1,356/[1 + 1,356 (0.05)2]

n = 309

The sample size was 22.79% of the study population thereby providing confidence on its representativeness of the sample as it was more than 10% generally considered by many researchers as good enough sample size to authenticate the research findings. Each manufacturing factory was anonymized by being given a unique reference code (identifier) that consisted of a unique number and two distinct letters, one representing nature of manufacturing business (letters T, F, E and O representing Timber based, Food manufacturing, Engineering and Other Manufacturing respectively) and the other representing class of the manufacturing factory [A (large ~100 and above employees), B (medium~51–99 employees) and C (small~l-50 employees)] respectively. Anonymization of the identity of the factory was paramount to uphold confidentiality of participating companies and their representatives so as to offset possible risks of victimization and institutional reputational damage. The sample size was proportionately distributed (Table 3) to all the 30 manufacturing factories in Mutare manufacturing industry according to the formula (58):

Table 3. Proportion of sample sizes as determined by Slovin’s formula.

n1=Xnx309N = 1,356

Where;

n1 = Proportion of sample size in a particular manufacturing factory.

Xn = Number of the workers in a particular manufacturing factory.

N = Total target population in the manufacturing industry of Mutare.

Simple random sampling technique that entailed application of random number tables was used to sample the 309 worker respondents for questionnaire administration. A rotary method was utilized to select the sample for worker respondents from the manufacturing industry of Mutare. A semi-structured questionnaire was chosen to extract data from workers owing to its ability to collect comparable data as well as to ensure achievement of anonymity and confidentiality which was paramount in boosting the questionnaire response rate. The simple random sampling technique was chosen owing to its ability to ensure equal probability of selection for each worker respondent in the sampling frame thereby enhancing the representativeness of the sample (59) which is critical in aiding generalizability of the findings in the manufacturing industry of Mutare. More importantly simple random sampling technique was ideal to enable the application of inferential statistics to draw meaningful conclusions that generalized the characteristics of the population. Involvement of workers as respondents was critical as it resonated well with observations by several authors that worker participation is an irreplaceable ingredient in successful implementation of OSHMSs (60–62). Stratified random sampling technique was used to draw 10% of the workers from the questionnaire respondents (total of 309 employees) for further data elucidation through follow up interviews basing on the acceptability of 10% of the study population as sufficient sample size in a survey (63, 64). The distribution of the number of interviewees from the worker constituency is tabulated in Table 4.

Table 4. Distribution of the number of interviewees from the worker constituency.

Questionnaire administration was also purposively extended to 30 and 11 respondents from the Top manager and Safety and Health Officer’s categories, respectively. This was necessitated by the need to collect comparable data from Top managers and Safety and Health Officers that would answer the research objectives.

Stratified purposive sampling technique was used to select 10% apiece of the Safety and Health Officers and Top managers for further in-depth data elucidation through interview administration. A Safety and Health Officer and a Top manager were targeted as interviewees because they are critical in OSHMSs implementation, hence were expected to be privy to factors that influence the implementation of safety systems. Purposive sampling technique was deployed to select one informant from each of the identified key OSH stakeholders (NSSA, EMCOZ, ZCTU, MPLSW, SAZ, ILO and Academia) for further in-depth interviews. Purposive sampling is a non-probability sampling technique that allows the researcher to use personal judgment to select the study respondents based on the basis of the knowledge of the population, its elements and the nature of your research aims (65). Purposive or judgmental sampling informed the selection of safety and health officers, top managers and key OSH stakeholders owing to the need for the researcher to extract specific in depth data that best answered the research objectives. Cronbach’s alpha (100) was applied on the questionnaires to assess their reliability. An acceptable reliability coefficient of 0.85 was found considering the generally acceptable Cronbach alpha reliability coefficient of 0.70 and above in most research situations (66).

Secondary data was extracted from past OSH research papers, ILO OSH conventions, OSH policy and legislation in Zimbabwe, OSH encyclopedia and other relevant OSH textbooks, OSH journals and NSSA’s records on factory inspection, registration and occupational injuries statistics among other sources. Key guiding words and phrases for internet search were established with the objectives of the research in mind. The key guiding words or phrases utilized included among others; Challenges of implementing OSHMSs, OSHMSs implementation in developing countries/developed countries, factors influencing OSHMSs implementation, employee involvement in safety management, safety culture in OSH management, management commitment in OSHMSs and safety training and awareness in OSH management. Figure 2 is a schematic representation of the strategy for secondary data internet search.

Figure 2. Schematic representation of secondary data search strategy. Source: researchers.

2.4 Variables for analysis 2.4.1 Factory size

Several authors have confirmed factory size as a proxy variable for implementation of OSHMSs (11, 12, 22, 23, 67, 96). Based on this understanding, the study explored a hypothesis to establish whether there was an association between factory size and implementation of OSHMSs in the context of the manufacturing industry of Mutare.

Hypothesis 1.

H0: There is no association between factory size and the implementation of OSH Management System.

H1: There is association between factory size and the implementation of OSH Management System.

According to Nordlöf et al. (67), a company size is normally measured by either the company’s turnover or the number of employees. A more universal measure of the number of employees was adopted to determine the factory size for each manufacturing company. The NSSA factories registration database that captures factory sizes was utilized to establish the number of employees at each manufacturing factory. Furthermore, the number of workers in each factory was validated by data provided by Human Resources departments of respective companies.

2.4.2 Employee involvement

Employee involvement in OSH was found to be strongly linked to employee commitment in OSH management (17, 60). Based on this observation by Tejamaya et al. (17) and ISSA (60), the study made a hypothesis to establish whether there was an association between employee involvement and implementation of OSHMSs in the context of the manufacturing industry of Mutare.

Hypothesis 2.

H0: There is no association between worker involvement and the implementation of OSH Management System.

H1: There is association between worker involvement and the implementation of OSH Management System.

An instrument that generally measures employee involvement cannot be found in literature (98); hence the researcher was motivated to design this measure by considering all best practices for employee involvement as revealed in literature. The following 9 factors were therefore adopted and used in this study to portray the state of employee involvement in OSH management in the manufacturing industry of Mutare: evaluation of PPE, establishment of OSH policy, Safety and Health committee, safety communication, safety audits and inspections, safety promotional programmes (safety talks, competitions, safety drills), risk assessment, incident and accident reporting, incident, and accident investigation. Questions and statements aligned to the 9 parameters for measuring employee involvement in OSH management in the manufacturing industry of Mutare were formulated and answered using a Likert scale with 5 options (Table 5) acknowledged by McLeod (68) as handy in allowing the respondents to indicate their positive to negative strength of agreement regarding a given question or statement.

Table 5. Likert scale.

2.5 Data analysis and presentation 2.5.1 Descriptive and inferential statistics

Descriptive statistics were grouped into defined data sets according to the research objectives, analyzed, presented in statistical manner using frequent tables, and pie charts and then discussed continuously in a descriptive manner. In terms of inferential statistics, the independent variables in this study were factory size and employee involvement and the dependent variable was implementation of OSH management system. Responses to questions that contained the variables of interest were coded to ease the application of Statistical Package for Social Science (SPSS) software, version 16 in the determination of association between variables of interest. Chi Square test of independence was performed at 5% significance level to test whether there was an association between independent variables (factory size and employee involvement) and implementation of OSH management system (dependent variable). The choice of the Chi square test was informed by the fact that both variables (independent and dependent) were categorical and the data to be analysed was from a random sample. Responses for the number of employees in a factory (factory size) were coded as reflected in Table 6.

Table 6. Factory size survey coding sample.

Each of the 9 primary factors that measure employee involvement was coded as follows; Strongly Agree and Agree were coded 1(Yes) and Strongly Disagree, Disagree and Undecided were coded 0 (no). The items were summed together to create that index (scores 0–9) as predictor variable in the main analysis. SPSS software was used to perform a Chi Square test of independence at 5% significance level to establish the existence or nonexistence of an association between independent variables (factory size, employee involvement) and implementation of OSH management system (dependent variable) thereby enabling some inference to be drawn about the characteristics of the population.

SPPS software was used to present the results of the Chi square test of independence in the form of cross tabulations showing the observed and expected counts, Pearson Chi-Square test result and Cramer’s V and Phi coefficient results. The p-value, or Asymptotic Significance of the Pearson Chi – square test was used to determine the existence of a statistically significant relationship between the variables of interest. The p-value that was less than 0.05, resulted in the null hypothesis being rejected and a conclusion being made that there is a statistically significant relationship between the variables. The opposite was true for p-value greater than 0.05.

Cramer’s V and Phi coefficient are vital measures for assessing the strength of association between two categorical variables (69). The two measures were applied to assess the strength of association between independent variables (factory size, employee involvement) and dependent variable (implementation of OSH management system) with a normalized value between 0 and 1. The Phi and Cramer’s V results were interpreted in accordance with Table 7.

Table 7. Interpretation of Phi and Cramer’s V.

2.5.2 Interview and secondary data analysis and presentation

Data from interviews was extracted from the written notes and recorded audios and compiled according to the research objectives. A comparative analysis was done to synthesize and group the data into defined data sets according to similarities and differences. Based on the research objectives, similar thoughts from the interview data were quantified and tabulated as exemplified in Table 8.

Table 8. Interview sample findings.

Significant differences of thoughts from the interview data were noted. The interview data was presented in a descriptive manner in the results and discussion sections to augment other data sources. Secondary data was synthesized and reviewed in a descriptive manner to augment other data sources.

2.6 Ethical considerations

Ethical conduct has increasingly received greater attention globally in the field of research in response to society’s expectation of greater accountability (70). Respondents’ consent was sought prior to the commencement of the data collection exercise through the administration of a consent form that was voluntarily signed independently by both the respondents and participating manufacturing factories without any form of coercion. Participating respondents and manufacturing factories were anonymized in line with the Committee of Publishing Ethics (71) assertion on the need to avert the potential risks of irreparable reputational institutional damage and victimization of research participants. World Health Organization (WHO) Covid 19 guideline (72) was implemented to guarantee a strict adherence to covid 19 measures that included sanitization, utilization of face masks, maintenance of social distancing and temperature screening. Highest level of professionalism, beneficence, justice, confidentiality and personal integrity (73) was exercised during questionnaire and interview administration so as to ensure that the respondents understood the purpose of the study and were comfortable throughout the entire research process. Bailey (74) lamented the risk of misinterpretation and misrepresentation of facts in the process of gathering data, hence the researcher granted the respondents an opportunity to validate the representativeness of the research paper before it was submitted for publishing.

3 Results

The results section covers the questionnaire and interview response rates, an exploration of the factors enhancing implementation of OSHMSs in manufacturing industry of Mutare, and development of a framework to promote the factors that enhance OSHMSs implementation in the Manufacturing industry of Mutare.

3.1 Response rate

A worker questionnaire response rate of 82.2% was achieved as a total of 254 questionnaires were successfully returned for analysis out of the anticipated 309 questionnaires (Figure 3).

Figure 3. Worker questionnaire response rate.

Analyses for questionnaire validity produced 180 (70.9%) valid questionnaires. One hundred percent (100%) and 87.1% of questionnaires distributed to OSH practitioners and Top managers, respectively, were valid for data analysis. All (100%) of the targeted interviewees (workers, Safety and Health Officers, Top managers, and key OSH stakeholders) were successfully interviewed. Response rates for both questionnaires and interviews were good enough to guarantee the authenticity and validity of the research findings taking cognizance of Njogu et al. (11) proclamation of the acceptability and validity of a response rate of 70% and above in a study.

3.2 Factors enhancing implementation of OSHMSs in manufacturing industry of Mutare

As reflected in Table 9, the generality of the respondents agreed that strong senior management commitment, involvement and support (89%), strong employee involvement and participation (91%), good safety culture (93%), provision of adequate resources (89%) and training of all personnel on the importance of OSH management systems (90%) were the top five factors enhancing implementation of OSH management systems in manufacturing industry of Mutare.

Table 9. Factors enhancing implementation of OSHMSs in manufacturing industry of Mutare.

Application of Chi square test at 5% significance level with 1 degree of freedom to test the existence of an association between employee involvement and implementation of OSHMSs revealed a Pvalue of 0.001 which was less than the 0.05 significance level (Chi square test results shown in Tables 10, 11). As the p-value was less than the 0.05 significance level, the null hypothesis (H0) was rejected and the alternative hypothesis (H1) was accepted. A conclusion was drawn from the test result that there was an association between employee involvement and implementation of OSHMS implementation.

Table 10. Employee involvement * OSHMS Implementation Cross tabulation.

Table 11. Pearson Chi-Square tests for association between employee involvement and OSHMS implementation.

Application of Phi and Cramer’s V to assess the strength of association between employee involvement and implementation of OSH management systems revealed a Phi and Cramer’s V value of 0.542 (Table 12) which was greater than 0.25 thereby implying the existence of a very strong relationship between employee involvement and implementation of OSHMSs.

Table 12. Phi and Cramer’s V symmetric measures for strength between employee involvement and OSHMS implementation.

The Chi square result therefore confirmed the strong view by most respondents (91%) that strong employee involvement and participation was a key factor in enhancing implementation of OSHMSs. The majority of key stakeholder interviewees’ (93.8%) and safety and health officers (100%) concurred with the overall opinion of the generality of the respondents on the top five factors enhancing implementation of OSHMSs. Furthermore, all the key OSH stakeholders were agreed that training of all personnel on the importance of OSH management systems and how to implement them was a key enhancing factor to OSHMSs implementation as it had a bearing on the manifestation of other factors. Most of the Top managers (90%) interviewed corroborated the general view by key OSH stakeholders by asserting the criticality of harnessing knowledge on OSHMSs through training; however, they lamented lack of adequate human and financial resources as an impediment to execution of the trainings especially in organizations categorized as SMEs (small to medium enterprises). A categorical analysis revealed that training of workers on OSH was more pronounced in Timber based (76.9%) and food manufacturing (61.8%) companies than in engineering (42.9%) and other manufacturing (0%) companies. Furthermore, the results revealed that most of the employees that received occupational safety and health training after joining their respective organizations were working in Timber based and Food manufacturing organizations that had an appointed safety and health officer and that had implemented an OSHMS.

A significant number of respondents (84%) as reflected in Table 9 cited the need for a mandatory law for OSHMSs implementation as a factor that enhances implementation of OSHMSs in the manufacturing industry of Mutare. Augmenting this view, NSSA interviewees asserted the importance of having a robust OSH legislation that captures the minimum requirements for an OSHMS as a tool to compel organizations to take up OSHMSs. However, NSSA bemoaned the low levels of OSH enforcement at workplaces owing to inadequate provision of operational resources as a drawback to realization of positive results even in the event that the legislation is reformed to legalize establishment of OSHMSs. This bottleneck of low levels of OSH enforcement was echoed by most workers (58, 3%) and key OSH stakeholders (62, 5%) that rated OSH enforcement in the country to be below satisfactory. Majority of the workers rated their organization’s overall compliance to OSH legislation as poor (61, 1%) whilst others rated their organization’s OSH compliance as satisfactory (32.2%), good (3.9%) and very good (2.8%).

Provision of adequate resources was highlighted as a factor enhancing implementation of OSHMSs by 77.8% of the workers and 89% of all the research respondents. It is interesting to note from the results that most of the worker respondents in all the categories of the manufacturing industry of Mutare that concurred on the provision of adequate resources as an enhancing factor to OSHMSs implementation described their remuneration as poor [timber based (37.4%), food manufacturing (43.4%), engineering (42.9%) and other manufacturing (66.7%)]. ZCTU acknowledged the importance of provision of adequate resources as a factor propelling the implementation of OSHMSs, however, it emphasized on the need to buttress this factor with other factors considering the available evidence in literature that attests to unavailability of OSHMSs even in organizations with healthy financial resources