Paper:Identification of OHS-related factors and interactions

Identification of OHS-related factors and interactions among those and OHS performance in SMEs

鑑別影響中小企業職安衛績效的因素與各因素間的交互作用

Source：Safety Science 49 (2011) 216–225

Authors: Enrico Cagno, Guido J.L. Micheli , Sara Perotti

Abstract

An enterprise can modify several factors that impact on the Occupational Health and Safety (OHS) performance.

Within the implementation of the E-merging project (financed by INAIL, the Italian National Institute for Insurance against Occupational Accidents) – to improve safety in Small- and Medium-sized Enterprises (SMEs) – development context, a thorough literature review, supported by later practitioners’ suggestions, has been performed in order to identify the factors which can be related to the OHS issue.

Then, the mutual interactions among the identified OHS-related factors and the interactions among the OHS-related factors and the OHS performance have been identified for SMEs and tested on the basis of two existing data sources, i.e. the INAIL most recent dataset and a survey carried out among SMEs in the metalworking industry. This allows to understand the root causes of some evidences, which enables entrepreneurs and managers to plan interventions for the improvement of the OHS performance.

結合文獻回顧與實務界的建議鑑別出可能影響中小企業的職安衛績效因素；然後經由兩個不同的資料來源測試各因素間的交互作用。結果可事業單位改善環安績效之參考。（來自義大利的研究）

摘要當中看不出牛肉

1. Introduction

1.1. OHS issue and SMEs                  

緣由：

There is evidence to show that SMEs do not manage health and safety as effectively as large enterprises.中小企業職安衛績效較大企業差的現象

對於此一現象的解釋：

This is generally due to a limitation – with respect to LEs （大企業）– of human, economic and technological resources (Micheli and Cagno (2010) and Beaver (2003)

Small Enterprises lack of capacity to assess and control risks in an effective way. (Hasle and Limborg (2006) and Champoux and Brun (2003)

The role of the low level of occurrence of accidents and injuries a SME can experience lowers risk perception, alters approach to risk control and changes the management priorities. Thus, only large severity accidents and injuries can have a beneficial and long term impact on OHS management system, but it can often be too late to intervene.  Hasle et al. (2009)

這個見解比較有創意=>低發生頻率的(嚴重)事故容易讓人低估風險，只有發生重大的事故時，職安衛管理才會受到衝擊與發生改變(然而通常為時已晚)

The characteristics of SMEs are so different that it is terribly difficult and expensive for general preventive efforts to reach all SMEs (Walters, 2001) and become effective with a SME manager has to face in the day-by-day enterprise running are plain: in SMEs he/she is often also the owner and has no (or a very little) team to deal with all the company activities. 

1.2. The E-merging project (see also Micheli and Cagno (2010))

說明此一計畫的來龍去脈

This is also coherent with the European Agency for Safety and Health at Work (2004) and Tait and Walker (1998), who state that a simple but adequate system of safety management for SMEs is necessary but hard to achieve; and also with Walters (2001), who states that it is difficult and expensive for preventive efforts to reach all SMEs.

……

2. Identification of OHS-related factors and interactions（摘錄）

2.1. Factors and interactions from literature review

The literature review gave as an output a referenced list (Table 1) of the OHS-related factors for which at least one interaction is empirically proven (i.e. that has a robust evidence of existence).

In Appendix A, a brief description of all the factors is provided.

從以上文獻資料彙整上，可以看到幾個影響安衛績效主要的關鍵因素與文獻質證發現的關連性與交互作用

公司規模影響管理承諾、風險分析與督導

管理承諾影響溝通、雇用程序與訓練

第一欄總共列了18項因素

第二欄列出了哪些可能影響這些因素的前因(例如任務型態、管理承諾與公司規模等)；（I）則代表間接影響

第三欄，則是代表這些因素衝擊的後果，例如態度、發生工傷的頻率等；（I）則代表間接衝擊

第四欄則代表參考文獻（似乎以歐洲地區的為主）

附錄A的部份列各項可能的相關因素

這樣的條列方式沒有層次感與邏輯

個人試圖把它改成以下形式：

員工階層level：

性別、年齡、臨時員工比例、外籍勞工比例

組織與運作管理階層：

安全程序與管理系統、溝通機制、作業程序、人力資源承諾(薪資)、員工與環境安全意識（5S水準）、管理承諾（員工流動與離職率）、設備品質

公司特質階層：

所在地、作業特性、公司型態、環境風險因素、

感覺以上三個階層間的因素交互影響，難以單獨釐清

這個研究的野心很大，這等於是在描繪工業安全管理的地圖

2.2. Factors and interactions from an expert panel review

接著找來了12位專家，試圖把以上文獻回顧找出的因素與關連性做進一步的分類

The panel of experts was composed of twelve practitioners of different expertise and coming from different knowledge fields, but with a specific experience related to SMEs:

[1] occupational medicine: two experts – 10–26 years expertise;

[1] health and industrial hygiene: six experts – 8–34 years expertise;

[1] OHS managers: four experts – 10–24 years expertise.

At the first step experts were separately interviewed and asked to identify all of company OHS-related factors and their interactions and interactions among those and OHS performance in SMEs.  Experts also tried to bundle the factors into groupings in order to identify different areas of competence and responsibility to manage in a SME.  They identified the following groupings: management, company characteristics, safety climate, indexes, working environment and manpower characteristics. In Table 2, column 3, groupings the factors belong to are reported.

表2的前面3欄和表1 相同

第四欄列出的此一關聯性專家的命名分群，

其中第2/3欄（*） 代表專家認為兩者間的關聯性可能不存在

第5欄X者，代表專家為此一關聯性存在顯著

以上文獻回顧與專家的看法/猜測，可以將各因素間的關連性匯整為圖1

中間的的Indexes包含三項變數(MEI, Frequency, Magnitude) 代表安全的產出績效

其他Management、Safety Climate、Company Characteristic、Manpower Management & Working Environment And Manpower Characteristic 等五大方塊，應該代表解釋安全績效的因素

3.1. The INAIL dataset

用義大利的產業資料進行實證

The first test makes reference to the full dataset of the years 2003–2005 (i.e. the newest and complete data available for Italy) that INAIL – territorial office of Lecco – has given Politecnico diMilano the exclusive right for using the most recent and completedataset available for the years 2003–2005 for data analysis. Of course, only data related to SMEs were considered. Unfortunately, no statistic analysis could be performed on the frequency (which should be aggregated at company level), due to privacy reasons.

只是很簡單的用ANONOVA來做群組間的差異檢定，致命傷是：沒有各公司的工傷頻率資料

3.2. A survey among SMEs in the metalworking industry

The questionnaire was administered to 396 SMEs in the metalworking sector of the Province of Lecco (Northern Italy), containing closed-format questions and divided into three main sections – (1) the role of safety in the enterprise, (2) policies and guidelines for safety management and risk prevention, and (3) critical economic, legislative and operational issues, accident rate (frequency), more urgent interventions.

The response rate was 27.5%, consisting of 84 Small- and Micro-sized Enterprises and 25 Medium-sized Enterprises.

On the basis of the available data, the test was carried out in two ways: single interactions among OHS-factors, then multiple interactions with respect to frequency, have been considered.

On the other hand, it has been possible to statistically test through ANOVA the impact of the following factors (in alphabetical order)on the magnitude of the accidents:

[1] age;

[1] company scale;

[1] employment contract (specifically, ‘temporary job’);

[1] gender;

[1] sector;

[1] task;

[1] working time (specifically, ‘day of the week’).

For the ANOVA, accidents ‘‘in itinere” and with a magnitude lesser than three lost days were not considered (in order to possibly avoid respectively bias and underreporting).

The single interactions – using the Fisher–Freeman–Halton non-parametric test. 

have been considered on the basis of the available data:

[1] company scale vs. resources;

[1] company scale vs. risk analysis, inspections and audit;

[1] management commitment vs. communication and feed-back

system;

[1] management commitment vs. training;

[1] resources vs. equipment quality;

[1] resources vs. Personal Protective Equipment (PPE) usage and

status;

[1] resources vs. training;

[1] training vs. correct operative procedures;

[1] training vs. PPE usage and status.

As for the multiple interactions – using ANOVA – between ‘frequency’ and the OHS-factors, the following factors (in alphabetical order) have been considered:

[1] clear task definition;

[1] company scale

[1] correct operative procedures;

[1] equipment quality;

[1] PPE usage and status;

[1] management commitment;

[1] non-EU workers;

[1] risk analysis, inspections and audit;

[1] sub-sectors (i.e. ‘sector’): machining, metallurgic, machine

construction, facilities, electronic and electro-mechanical;

[1] training.

4. Results and discussion

As for the ANOVA results reported in Table 3 (‘OHS-factors’ –‘magnitude’ from database INAIL),

顯示：不同的年齡、公司規模、行業別間的員工安全態度是有顯著差別，與先前文獻的發現一致。

至於其他的項目的驗證結果與文獻發現之間存在著差異

備註：

用不同的資料得出不盡相同的結果，理所當然也顯然還有些爭議存在。

表4、5是另外的一些檢定結果

整個結果的精華彙整可看圖2

顯然受限於資料，一些變數間的關連性沒有辦法驗證

例如：安全氣候

雖然有哪些因素影響安全績效與如何發生影響的機制是一個black box（與學者各說各話），但是這個研究好歹已經整理出一些頭緒

5. Conclusion and further research

這個研究把所有可能的相關因素，再彙整成五大因一大果，並且藉由專家學者的參與與猜測，找出了20條新的關連

‘magnitude” of accidents – usually less investigated than ‘frequency’: a number of factors seem to have a significant influence (‘age’, ‘company scale’, ‘employment contract’, ‘gender’, ‘sector’, ‘task’, ‘working time’). As far as this is concerned,

three new interactions with ‘magnitude’ have been empirically confirmed – ‘gender’, ‘task’, and ‘working time’. This is particularly interesting, because from a OHS management point of view, while ‘gender’ and ‘task’ are not assessed as factors on which is simple to intervene in the SME context, the ‘working time’ factor can be easily exploited as a powerful leverage.

As for the five ‘OHS-factors’ interactions already tested in literature – namely, ‘company scale-risk analysis, inspections and audit’, ‘management commitment-communication and feed-back system’, ‘management commitment-training’, ‘training-correct operative procedures’, ‘training-PPE usage and status’, they have been confirmed. Nevertheless, it has to be pointed out that from

a SME OHS management point of view, only the ‘training’ factor with the two interactions with ‘correct operative procedures’ and ‘PPE usage and status’ seems to be interesting.

As for the interactions ‘OHS-factors’ and ‘frequency’, it is noteworthy that the five out of six interactions already tested in literature – namely, ‘clear task definition’, ‘company scale’, ‘management commitment’, ‘sub-sector’ and ‘training’ – are confirmed, but only ‘clear task definition’ and ‘training’ are factors

on which is simple to intervene in SMEs. In addition, a new interaction (‘PPE usage and status’) is confirmed by the statistical validation and this factor is also one on which is simpler to intervene.

從研究顯示，雖然公司規模、產業作業特性對於事業安全績效會有先天的影響，但就如何幫助中小企業提升安全績效而言，可以建議從：控管工作時數、落實訓練與PPE穿戴、還有清楚的指派說明任務這幾點著手

（但個人感覺這從實務的角度來說是個屁話=>中小企業就是因為先天規模與資源不足，所以在這幾點方面才無能為力。）

這篇文章的創意：

1.      非常宏觀=>相較於幾家公司的安全文化量測

2.      整合了四大面向的資料來源=>文獻的研究資料、專家學者的意見、整個義大利2003-2005的資料、還有金屬業的調查資料

就研究方法而言，要再想一想哪些數量方法可以呈現各項因素間的關連性遠近，以及其使用限制（這點要先自己想一想，免得meeting的時候浪費老師的時間）

另外作者畫的圖也很有學問，就此一研究內容而言，圖2比較不會引起誤會（也難過我碩士論文的研究架構圖會被修理）

就這樣的探索型的研究而言，還是要看資料的完整和豐富程度，這點卻也是研究工業安全績效最大的困難：太多相關的解釋因素，實務上卻又不可能做這樣完整普查與工廠調查。所以雖然有許多文獻和研究，然而都只有鑑別出來片段的因果關聯，==>這點不得不佩服這三位作者的心血與付出，幫大家建構出(中小企業)公司/事業單位階層的安全相關因素地圖。

而另外這個研究未來要去面對的罩門與裂縫在於：如何把”管理”與”安全氣候”這兩大因素進行無縫接合與整合；這裡Management的衡量是一家公司發一份問卷，大概看訓練、資源投入、管理承諾與作業安全程序等幾個問項（沒提到是Y es or No亦或五點尺度）；而一般安全氣候的衡量，反而是針對公司內不同職務與階層發放問卷，則麼樣才算與代表該公司的整體安全氣候？

其次更有野心的挑戰在於：如何衡量不同因素的貢獻度(類似多元回歸的方式)？而作者群也有野心，這篇文章只是第一集。