Safety Science 48 (2010) 980–990

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Safety Science

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Port safety and the container revolution: A statistical study on human factorand occupational accidents over the long period

Bruno Fabiano *, Fabio Currò, Andrea P. Reverberi, Renato PastorinoChemical and Process Engineering Department ‘‘G.B. Bonino”, University of Genoa, Via Opera Pia 15, 16145 Genoa, Italy

a r t i c l e i n f o a b s t r a c t

Article history:Received 29 December 2008Received in revised form 2 July 2009Accepted 30 August 2009

Keywords:AccidentContainerInjuryPort safetyResponse surface methodology

0925-7535/$ - see front matter � 2009 Elsevier Ltd. Adoi:10.1016/j.ssci.2009.08.007

* Corresponding author. Fax: +39 010 3532586.E-mail address: brown@unige.it (B. Fabiano).

Several factors can affect occupational accident frequency, namely economical factors, technologies used(low automation, discontinuous operating) job design, organization of work/environmental conditionsand human factors. In particular, technological advances in industrial activities can give rise to improve-ment in productivity and in occupational health and safety, but not necessarily simultaneously. Thebeginning of the container transport dates back to 50 years ago, but while containerization changedeverything, from ships and ports to patterns of global trade, its impact on work injuries was not exploredat all. The aim of this paper is to investigate the relationship between work organization, job experience,productivity and occupational accidents, from the starting of the container expansion to nowadays, con-sidering Genoa port (Italy), one of the largest of the Mediterranean Sea. In order to minimize possiblereporting biases, such as underreporting or reclassification to a lower level of severity, injury statisticsare elaborated starting from data collected directly on-site, from internal accident or medical-aid reports.An in-depth statistical analysis on occupational injuries in the years 1980–2006 is carried out, with ref-erence to frequency indexes, mechanism of injury and material causes. The increase of container-shipstraffic and, consequently, the sharp change in port infrastructure involved a rapid modification also inthe work organization, with particular reference to the number and characteristics of workforce(decrease from 5783 to nearly 1000 employees and increase of low experience workers from 28% to74%). The striking high percentage increase of young or low experienced workers in handling container(and performing correlated new tasks) caused a remarkable increase of the risk for occupational injuries.In the studied port, we recorded an increase of the frequency index (injuries per hundred thousand hoursworked) from 13.0 to 29.7. It results that the increased expansion of shipping container utilization is notconnected to a correspondent human factor safety implementation. Main risk factors are pointed out,revealing an increase of accidents due to transport vehicle (+8.3%) and a reduction of accidents causedby substance or materials (�4.5%). These factors show a statistical significant correlation with the newjob tasks. Consideration of these findings may enable managerial solutions and workplace organizationinterventions for the prevention of injuries and safety performance improvement in port activities.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Changing work environment issues can be summarized as newwork organisational forms, new contractual relationships and useof working time, new technologies, changes in the workforce,and changes in occupational safety and health systems (EuropeanAgency for Safety and Health at Work, 2002). However, we mustnotice that, as in different industrial activities, technological ad-vances can give rise to improvement in productivity and in occupa-tional health and safety, but not necessarily simultaneously. In thisrespect, ports experienced fundamental changes in the past dec-

ll rights reserved.

ades due to changes in shipping, cargo-handling technology andworking culture, in particular the introduction of the standard-size,intermodal shipping containers (Beresford et al., 2002). In particu-lar, the beginning of the container transport dates back to nearly50 years ago: on 26th of April 1956, a war surplus oil tanker witha steel reinforcement loaded 58 aluminum containers at a dock inNewark, New Jersey. On 1st May, the ship steamed into Houston,(TX), where 58 trucks took on the metal boxes utilizing a speciallybuilt crane and carried them to their end users. Undoubtedly, theintroduction of container in marine shipping was revolutionary,firstly from the economic viewpoint: before the era of containershipping costs could add as much as 25% to the cost of a given com-modity. The price of freight was cut down by getting ships in andout of ports in hours instead of days, moving goods from ships to

B. Fabiano et al. / Safety Science 48 (2010) 980–990 981

trains or trucks faster, cutting out labour costs and integrating thedifferent form of transportation in the newly intermodal scheme.As reported by Levinson (2006), containerization is a monumentof the most powerful law in economics, that of unanticipated con-sequences. The pros and cons of the container revolution were dee-ply analyzed, mainly from the economical and social viewpoints,concluding that there is a straight line from containerization toglobalization. The simple thing the container did was sharply lowerthe cost of shipping goods from one place to another. However, thecontainer revolution also changed the mechanics of shipping: thelogistics, the speed and the capital structure. As a matter of fact,its impact on port safety and related work injuries is not exploredat all in the scientific literature. In addition, as ports continue topursue complementary business opportunities by diversifying intoproperty development, management of industrial estates andestablishment of free trade zones (Wooldridge and Beresford,1998), it could be said that they are becoming exposed to thehealth and safety issues typical of other large industrial and man-ufacturing operations. After the containerization, port can be de-fined as the interface among different transportation modes, oneof which is maritime transportation. From the safety view point,a noteworthy characteristic is represented by the broad range ofinvolved authors, sometimes characterized by conflicting interests:port authorities, ship masters and owners; berth operators; on-board and port workers; terminal operators; owner and operatorsof different transport modes interacting with the area (rail, road,inland navigation). Occupational risk management in maritimeports assumes high importance, as accidents at industrial portscan results in personnel injury or death, as well as severe environ-mental damages. Marine traffic risk is coupled with transportsafety, shipping efficiency, distribution reliability and loss preven-tion. De and Ghosh (2003) evaluated the relationship between portperformance and port traffic in the context of India, proving thattraffic volume remains a good indicator of port performance. Dar-bra and Casal (2004) showed a clear upward trend regarding thefrequency of accident occurrence, starting from 471 accidentsoccurring in seaports in the years 1941–2002; they concluded thatthe trend is in part attributable to the increase in port activity andthe growth in sea transport of hazardous substances. During thepast 30 years, also the sea transportation of chemicals experiencedsignificant changes, from drum and container use to larger tankers,originally used only for oil products transportation. Chemicalsshipped by containers are gaining increasing popularity with theprocess industry. Discrete storage of hazardous chemicals in trans-portable containers poses different hazards as compared to con-ventional storage installations. The hazards connected withhandling and storage of hazardous materials in port areas mainlyoriginate from the complicated nature of activities taking place,the possibility of hardware failure, either in the ship, or in the in-land and loading/unloading equipment, or from external events,such as bad weather conditions or fire/explosion in a ship close-by Christou (1999). From the safety viewpoint, difficulties arisefrom the fact that the port authority has to depend on documenta-tion provided by shippers, regarding chemical identity, classifica-tion and connected hazards (Roa and Raghavan, 1996). In case ofhazardous release in port area, a realistic assessment of the natureand size of the possible threat and of the resources/plant most atrisk must be performed and intervention time and types to containthe risk on an acceptable level must be selected considering thebehavior of both the vapor and the liquid phase. As an example,a conservative model was recently presented (Palazzi et al.,2004) allowing the attainment of cautious values of the maximumspreading area, corresponding to the maximum vaporization rate,as well as of the complete spreading time.

In this work, the authors consider the effect of containerizationmaking reference to Genoa port (Italy), one of the most important

and ancient in the Mediterranean Sea. As previously remarked, thispaper is focused on the impact of the radical changes induced bycontainers on safety for workers and represents the first attemptto investigate this issue.

2. Material and methods

2.1. Research design

In order to minimize possible reporting biases, such as underre-porting or reclassification to a lower level of severity, injury statis-tics are elaborated starting from data collected directly on-site,starting from internal accident and medical-aid reports of the portcompany, operating, as explained in the following section, at a‘‘quasi-monopoly” regime in Genoa port for a long period. The ana-lyzed reports cover the period 1980–2006 and include all accidentsoccurring among workers (only basic information were availablefor the period 2002–2006). A single reviewer examined all avail-able text reports for each injury, to code basic information onintrinsic and external factors. Data on the injuries included thedate, the nature of the injury, body part involved and materialagent. In particular, factors determined to contribute to the injurywere categorized utilizing, when possible Haddon’s matrix (Rob-ertson, 1998) to distinguish, at least partially, contributions ofagent, human, environmental and organizational factors. Humanfactors included age, real work experience, training; environmentalfactors included weather (wind, ice, rain, etc.), time of the day, dayof the week and month; organizational factor included specifictask, appropriate equipment for the task.

The elaborated indices allow to point out the incidence of acci-dents of the workers exposed to risk and are defined as follows,respectively for the frequency and injury index.

FI ¼ Number of total accidentsNumber of worked hours

� 105 ð1Þ

II ¼ Number of total accidentsNumber of employees

� 103 ð2Þ

Dealing with the particular port context, Eq. (1) differs from thedefinition commonly adopted in other industrial sectors and re-ferred to one million worked hours. In this study, the referenceparameter, ‘‘worked hours”, was calculated accurately fromemployees’ registers, so that frequency index can represent a prop-er instrument of evaluation of accidents dynamics and evolution.

Data directly obtained ‘‘in field” were also compared with theoccupational fatal and non-fatal injury raw data obtained from IN-AIL (National Italian Institute Workers’ Compensation). Contrarilyto data collected on-site, the limiting factors in these last raw dataare that accidents involving less than three days’ absence fromwork, which can occur more frequently than those causing longerabsence, are not considered. In addition, accidents in case theemployment is not regularly signed and registered (e.g. moonlight-ing phenomenon) are not taken into account. Moreover, a concernconnected to the changing work environment is the validity ofaccidents indicators, for example, a decrease of the frequency in-dex might be explained by better prevention strategies, or by theexportation of dangerous activities.

2.2. Time-series

After merging the text related to each injury and descriptorsdata, descriptive statistics were generated on the injury rate, bynature of injuries and body parts injured, according to interruptedtime-series selected as follows. The complete diffusion of contain-ers in the international market required several decades, startingfrom the first containers in 1956. Dealing with Genoa port this rev-

982 B. Fabiano et al. / Safety Science 48 (2010) 980–990

olution took place in the 20 years from 1980 to 2001, so the de-tailed statistical analysis covers three time-series of 4 years, withinthe whole time span considered: the early period from 1980 to1983 corresponding to the start-up of container utilization in Gen-oa port; the maturity period from 1993 to 1996, corresponding tothe widespread container utilization and the period from 1998 to2001, ending just on the 50th anniversary mentioned in Section1 of this paper. After the ‘‘revolution”, a fourth series was consid-ered, namely 2002–2006, elaborating only FI and II data from avail-able injury reports.

2.3. Statistical analysis

In order to obtain a statistical reinforced correlation with theport productivity, we considered Genoa port traffic of containerin term of Twenty feet Equivalent Unit (Teu) per year starting fromtraffic data directly collected on-site.

Starting from (2), the concatenated injury indices were definedas:

CII ¼ IIi

IIi�1100 ð3Þ

Similarly, the concatenated indices of the container port pro-ductivity were calculated as:

CCI ¼ CIi

CIi�1100 ð4Þ

where CIi is the container traffic index of the ith year [Teu year�1].From accident reports we looked for variables showing a statis-

tically significant relationship with injury rate, considering in par-ticular, variables connected to work organization, and workplaceenvironment, socio-economic factors and workforce characteris-tics. Data from the injury records were coded and entered into adatabase for subsequent univariate analysis of variance (ANOVA).Statistical significance was evaluated by the Pearson correlationprocedure and significance testing for correlation coefficient. Ade-

Table 1Teu 103 (Twenty feet Equivalent Unit) container traffic in main European ports, up to the

Year Italian ports

Genoa Gioia Tauro Livorno Napoli La Spezia Tri

1980 258 3061981 284 3031982 230 2831983 238 3701984 296 4541985 325 4751986 316 481 1861987 271 490 2371988 325 480 3121989 238 410 4211990 310 416 4471991 344 411 4571992 338 334 5831993 342 361 171 748 151994 512 371 200 822 141995 615 16 424 235 946 151996 826 572 417 246 872 171997 1180 1449 501 299 616 201998 1266 2126 522 312 732 171999 1234 2253 462 334 843 182000 1501 2653 501 397 910 202001 1527 2488 521 430 975 202002 1531 3009 520 444 975 182003 1606 3149 541 433 1007 122004 1629 3261 639 348 1040 172005 1625 3161 659 374 1024 192006 1657 2938 658 445 1137 222007 1835 3500 702 450 1190

quacy of the model was evaluated using coefficient of determina-tion analysis (R2). It was employed Statistica software trialversion ver. 6.0 (Statsoft, Tulsa, OK). Significant results were ana-lysed adopting response surface methodology (RSM). The last oneis a collection of mathematical and statistical techniques adoptedto optimize different processes (e.g. Dasu and Panda, 2000) and re-cently applied in an occupational safety study related to temporaryworkers (Fabiano et al., 2008).

3. Results and discussion

3.1. Downsizing issues

Containerization was the driving force modifying substantiallythe shipping sector, with development of ‘‘full container vectors”,port infrastructure, as well as number and characteristics of theworkforce. Labour leaders feared the container, but even they werenot prepared for the speed with which it destroyed conventional‘‘water-front job”. Teddy Gleason, New York dock union president,predicted that containerization would eliminate 30% of his mem-ber works; in reality 75% had vanished by 1976. This figure isreproduced with fairly good agreement in Genoa port. In fact, atthe beginning of the first time-series considered (1980), the overallcontainer traffic corresponded to 258000 Teu (Twenty feet Equiva-lent Unit); in 2001 the overall traffic reached 1500000 Teu with anincrease equal to 584%. From 2001 to 2006 the traffic in Genoa portremains nearly constant at this figure, with values ranging from1531000 in 2002 to 1657000 in 2006. As shown in Table 1, thetrend up to the year 2007 is common to several Italian ports, witha striking upswing in the last 12 years for Gioia Tauro (Italy), mov-ing from 16,000 Teu to 3500000 Teu in 2007. A similar trend wasrecorded in Hamburg port (D) (+1163%), Anvers (B) (+1029%), Bar-celona (E) (+710%) and Rotterdam (NL) (+468%). Several modifica-tions were induced by this phenomenon, mainly connected toterminal location and dimension, workforce intensification, with

year 2007.

European ports

este Hamburg Anvers Barcelona Marseille Rotterdam

783 724 186 296 1901907 795 208 367 2100889 846 213 366 2159930 1026 242 355 2314

1073 1248 326 380 25461159 1243 353 488 26551246 1313 341 473 28981451 1437 385 390 28391620 1470 410 393 32001728 1474 440 480 36001969 1549 448 482 36662189 1761 489 447 37832262 1836 552 351 4114

6 2486 1876 501 432 42503 2726 2208 605 437 45390 2890 2329 689 500 47877 3054 2654 767 547 50004 3337 2969 965 620 54004 3550 3266 1095 660 60129 3740 3614 1235 664 63436 4248 4100 1360 722 62751 4689 4218 1411 742 59455 5374 4777 1461 809 65060 6138 5445 1652 833 71435 7003 6064 1916 916 82408 8087 6489 2071 908 92860 8861 7018 2318 941 9654

9889 8176 2398 1000 10790

B. Fabiano et al. / Safety Science 48 (2010) 980–990 983

staff reduction and optimization, as well as widespread diffusion ofPC based technologies for loading and unloading operations. Someof these changes are similar to those experienced by the processindustry for improving economic competitiveness in facing grow-ing global competition. Of the process job types that were commonin the process industry in 1970, about 70% may completely disap-pear by 2020, and the other 30% will change dramatically (Zwets-loot et al., 2006). The trend is going to continue with theglobalization market and the striking emerging economy of theso-called East-Tigers: South Korea, China and India, requiring in-creased quantities of materials and goods to be shipped and trans-ported. In the first period examined, containerization was in thestarting phase with an overall increase in term of Teu in Genoa portcorresponding to 15%. In the middle of the Nineties goods trans-ported by containers exceeded for the first time conventional ship-ping. As shown in Table 1, in the third period, Genoa port reachedfor the first time the figure of 1.5 � 106 Teu globally handled.

As already remarked, this kind of technological innovation in-duced port activities liberalization, a substantial decrease in thenumber of operators and a modification of the characteristics ofthe labour force. In fact, one of the main modification induced bythe widespread containerization has been, in several ports the lib-eralization of port activities with terminal management directedoperated by private companies rather than by public workers. Atthe same time, the number of operators was drastically reduced,with different labour organization and staff optimization. In thissense, technological innovation induced by container representsthe main factor triggering manpower reduction and modificationof the characteristics of the labour force, accompanied by the pro-cess of outsourcing activities. This study considers the peculiarcase of Genoa port where, up to the last period considered owingto a strict defense policy, only employees from a single companywere allowed to operate on all terminals, in connection withemployees of the firms directly managing the different terminals.The direct consequence of this kind of monopoly is that the vastmajority of port manpower is represented by employees fromthe so-called port worker company: a pool of workers operatingeverywhere, upon ‘‘call”, especially during intensification of workand productivity. In the 20 years ‘‘from the beginning to the matu-rity”, the overall number of the company employees was consider-ably reduced, passing from nearly 5000 in the first years of the1980s to a minimum value in 1995 corresponding to 666. By theend of the XX century, the number of employees is constantly

0

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10000

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Em

ploy

ees

Fig. 1. Number of employees in Genoa

around 1000, as shown in Fig. 1. Up to the year 2006, this value re-mains constantly the same. The phenomenon of staff reduction andreorganization was already noticed by Levinson (2006), ‘‘labourleaders feared the container, but even they were unprepared forthe speed with which it destroyed water-front jobs”. Also in Genoa,like ‘‘in ports all over the world, strong-backed, long-shoremengave way to computers and mechanization”. Moreover, we shouldnotice that downsizing has become an extremely popular strategyin today’s business environment. It is used to reduce labour costs inan effort to become more price competitive, especially internation-ally (Nienstedt, 1989). Downsizing was associated with changes inwork characteristics, social relationships and health behaviors. Ma-jor downsizing was associated with increased levels of physicalwork demands, job insecurity and decreased levels of skill discre-tion and participation (Kivimäki et al., 2000).

3.2. Occupational injuries

When one comes to quantitative observations regarding safetyperformance in the three 4-year time-series up to 2001, a notewor-thy negative trend must be put in evidence. As shown in Fig. 2, inthe first years of the 1980s, the average frequency index FI is 12,with a slightly increasing trend. In the middle of the same decade,FI reaches the value of 17.32, while in the middle of the subsequentdecade it goes down to the value of 16. A drastic increase (+229%)is recorded in the last 4 years under in-depth examination, with avalue of 35.29 in 2001. In other words, the frequency of injury forworkers from the company, in Genoa port over the 20 years exam-ined raised by a factor of 300%. It seemed advisable to consider aswell the trend of the injury index, II, i.e. the number of occupa-tional accidents on the total number of employees according toEq. (2). As depicted in Fig. 3, we can evidence II value correspond-ing to 103 in the first period under examination and an upswingtrend, reaching its maximum in the year 2001 with a value of559, corresponding to an average yearly increase over the 20 yearsfrom the beginning to the maturity of 21.1%. The findings reportedhere show a drastic worsening of safety performance indicators inGenoa port workers, with a faster dynamic evolution in the lastyears of the XX century. We must notice that in the last series,2002–2006, II shows a decreasing trend, down to a sort of basic va-lue in the years 2004–2006 corresponding to an average of 305.8(SD 10.5).

1992

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Year

Coop. Company

Total Genoa port

port and in the worker company.

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30

35

40

1980

1981

1982

1983

1993

1994

1995

1996

1998

1999

2000

2001

Year

FI

Fig. 2. Frequency index of accidents referred to worker company in Genoa port over the three time-series up to 2001.

0

10

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30

40

50

60

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1981

1982

1983

1993

1994

1995

1996

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II

Fig. 3. Injury index referred to worker company in Genoa port, over the three time-series.

984 B. Fabiano et al. / Safety Science 48 (2010) 980–990

Assuming a value of 100, as the average number of containermoved in Genoa port in the years 1080–1983, the average numberis 188 in the period 1993–1996, up to reach an average value of544 in the last 4-year period. The trend of containerized port trafficshow a 100% increase in the first 10 years and over a 200% increasein the last 4 years under examination, up to 2001. This value re-mains nearly constant in the subsequent period, up to the year2006.

Fig. 4 shows the average percentage accident distribution dur-ing the whole day, over the three periods deeply considered. By aproper statistical examination of the injury records, it was possi-ble to evidence that no statistical correlation exists between thehour of the day and FI (p > 0.05), even if 57.7% of accidents are re-corded in the first 3 h from the starting of work. Fig. 5 shows theaverage FI index by month, for the three periods examined.Firstly, we must underline that seasonal activity pressure wasalso present before widespread containerization. We should no-tice that during the summer period a sharp increase of the fre-quency index is recorded. The trend, which is dramatically more

remarked in the last period considered, is to be connected tothe intensification of work and productivity per worker, in combi-nation with an increase in overtime (characteristic of summerwith several workers absent for vacation). These well-knownitems were referred to as constituting a set of interacting factorsincreasing injury risk (Saari, 1982). We must notice that higherinjury frequencies are associated to risk transfer (with the elimi-nation of a specific hazard by transferring the risk to another taskor another group of workers).

On the basis of experimental data, we tried to investigatewhether ‘‘new” occupational risks can be connected to container-ization. In the context of changing work environment ‘‘new” isassociated to one of the following items (Koukoulaki et al., 2008):

� the risk was previously unknown and is caused by new pro-cesses, new technologies, new types of workplace, or social ororganisational change;

� a long-standing issue is newly considered as a risk due to achange in social or public perceptions (e.g. stress);

0-6 6-12 12-18 18-24

7,7

20,9

37,8

34,0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Acc

iden

t [%

]

Time [hour]

1980-1983

1993-1996

1998-2001

Fig. 4. Accidents distribution [%] during daily hours, over the three time-series up to 2001.

jan feb mar apr may jun jul aug sep oct nov dec0

10

20

30

40

50

60

FI

Month

1980-19831993-19961998-2001

Fig. 5. Average monthly frequency index, over the three time-series examined up to 2001.

B. Fabiano et al. / Safety Science 48 (2010) 980–990 985

� new scientific knowledge allows a long-standing issue to beidentified as a risk (e.g. repetitive-strain-injury (RSI) wherecases have existed for many years without being identified asRSI because of a lack of scientific knowledge).

The mechanism of injuries, as resulting from data analysis, issummarized in Fig. 6. Overall, throughout the three periods, ‘‘fallfrom elevation”, in many cases associated with slip, represents al-ways the first injury dynamic, followed by the mechanism‘‘smashed by something”. In particular, a high number of accidentsstill involve passively the operators (‘‘smashed by something”)even if with a decreasing trend, possibly connected to hardwareimprovement in safety automatic safeguards during container han-dling. These mechanisms are often to be connected to human con-tributing factors, the most common being inappropriate behavior,followed by safety violations, non adequate training/instructionsand occasionally fatigue. Human factors, such as movement, per-formance and speed of work tasks are increasing being recognizedfor their potential contribution to injuries for slips and trips (Court-

ney et al., 2001). The analysis of the material causes of accidentsoffers the possibility of drawing useful indications: as depicted inFig. 7, we were able to identify the ‘‘labour environment” as themain contributing factor in the three periods, with percentagesranging from 27.6 to 40.9 of the overall injuries. These labour envi-ronment factors were often related to inadequate house-keeping,such as proximity of co-workers, non adequate signaling, etc. Theimportance of accidents directly connected to the work organiza-tion and environment has turned out in several studies on the to-pic, not only in Europe and USA, but also in the emerging markets.For example, over the last years, the Council of Labour Affairs inTaiwan noticed the seriousness of fall and injuring accidents andstrongly encouraged the use of relevant fall protection, e.g. helmet,safety nets, hand rails, safety belts and reins (Chi and Wu, 1997). Itis clear that it is a matter of direct intervention on work organiza-tion and environment within the port, which, though simple, canquite affect risk level for operators: fixed courses, safety rangesand installation of railings, handrails and catwalks. Unfortunately,these interventions are often disregarded.

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Acc

iden

t [%

]

1980-81 15.2 5.4 7.5 30.8 6.6 31.7 2.2 0.61993-96 15.6 7.3 9.2 21.9 9.6 34.0 0.0 2.41998-2001 11.4 4.6 6.8 14.1 6.2 39.6 12.3 5.0

Collisionagainst

Lifting sthg. makingeffort

Injuredhimself with

sthg.

Smashed by sthg.

Crushed by sthg. Fallen down

Accidentwhile

drivingOther

Fig. 6. Dynamics of injuries: average percentage values, over the three time-series under examination up to 2001.

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5

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35

40

45

Acc

iden

t [%

]

1980-83 0.5 17.6 15.2 12.1 29.3 0.3 23.2 1.8

1993-96 0.4 35.8 7.7 1.5 40.9 0.2 12.6 0.9

1998-2001 0.3 25.9 23.9 7.8 27.6 0.4 8.7 1.0

MachinesLoading and

transportmeans

Equipmentand devices

Material,substances

Labourenvironment

Persons,animals,

vegetables

Containers,vessels, etc.

Parts of: equipment,devices etc.

Fig. 7. Injuries material causes: average percentage values, over the three time-series under examination up to 2001.

986 B. Fabiano et al. / Safety Science 48 (2010) 980–990

Weather factors, such as rain, ice, snow and wind were not re-lated with statistical significance (p > 0.05) to FI. This outcome ismainly to be connected to the interruption of activities, by workersof the company, even in case of slightly bad weather.

‘‘Loading and transport” recorded constantly the second per-centage, as determining material cause. This finding points outthe importance of preventive efforts addressing safe areas for oper-ator walking and heavy vehicle transfer, on a large labour area suchas a port. Again, the need of an adequate qualification of the oper-ators must be remarked: each container operation should be con-ducted in strictly accordance with procedures and checklists.Summarizing, the analyses of the accident dynamics and of theimmediate material causes show that, in spite of the developmentof safety technique in both hardware and software, still higher con-sideration is to be paid to the human factor.

3.3. Workforce issues

In order to statistically investigate the influence of the produc-tivity pressure on the accident rate, we correlated the injury index

with the Teu container traffic per year. A good relationship be-tween the injury index II and the productivity is highlighted inFig. 8 up to the year 2001 (Pearson correlation coefficient 0.985;R2 = 0.971). The important role of work experience is well docu-mented from data pertinent to the fourth period examined: not-withstanding constant Teu traffic and constant manpower size,due to the experience that workers gain on-site, II reduces downto a sort of physiological level. Last series evidence the existenceof a sort of ‘‘lag phase” in adapting to new technologies: in thissense this trend needs further investigation. The degree of correla-tion between the injury index and the port productivity is moreevident in the two time-series of observation corresponding toexpansion and maturity, as highlighted in Fig. 9, reporting the ra-tios between the concatenated indices of the injury frequency CIIand of the port productivity CCI (standard deviation 0.12; 95% con-fidence limit 0.083). If compared with results obtained in theprocess and manufacturing industries in Italy (Fabiano et al.,2001), we must put forward that the degree of correlation in portactivities is slightly lower. The presented case-study is ratherimportant as it covers a period of huge transformation connected

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tra

ffic

[10

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]

Injury index

Teu traffic

Fig. 8. Relationship between injury index and productivity (expressed as Teu traffic), over the time span 1980–2006.

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1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

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CII

/CC

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Fig. 9. Injury frequency and industrial production concatenated indices ratio covering the period 1993–2006.

B. Fabiano et al. / Safety Science 48 (2010) 980–990 987

to both containerization and port liberalization culminating by theend of XX century with a strong reduction of operative staff. A largenumber of workers were shifted to pension and only partially re-placed by new workers, so that the overall labour force is composeby nearly 70% by young people and/or first employment). Unfortu-nately, the introduction of new technologies (container) and con-nected staff reduction was not accompanied by enough trainingin new skills or techniques, so that an adaptation period is requiredfor workers to perform adequately in new job tasks and a changedenvironment. In fact, this new labour force is reaching at the end ofthe period under investigation 7/8 years experience and job com-petence and, as depicted in the already mentioned (Fig. 8) this istranslated into lower accident rates, notwithstanding high Teutraffic. In addition, containerization clearly involves automationsuitable to reduce human errors; however automation is likely torequire greater operation competencies and unlearning old rou-tines and may even lead to new kinds of human errors (Zwetslootet al., 2006). As a matter of fact, containerization involved a shiftfrom handicraft to mechanization and a corresponding strong

interaction man–machine in goods handling. In addition, as docu-mented, widespread container utilization is the driving force fordownsizing and utilization of young and inexperienced workers,under the three time-series examined. The importance of the pres-ent research can be highlighted looking at (Fig. 10), where we com-pare FI calculated for the sample under investigation with thetrend in the most hazardous Italian sectors (i.e. Building andWood) and with the overall transport sector (including all meansof transportation, loading and unloading). In the first year of obser-vation (1980), the highest accident rates (FIBuilding = 7.96 and FI-Wood = 7.76) and the average for all Italian industrial sectors(FI = 5.40) compare to FI in port activities equal to 10.74. The max-imum accident rate in of 35.29 per hundred thousand workedhours in 2001 is to be compared with accident rates of 4.19 and3.96, respectively accounting for Wood and Building, being theaverage for all industrial sectors equal to 2.18. Despite the drop re-corded in the last time-series, in 2006 FI in port corresponds to23.17, i.e. a value higher by 457% than the most hazardous sector(Wood 4.11) and higher by 688% than the whole transport sector

0

5

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quen

cy in

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Genoa Port

Building

Wood

Transport

Overall Ind.

[…]

Fig. 10. Frequency index calculated for Genoa port, for the most hazardous industrial sectors and average overall industries in Italy, over the period 1980–2006.

Fig. 11. Response surface plot of number of accidents over the time-series 1998–2001, as a function of job experience and employees age.

988 B. Fabiano et al. / Safety Science 48 (2010) 980–990

(2.94). These findings evidence that containerization and conse-quent downsizing, combined with inexperience and inadequateadaptation to new handling technologies may explain the increasein the accident rate. As an additional reflection, reinforcing theimplications of this study, we must notice that during the periodinvestigated the reporting culture of data utilized in the analysisdid not improve at all, as concerning reliability and accuracy: in

fact we adopt data mining technique directly from internal reporthard copies. Dealing with these raw data, the only improvement isthat nowadays the reporting system is based on electronic data-base and subjected to stringent privacy legislation. On the con-trary, a criticism on traditional accident statistics data concernsnot only Italy, but the worldwide safety community: the problemof improving the organizational memory and the need of a new

Fig. 12. Response surface plot of gravity of accidents (lost time injury) over the time-series 1998–2001, as a function of job experience and employees age.

B. Fabiano et al. / Safety Science 48 (2010) 980–990 989

look at the sort of accident data that are collected and analyzed(Kletz, 1993) are becoming more and more important.

Of primary interest in this study was to examine the human fac-tor, which appears a rather critical issue in Genoa port, after thecontainer revolution. A considerable reduction in the number ofemployees in the company was accompanied by labour turnover,with marked in- and out-flows negatively affecting the profes-sional experience. A notable presence of temporary workers anda concentration of manpower in the lower age ranges (in the per-iod ending with 2001, more than 40% of the employees are in theage bracket 18–24 years), further reduces the level of formationand professional training in such undertakings. By the way, wemust observe that in port activities training per se is not sufficientto replace the direct experience gained directly on-site. Similartrends were also verified in different sectors: on construction sitesin Finland, total accidents and fatal accidents occur more often ingroups characterized by a low occupational status, wage leveland job security (Saloniemi and Oksanen, 1998). In this regard,temporary workers, engaged both in process industries and inother productive sectors, suffer a higher frequency index than in-house workers employed in the same activities. Reasons are tobe traced into lack of experience in the activity, insufficient specificknowledge (formal and informal knowledge) about a particularinstallation and into inadequate training period (Zwetsloot et al.,2006). Analysis of injury records using ANOVA and response sur-face methodology highlighted possible interaction between theaccident number and age and job experience. Results obtained byRSM modelling are depicted in Fig. 11, evidencing that a significantcorrelation was obtained (p < 0.05 and Fvalue = 4.62) with both jobexperience and age. Among the test variables used in the study,by checking the p-values it resulted that job experience had a moresignificant effect on number of injuries (p < 0.032). Fig. 12 shows

the interaction between the job experience and age on the injurygravity (evaluated in term of days lost from work), a statistical cor-relation (p < 0.05), was verified only with job experience (seeFig. 12). This figure evidences that the most advantaged age brack-et, with respect to severity, is in the range 36–55. The experiencefactor (on-site acquired knowledge of new technologies and of spe-cific operations/tasks) is a well-known item determining risk level:in all industrial sectors, the lower job/task experience, the higherthe accident rates. Even if limited to the sample analyzed, it resultsthat old workers make poorer use of new than old technologies andfail to adapt to the new skills, so that accident severity suffers.These observations recalls the importance of training safe proce-dures for the many tasks in which port workers can use alternativeless safe procedures and also the importance of a regular reinforce-ment of these safe procedures (Verhaegen, 1993).

4. Conclusions

The results presented in this paper reveal that the box thatchanged the world has not improved safety conditions in portactivities. Even if containerization induced a considerable stan-dardization and a labour organization more similar to the processindustry one, Genoa port recorded a striking increase of occupa-tional accidents frequency. Main conclusion of the analysis per-formed is that the effect of technology development representedby containerization on injuries is not so effective: as in differentfields of activity, the magnitude, type and distribution of injuryrisks following the implementation of a technological changemay depend on intrinsic characteristic of a new technology, butare also conditioned by other factors, that moderate any main ef-fect of it (Blank et al., 1997). The results on immediate injury

990 B. Fabiano et al. / Safety Science 48 (2010) 980–990

causes are to be considered for setting priorities for improvinghardware to raise safety performance. However, hardwareimprovement is to be accompanied by higher consideration on hu-man factors such as managerial and organizational systems. Theaim of a correct and useful safety practice therefore should be toprovide equipment and procedures able to minimize the possibili-ties of errors by operators, designs avoiding the possibilities ofinjuries in case of operator errors, as well as designs and safeguardsable to prevent injury if an accident occurs. In particular, a specifictraining activity should be addressed to ‘‘young and low experi-enced” port workers. Further effort is needed to investigate possi-ble relationship between age and experience and the causes andtypes of injuries/accidents. The analysis of injuries raises the ques-tion of whether such activities are indeed efficacious in improvingsafety: probably it may require a new ‘‘mind set”, developed overtime, which would somewhat gradually accepted by the workforce(Shannon et al., 1997) addressing, as well, specific needs andopportunities for safety performance improvement. In addition, gi-ven the complexity of the port environment where huge volumesof containers are moved, a suitable training period including pro-fessional training and job tutoring by ‘‘old workers” seems advis-able, so as to increase experience and acquaintance with one’sduties and reduce the probability of an accident. Starting from thisfirst study on the topic, the data collection and its analysis can bedeveloped in other European ports, in order to establish similari-ties or different tendencies.

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