ࡱ> *,%&'()xbjbjVV 4<<l& C(k 8 " $M2)1 112[FFF1f  F1 FF$ xw;4Jq02BZ\ B&FV*D- 22Fd 1111 :WORKING CONDITIONS AND EFFICIENCY IN MANUFACTIRING ENTERPRISES OF THE SPLIT-DALMATIA COUNTY (REPUBLIC OF CROATIA) Mario BOGDANOVI }eljko MATELJAK Abstract Organisational efficiency of an enterprise depends on the workers' attitude and the existing working conditions. Therefore good working conditions lead to good attitude to work and regularly result in numerous benefits: higher productivity, better capacity utilization, higher coefficient of inventory turnover, shorter inventories period, reduced scrap, shorter production cycle, shorter delivery time, shorter delays, minimized idle run in production process, improved work energy and health in workers, lower rate of absenteeism, lower costs due to injuries at work and occupational diseases, lower rate of sick leaves, reduced fluctuation costs, and better work satisfaction and motivation in general. This paper presents a research into basic elements of working conditions (temperature, humidity, airing, lighting, noise, vibrations, radiation, cleanliness, colours, tidiness and organization of the workplace, and other important conditions mentioned by the surveyed workers)and organizational efficiency (product and service quantity and quality, utilization of available human and capital resources, ability to predict problems and ways of solving them, workers' familiarity with innovations, adaptability to changes, workers' adaptability in contingencies)in manufacturing enterprises of the Split-Dalmatia County (Republic of Croatia). Measuring of work conditions was carried out by a six-scale (0-5) Likert-type questionnaire, whereas perceived organizational efficiency was measured by a five-scale (0-4) Likert-type questionnaire. The research was carried out on the sample of seven manufacturing enterprises from different industries with the total of 144 respondents. The analysis of results was carried out on two levels: a) Overall working conditions in all the surveyed manufacturing enterprises (determining descriptive data, arithmetic means and standard deviations, and correlating each element of working conditions to organizational efficiency). b) Working conditions in each of the seven manufacturing enterprises to determine specific working conditions statistically significant for a particular industry. The research results determine the frequency of particular positive and negative working conditions in manufacturing enterprises of the Split-Dalmatia County as well as statistically significant correlations of particular working conditions to organizational efficiency at two analysis levels (overall for all enterprises and for each one in particular). Key words: working conditions, organizational efficiency, manufacturing enterprises, Split-Dalmatia County, Republic of Croatia. 1. INTRODUCTION Correlation between working conditions and business results (organizational efficiency) and the impact of working conditions on organizational efficiency have been researched in terms of different contents of working conditions in companies. Namely, the concept of working conditions has a wide content. Thus, for example, the research of working conditions can focus on detrimental and beneficial factors influencing performance which can be divided into three groups: a) Objective physical-chemical working conditions that have a direct impact on human body such as temperature and its oscillations (cold, heat), air humidity, lighting, vibrations, air purity and pollution (fumes, dust, dirt), noise, radiation (ultraviolet, x-ray, radioactive, magnetic and other forms of radiation originating from equipment, e.g. in welding), lighting, available space, cleanliness of materials to be processed, suitable tools and appliances, cleanliness and tidiness of the work area, etc. (Rasanen et al., 1997; Bulat, 1976; Stevenson, 2009; Fischer et al. 1998; Gavhed and Toomingas, 2007; Kroemer and Grandjean, 2000; Drobac, 2006; Saurin and Ferreira, 2009, Slack et al., 2010). b) Psycho-physical working conditions by which the worker responds to performance requirements referring to the effect on human physiology (static work, dynamic work, physical work, intellectual work) and referring to repetitive activity of the same group of muscles, to holding and carrying objects, walking, cognitive-emotional engagement that can result in stress, etc. (Cf. Rasanen et al., 1997.; Bujas, 1964.; Platonov, 1966.; Laird and Laird, 1964.). c) Psychosocial working conditions that indirectly affect human organism and are influenced by the working group. These may be: conflicts between co-workers, conflicts between subordinates and superiors, perception of job insignificance, competition between co-workers, perception of work (dis)organisation, job (in)security, job content, social conditions of work, way of work planning, perception of workspace (in)convenience, e.g. colours, music, spatial layout, feeling of alienation and monotony, feeling of frustration and irritation, lack of trust between employees, and generally poor working and psychosocial climate and corporate culture resulting in reduced or wrong motivation (Laird&Laird, 1964, Cohen et al., 1992; Stevenson, 1993; Rasanen, 1997; McCormick and Ilgen, 1996.; Petz, 1987.; Greenberg and Baron, 1997; Frieling at all, 1997, Laitinen et al., 1998; Fredriksson et al, 2001; Skargren and Oberg, 1999; Ostry et al., 2001; Boakovi, 2006, Jablonska et al., 2006). Besides the above mentioned working conditions there are also those that can be classified over all the three categories, such as: stressful job (various forms of stressors), workspace tidiness, working time (long hours and tiredness of commuters), shift work and night work, (im)possibility of rest and total regeneration of employees, teamwork, safety at work, job security, equality of blue-collar and white-collar workers, occupational and health safety, ethical-legal protection (violation of employees rights may result in stress, resistance and lower productivity), strain due to inconvenient appliances, tools and other equipment (Veljovi et al., 2006; Cigula et al., 2002). Good working conditions are indispensable in living and working improvement systems and beside their ethical dimension they lead to optimal effort in workers which causes increased labour productivity (Bulat, 1976). Consequently, it is obvious that working condition are a complex issue undoubtedly affecting labour efficiency. Therefore it is important to determine which are they and how to treat them in order to improve organizational efficiency. The aim of this research was to determine the correlation between working conditions and organizational efficiency, and to determine which working conditions are vital for efficiency in a particular industry. In accordance with this aim, the research problems were defined in the following way: What is the correlation between working conditions and organizational efficiency in manufacturing companies of the Split-Dalmatia County in Republic of Croatia? Which are the crucial (statistically significant) working conditions in manufacturing companies from different industries (manufacturing of car parts, metal processing, textiles, shipbuilding, fish processing, manufacturing of dairy products, alcoholic and non-alcoholic beverages)? 2. RESEARCHING CORRELATION BETWEEN WORKING CONDITIONS AND ORGANIZATIONAL EFFICIENCY IN MANUFACTURING ENTERPRISES OF THE SPLIT-DALMATIA COUNTY 2.1. Research method The starting point of this research was that working conditions in manufacturing enterprises could be examined by a comprehensive questionnaire. For that purpose a questionnaire was created dealing with physical working conditions (see Appendix 1). It was also assumed that organizational efficiency could be validly measured as perceived organizational efficiency, and for that purpose an already tested and for manufacturing enterprises adapted questionnaire was used (Domovi, 2000, Bogdanovi, 2010, see Appendix 2). Socio-demographic characteristics of respondents were also collected, suc as sex, age, qualifications, position within the organization hierarchy, and net monthly salary (see Appendix 3). The starting hypothesis was that there was positive and significant correlation between good working conditions and organizational efficiency, while there is negative and significant correlation between poor working conditions and organizational efficiency. To determine this correlation it was necessary to carry out the correlation research. Working conditions were measured on the Likert-type scale (0-5), while organizational efficiency was measured on the Likert-type scale (0-4). Reliability of the internal consistency type of organizational efficiency was preliminarily determined on Croatian manufacturing enterprises, which was high, i.e. alpha=0.97 (Bogdanovi, 2010), and on the smaller sample of manufacturing companies in the Split-Dalmatia County it was a bit lower but satisfactory alpha=0.85. Using questionnaires as measuring instruments physical working conditions were determined in various enterprises of the Split-Dalmatia County as independent variable and organizational efficiency as dependent variable. Procedure and respondents The questionnaire was sent to target enterprises. Also, where it was possible the researchers personally communicated with them in order to get an insight into real working conditions in the particular industry. The research comprised 144 respondents from seven manufacturing companies in the Split-Dalmatia County of whom 68% were males and 32% females. Their age structure was: 15% were 19-30, 16% were 31-40, 42% were 41-50, 24% were 51-60, and 3% were above 60. The dominant age group was 41-50. In terms of qualifications their structure was as follows: 5% with elementary education, 72% with secondary education, 9% with two-year post-secondary school qualifications, and 14% with university qualifications. In terms of organisational positions 69% were blue-collar workers, 27% were white-collar workers and 4% were managers. In terms of salary their structure was: 24% under 3,000 kunas, 52% between 3,000 and 5,000 kunas, 19% between 5,000 and 7,000 kunas, 3% between 7,000 and 9,000 kunas, 1% between 9,000 and 11,000 kunas, and 1% between 11,000 and 13,000 kunas. The dominant salary range among respondents was 3,000-5,000 kn. 3. RESULTS AND SHORT DISCUSSION ON THE EMPIRICAL RESEARCH RESULTS 3.1. Sample characteristics The research comprised manufacturing companies in the Split-Dalmatia County in the Republic of Croatia (N=7). The sample structure in terms of the number of respondents is shown in the Table 1. Table 1. The structure of the sample with respect to the number of respondentsName companyFrequencyPercentValid PercentCumulative PercentAD Plastik1611,111,111,1Adriacink1812,512,523,6Galeb Omi1812,512,536,1Brodotrogir4128,528,564,6Sardina Postira2013,913,978,5Mljekara MILS1812,512,591,0Dalmacijavino139,09,0100,0Total144100,0100,0Source: research date In terms of size the manufacturing companies comprised in the survey are classified in compliance with the Croatian Accounting Law (NN, 109/07). Consequently, three companies are of medium size (50-250 employees), while four companies are large (more than 250 employees). The share of respondents follows the size of the company therefore companies with the largest number of respondents are also of the largest size and vice versa (e.g. 28.5% of respondents are employees of Brodotrogir, the largest company among seven, while 9% of respondents are employees of Dalmacijavino, the smallest company among them). 3.2. Working conditions and efficiency of surveyed companies In response to the first research problem, i.e. the question concerning the general correlation of working conditions and efficiency of the surveyed companies, correlation analysis was carried out, whose results are presented in the Table 2. Table 2. Means, standard deviations and correlations of individual working conditions and company performance of Split-Dalmatia County with their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,160,661,000-High / low temperature2,811,25-0,1740,038(Bad (polluted) air2,501,48-0,288 0,000((Sultriness / high humidity2,611,24-0,1980,018(Good lighting3,061,610,272 0,001((Pleasant colours in the workspace2,331,550,413 0,000((Noise3,381,28-0,078 0,355Vibration2,821,54-0,2110,011(Radiation2,361,75-0,2180,010(Workspace cleanliness3,171,370,368 0,000((Well arranged workspace2,491,370,405 0,000((Organization of work2,691,180,501 0,000((Untidiness3,481,45-0,259 0,002(( Source: research date Note: ( correlations significant at p<0.05 (( correlations significant at p<0.01 The Table 2. firstly shows the arithmetic means of measured efficiency and working conditions. Organizational efficiency of the surveyed manufacturing companies proves to be average, i.e. at the level of M=3.16. The arithmetic means of particular working conditions are M=2.33-3.48 and indicate that in the Split-Dalmatia County the existing working conditions may be favourable and unfavourable. The standard deviations of all working conditions are s=1.18-1.75 which indicates that variations may be quite large, or that the perception of working conditions varies from company to company. Consequently, in the course of further investigation working conditions were analysed in each of the companies as a representative of a particular industry. The unfavourable (poor) working conditions are averagely present (M=2.50-3.49) as: untidy working space M=3.48, noise M=3.38, vibrations M=2.82, sultriness M=2.61, uncomfortable temperature M=2.81, and bad air M=2.50. If these general results on poor working conditions could lead to any conclusions, then such frequently mentioned poor working conditions should be purposely eliminated. The only unfavourable working condition that was not mentioned to a disturbing extent (according to criterion M<2.50) was radiation with M=2.36. An insight into favourable working conditions showed especially low grading (<2.50) in: workspace colours M=2.33, workspace tidiness M=2.49. Untidy workspace clearly indicates that organizational environment is inappropriate in terms of tidiness, and with inappropriate colours (which is not so much a question of cost as the concern of management) this may be seen as a connotation of negligence, which is surely one of the crucial reasons for average efficiency in the surveyed companies (M=3.16). Working conditions averagely graded are: work organization M=2.69, cleanliness M=3.17, good lighting M=3.17. Naturally, these average results obtained for favourable working conditions also depart from the optimum (M=5.00), therefore they should also be targeted for improvement. Furthermore, the unfavourable working conditions presented in the Table 2 (excessive temperature, bad air, sultriness, noise, vibrations, radiation, and workspace untidiness) are negatively correlated with efficiency in all the surveyed companies and are all statistically significant, except noise (r=-0.078, p<0.05). Thus the correlation of noise with efficiency proved to be almost zero, which could be explained by the lack of disturbing noise in most of the surveyed manufacturing companies. The highest negative correlation with efficiency was shown by bad air (r=-0.288; p<0.01), workspace untidiness (r=-0.259, p<0.01), radiation (r=-0.218; p<0.05) and vibrations (r=-0.211; p<0.05). All the favourable working conditions (good lighting, pleasant colours, workspace cleanliness, tidiness, and good work organization) were positively and significantly correlated with efficiency, and were all statistically significant. The highest positive correlation (r>0.350) with efficiency was found in: good work organization (r=0.501, p<0.01), pleasant colours in the workspace (r=0.413, p<0.05), workspace tidiness (r=0.405, p<0.01), cleanliness (r=0.368, p<0.01). Good lighting also proved to be an important factor of good productivity, although in terms of correlation it ranked only fifth (r=0.272, p<0.01). These general findings on favourable and unfavourable working conditions and their correlation with efficiency may lead to some conclusions. In manufacturing companies of the Split-Dalmatia County the working conditions proving to be highly correlated with good efficiency are ranked as follows: Good work organization. This proves to be the crucial work condition as it has highest positive and statistically most significant correlation with organizational efficiency (r=0.501, p<0.01). The respondents graded this working condition with a suboptimal average grade (M=2.69), which means that this condition absolutely has to be improved. Pleasant colours in the workspace. Workspace in some manufacturing companies seems to be quite poorly maintained, bleak and cheerless (which is the personal perception of researchers when visiting these companies). The respondents recognized this by grading it M=2.33. Pleasant colours are also positively and statistically significantly correlated with efficiency (r=0.413, p<0.01). This working condition could be improved at a relatively low cost of regular maintenance using some pleasant colours instead of the standard ones. Well arranged workspace (good ergonomic arrangement of the workspace, easily accessible materials and equipment, work free of unnecessary effort, non-physiological positions and tiredness due to repetitive activities of the same muscle groups) proves to be the third statistically significant work condition in terms of correlation with efficiency (r=0.405, p<0.01). Unfortunately, according to the arithmetic mean (M=2.49) it is not at a satisfactory level in the surveyed companies and should be improved. Workspace cleanliness proves to be statistically significant and positive correlate of organizational efficiency (r=0.368, p<0.01). It can be generally stated that cleanliness increases effectiveness and commitment. It can also indirectly affect efficiency and in the surveyed companies it was graded M=3.17. Cleanliness in food processing industry is a crucial working condition, so this result would there be considered poor rather than average. Therefore this working condition is to be treated with regard to the industry. Good lighting proves to be statistically significant and positively correlated with efficiency (r=0.272, p<0.01), and in the workspace where appropriate lighting is to be provided to ensure productivity it is also a crucial working condition. In the surveyed companies it was averagely graded (M=3.06). Bad (polluted) air (due to fumes, smoke in welding, dust, paint and varnish evaporation, bad smells, poor ventilation, etc.) has the highest statistically significant negative correlation with efficiency in manufacturing companies (r=-0.288, p<0.01). In the surveyed companies it is recorded at an average level (M=2.50). Untidiness also has statistically significant negative correlation with company efficiency (r=-0.259; p<0.05). Untidy workspace with heaps of waste or materials lying about in a disorganized manner or poorly maintained premises (e.g. broken windows, dampness, peeling walls, defective machinery, etc.) may negatively affect company efficiency. The respondents have also identified this factor at a high level (M=3.48), which certainly calls for action. Radiation, although not occurring in all companies, has a high weight in some of them (e.g. in welding or caused by some appliances) so this factor also has statistically significant negative correlation with efficiency (r=-0.210, p=0.01). For all the surveyed companies it is relatively low M=2.36, but with highest standard deviation s=1.75 (variating in different companies). As already noted, this condition has to be considered partially, i.e. for those companies where some kinds of radiation do occur. Vibrations caused by machinery are also negatively correlated with efficiency (r=-0.211, r<0.05), although ranked only ninth, because employees in the surveyed companies were not exposed to them unlike for instance forestry workers, ploughmen, or compressor workers. Vibrations are recorded at a medium level (M=2.82) with a rather high standard deviation s=1.54. Sultriness/high humidity due to inadequate of entirely missing air conditioning (summers in the Split-Dalmatia County are hot, which with high humidity can create discomfort) was reported as a negative factor in some companies, so this condition proves to be statistically significant and negatively correlated with organizational efficiency (r=-0.198, p<0.05). Overall sultriness was recorded at a medium level (M=2.61, with s=1.24), therefore it may be concluded that where premises are air-conditioned this will not be a problem. Temperature, i.e. excessive heat/cold has statistically significant negative correlation with company efficiency (r=-0.174, p<0.05), although not so pronouncedly as could be expected, because in some companies premises are adequately heated and air-conditioned (M=2.81, s=1.25). Noise is statistically significantly correlated with efficiency in overall results (r=-0.078, p>0.05) which is to some extent surprising, because the findings recorded in literature are contrary to that. The probable reason for that may be the awareness of management and attention paid to this problem, even though this factor is recorded at a medium level (M=3.38). As has already been noted, the same working conditions are not equally important for efficiency in all the surveyed manufacturing companies because this primarily depends on the type of industry. Therefore it was necessary to examine working conditions and efficiency in each of the companies belonging to a particular industry in order to determine which working conditions are important, which are marginal, and which are statistically insignificant. With the obtained results it is possible to give recommendations to each of the companies (as the representative of a particular industry) about the working conditions that should be upgraded to increase productivity. 3.3. Working conditions in particular enterprises and their effectiveness This section presents the findings on working conditions and efficiency for each manufacturing company with regard to the respective industry. In other words it responds to the second research problem: Which are the crucial (statistically significant) working conditions in manufacturing companies from different industries (manufacturing of car parts, metal processing, textiles, shipbuilding, fish processing, dairy, alcoholic and non-alcoholic beverages)? The Table 3. shows the findings for AD PLASTIK PLC, Solin. Table 3. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise AD PLASTIK PLC., Solin (production of parts for cars from artificial materials) with their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,370,601,000-High / low temperature2,251,39-0,1870,487Bad (polluted) air2,001,63-0,4600,073Sultriness / high humidity2,261,39-0,1570,560Good lighting3,251,620,2690,313Pleasant colours in the workspace2,751,18-0,0850,754Noise2,441,37-0,5560,025(Vibration2,691,45-0,4260,100Radiation2,931,39-0,2080,457Workspace cleanliness4,001,10-0,4060,119Well arranged workspace3,071,10-0,2470,374Organization of work2,811,050,5950,015(Untidiness2,941,570,0170,950 Source: research date Note: ( correlations significant at p <0.05 ( ( correlations significant at p <0.01 It is obvious that manufacturing of plastic car parts in AD PLASTIK PLC, Solin records significant correlation of two working conditions with efficiency: Noise (r=-0.556, p<0,05) and Work organization (r=0,595, p<0,05) Consequently, for this company it is recommended to take action that will reduce noise and enhance work organization. The employees stated the following problems related to the noise and organization of the working process: inadequately connected work areas, pressure due to tight deadlines, inadequate regulation of heating and air conditioning appliances. They also complained about: neon lighting, excessive heat during summer poor interpersonal relations, inequality in rewarding and implementation of regulations. The Table 4. presents the findings for ADRIACINK PLC, Split. Table 4. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise ADRIACINK PLC, Split (metal production) and their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,430,371,000-High / low temperature3,001,28-0,3060,217Bad (polluted) air2,891,23-0,4960,036(Sultriness / high humidity3,061,16-0,3460,160Good lighting3,611,290,5040,033(Pleasant colours in the workspace3,611,040,5890,010(Noise4,000,84-0,3270,185Vibration2,891,37-0,310,605Radiation2,611,94-0,0590,815Workspace cleanliness3,830,990,5050,033Well arranged workspace3,721,070,3330,177Organization of work3,180,880,6370,006((Untidiness2,671,19-0,1050,679 Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 It is obvious that in the metal processing industry work conditions statistically significantly correlated with company efficiency are: Bad air (r=-0.496, p<0.05), Good lighting (r=0.504, p<0.05), Pleasant colours (r=0.589, p<0.05), Work organization (r=0.637, p<0.01). The employees stated the following problems related to: bad air (poor ventilation in the plants, poor ventilation in general, especially when dealing with acids, sultriness) work organization (inadequate organization of the work process from preparation to assembling, lack of space, occasional shortage of equipment) The employees also complained about: extreme heat in summer lack of motivation due to low salaries The Table 5. presents the findings for GALEB PLC, Omis, which manufactures textile products. Table 5. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise GALEB PLC., Omis (textile manufacturing) with their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,270,541,000-High / low temperature3,391,42-0,4530,059 (border)Bad (polluted) air3,281,49-0,4200,083Sultriness / high humidity3,281,67-0,4630,053 (border)Good lighting3,061,730,2590,300Pleasant colours in the workspace1,591,730,4280,087Noise4,001,46-0,4220,081Vibration3,671,68-0,2030,420Radiation3,181,94-0,1550,554Workspace cleanliness2,831,620,5860,011(Well arranged workspace1,941,550,2560,305Organization of work2,671,370,3380,170Untidiness4,221,26-0,1800,475 Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 Here it is obvious that working conditions that are significantly correlated with company efficiency in the textile industry are: Workspace cleanliness (r=-0.586, p<0.05), and Two marginal (weakly significant) work conditions: b1. Sultriness/high air humidity (r=-0.463, p=0.053) b2. Excessively high/low temperature (r=-0.453, p=0.059). The workers complained about: cramped workspace in the plant, too many people in a small area, dampness, draught, excessive noise, dust, run-down premises, lack of air-conditioning, need for at least better ventilation, lack of resolution and agreement in management negatively affecting the work process and workers who are expected to do the work disregarding conditions, inadequate involvement and rewarding of employees, obsolete and run-down work chairs. The Table 6. presents survey results for BRODOTROGIR PLC, Trogir. Table 6. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise BRODOTROGIR PLC., Trogir (production of ships) and their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness2,820,671,000-High / low temperature2,931,08-0,2760,085Bad (polluted) air2,851,32-0,405 0,009((Sultriness / high humidity2,680,99-0,2280,157Good lighting1,981,42-0,3200,843Pleasant colours in the workspace1,411,290,434 0,006((Noise3,291,15-0,3800,016(Vibration3,101,46-0,3980,011(Radiation2,631,46-0,3230,042(Workspace cleanliness2,101,260,3280,039(Well arranged workspace1,801,230,486 0,002((Organization of work2,201,270,363 0,021(Untidiness3,661,56-0,1940,231Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 Working conditions significantly correlated with work efficiency in BRODOTROGIR, which is involved in shipbuilding, are: Bad air (r=-0.405, p<0.01), Pleasant colours (r=0.434, p<0.01), Noise (r=-0.380, p<0.05), Vibrations (r=-0.398, p<0.05), Radiation (r=-0.323, p<0.05), Cleanliness (r=0.328, p<0.05), Tidiness (r=0.486, p<0.01), Work organization (r=0.363, p<0.05). The employees of BRODOTROGIR complained about: lighting, disposition of materials, tools, and cranes, ventilation, weather conditions (outdoor work) poor work organization noise, dust, radiation (in the welding process) welding and grinding without ventilation, run-down machinery polluted air heat and cold idleness, lack of discipline, disagreements among workers excessive bureaucracy, low wages, poor education of staff, poor quality tools inadequate safety working hours (six hours during summer) lack of coordination between working units problems with purchasing of materials and tools lack of working discipline. The Table 7. shows the survey results for SARDINA POSTIRA Ltd, Postira. Table 7. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise SARDINA POSTIRA Ltd, Postira (production of fish products) and their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,870,341,000-High / low temperature2,750,85-0,5100,829Bad (polluted) air1,351,23-0,0100,966Sultriness / high humidity2,051,28-0,0140,952Good lighting4,420,900,0950,698Pleasant colours in the workspace3,171,250,3740,127Noise3,601,100,2590,269Vibration2,151,600,0020,994Radiation1,001,41-0,4390,060Workspace cleanliness3,840,830,3560,135Well arranged workspace3,350,810,3200,169Organization of work3,550,51-0,0170,943Untidiness2,801,24-0,1130,635 Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 As shown in the Table 7, in this company there are no working conditions that are statistically significantly correlated with efficiency. In spite of such findings, it is to be noted that the workers complained about: poor air-conditioning in the plant, heat and cold, noise, dampness and sultriness, hard physical work, obsolete production equipment. The Table 8. presents the survey results for DALMACIJAVINO Ltd, Split. Table 8. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise DALMACIJAVINO Ltd, Split (production of alcoholic and nonalcoholic beverages) and their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness2,500,411,000-High / low temperature2,381,66-0,0450,883Bad (polluted) air1,771,090,3910,186Sultriness / high humidity2,311,180,0001,000Good lighting3,850,99-0,2040,505Pleasant colours in the workspace2,351,850,3530,237Noise2,461,390,2530,405Vibration2,381,450,2430,423Radiation2,151,820,5390,057 (border)Workspace cleanliness3,540,88-0,1200,709Well arranged workspace2,081,120,1800,556Organization of work2,381,190,5480,053 (border)Untidiness3,921,320,0001,000Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 It is obvious that in this company, which manufactures alcoholic and non-alcoholic beverages, there are two working conditions of marginal statistical significance with efficiency: Radiation (r=0.539, p=0.057) Work organization (r=0.548, p=0.053) The employees in this company complained about: lighting, vibrations, heat/cold, lack of responsibility in senior management, disorganisation, poor communication, obsolete technology, inadequate staff structure, ventilation and air-conditioning. The Table 9. shows the survey findings for MLJEKARA MILS Ltd. Split. Table 9. Means, standard deviations and correlations of individual working conditions and efficiency of enterprise MLJEKARA MILS Ltd., Split (production of milk and dairy products) and their statistical significance Work conditionsMean (M)Standard deviations (s)Effectiveness (Pearsonov r)Statistical significance (p)Effectiveness3,050,471,000-High / low temperature2,611,20-0,3450,160Bad (polluted) air2,781,520,1300,607Sultriness / high humidity2,500,79-0,2300,359Good lighting2,821,59-0,0340,897Pleasant colours in the workspace2,471,179-0,0310,906Noise3,561,040,0020,995Vibration2,441,500,0300,905Radiation1,831,76-0,2220,376Workspace cleanliness3,561,150,1930,443Well arranged workspace2,181,19-0,3270,201Organization of work2,501,100,3220,193Untidiness4,061,11-0,2740,270 Source: research date Note: ( correlations significant at p <0.05 (( correlations significant at p <0.01 As can be seen from the Table 9., in this company, which manufactures dairy products, there are no working conditions that are significantly correlated with efficiency. However, the employees complained about: obsolete equipment, noise, vibrations, bad smells, dampness, low ceilings, poor ventilation, cramped workspace, slippery floors. poor interpersonal relations, work organization. As already noted, the surveyed enterprises belong to different types of manufacturing industries and therefore it is possible to provide some recommendations for each industry in terms of particular working conditions. The results obtained in this study and its heuristic value reveal a wide possibility of research concerning work rationalization, involving technical, economic and psychosocial rationalization. It is obvious that the reason for suboptimal competitiveness of Croatian companies can be attributed to suboptimal working conditions and suboptimal work rationalization. Therefore any research into working conditions will be seen as an important contribution to improvement of productivity and efficiency in manufacturing companies. CONCLUSION Working conditions are an important factor of efficiency in each job. Therefore they are considered to be a factor of productivity, which is one of the factors of company competitiveness. The correlation between different working conditions and business performance, or organizational efficiency, has been investigated and proved in a large number of research studies. In those studies both harmful and desirable elements were highlighted, which can be divided into three, or rather four basic groups: a) objective physical-chemical working conditions, b) psycho-physiological working conditions, c) psychosocial working conditions, d) mixed working conditions. This research focused on the first group of working conditions that may be called physical-chemical working conditions. The aims of the research were to determine the correlation of working conditions with organizational efficiency, classify the conditions crucial for organizational efficiency, and give recommendations for their improvement on the sample of manufacturing companies of the Split-Dalmatia company in Croatia. The aims of the study were achieved by determining statistically significant correlations of working conditions with organizational efficiency on two levels: a) overall (including all the surveyed companies, and b) for each particular company as a representative of an industry. In accordance with these aims the research problems were set, for which the responses are here summarized. The response to the first problem, i.e. the issue of general correlation of working conditions and efficiency of all the surveyed manufacturing companies, was obtained by correlation analysis. For all the surveyed manufacturing companies the following working conditions were ranked as crucial for efficiency: Good work organization proves to be the key working condition due to its highest statistically significant positive correlation with organizational efficiency (r=0.501, p<0.01). Pleasant colours in the workspace are statistically significantly and positively correlated with efficiency (r=0.413, p<0.01). Well arranged workspace (good ergonomic arrangement of the workspace, easily accessible materials and equipment, work free of unnecessary effort, non- physiological positions and tiredness due to repetitive activities of the same muscle groups) proves to be the third statistically significant work condition in terms of correlation with efficiency (r=0.405, p<0.01). Workspace cleanliness proves to be statistically significant and positive correlate of organizational efficiency (r=0.368, p<0.01). Good lighting proves to be statistically significant and positively correlated with efficiency (r=0.272, p<0.01). Bad (polluted) air (due to fumes, smoke in welding, dust, paint and varnish evaporation, bad smells, poor ventilation, etc.) as an unfavourable working condition has the highest statistically significant negative correlation with efficiency in manufacturing companies (r=-0.288, p<0.01). Untidiness also has statistically significant negative correlation with company efficiency (r=-0.259; p<0.05) Untidy workspace with heaps of waste or materials lying about in a disorganized manner or poorly maintained premises (e.g. broken windows, dampness, peeling walls, defective machinery, etc.), as well as outdoor work that should be performed indoors due to weather conditions may negatively affect company efficiency. Radiation, although not occurring in all companies, has a high weight in some of them (e.g. in welding or caused by some appliances) so this factor also has statistically significant negative correlation with efficiency (r=-0.210, p=0.01). Vibrations caused by machinery are also negatively correlated with efficiency (r= 0.211, r<0.05), although ranked only ninth, because employees in the surveyed companies were not exposed to them. Sultriness/high humidity due to inadequate of entirely missing air conditioning (summers in the Split-Dalmatia County are hot, which with high humidity can create discomfort) was reported as a negative factor in some companies, so this condition proves to be statistically significant and negatively correlated with organizational efficiency (r=-0.198, p<0.05). Temperature, i.e. excessive heat/cold has statistically significant negative correlation with company efficiency (r=-0.174, p<0.05), although not so pronouncedly as could be expected, because in some companies premises are adequately heated and air-conditioned. Noise is not statistically significantly correlated with efficiency in overall results (r=0.078, p>0.05). As all working conditions are not equally important in all types of manufacturing companies (due to different manufacturing industries) the research into correlation of working conditions with efficiency was extended in terms of particular companies, which responded to the second problem set in this study. So the findings for AD PLASTIK PLC, Solin (manufacturing of car parts) show that working conditions statistically significantly correlated with efficiency are: noise (negative correlation), and work organization (positive correlation). Besides these, the workers also emphasized: lighting, heat, poor interpersonal relations, and perception of inequality in rewarding and implementation of regulations for all employees. In the metal processing industry the findings for ADRIACINK PLC, Split show that the working conditions statistically significantly correlated with efficiency are bad air (negative correlation), good lighting, pleasant colours, and work organization (positive correlation). The employees complained about bad air and work organization (inadequate organization of the working process from preparation to assembling, shortage of space). In the company GALEB PLC, Omi, (manufacturing of textile products) working conditions significantly correlated with efficiency are workspace cleanliness (negative correlation), while sultriness/humidity and excessive temperature are marginal. The two marginal working conditions have negative correlation. The workers also emphasized inadequate working conditions such as cramped workspace, dampness, noise, lack of air-conditioning, inadequate involvement of workers, obsolete and run-down work chairs, lack of resolution and agreement in management. The working conditions significantly correlated with work efficiency in BRODOTROGIR PLC, Trogir, (shipbuilding) are: bad air, noise, vibrations, radiation, work organization (negative correlation), and pleasant colours, cleanliness, tidiness (positive correlation). In this company employees complained about lighting, ventilation, exposure to weather conditions, noise, dust, excessive cold/heat, bureaucracy, poor quality tools, inadequate safety, etc. In SARDINA POSTIRA Ltd, Postira (fish processing) and MLJEKARA MILS Ltd, Split (manufacturing of dairy products) there are no working conditions that are statistically significantly correlated with organizational efficiency. However, their employees complain about poor air conditioning, excessive temperature, noise, dampness and sultriness, hard physical labour, ventilation, interpersonal relations, work organization. Finally, in DALMACIJAVINO Ltd, Split (manufacturing of alcoholic and non-alcoholic beverages) only two working conditions are marginally correlated with efficiency: radiation and work organization (positive correlation). Employees in this company complained about lighting, vibrations, heat/cold, lack of responsibility in management, poor communication, disorganization, ventilation, and air-conditioning. According to the obtained results it is obvious that the work in manufacturing companies of the Split-Dalmatia County can be significantly improved in terms of technical rationalization by upgrading working conditions, and that it can be better organized. This should enhance productivity and organizational efficiency, which should lead to better competitiveness of Croatian manufacturing companies. 6. LITERATURE BOOKS Bulat, V. (1976). Organizacija proizvodnje: Analiza i sinteza. Beograd: Izdava ko informativni centar studenata Bogdanovi, M. (2010). Organizacijska klima u hrvatskim proizvodnim poduzeima. Doktorska disertacija. Split: Ekonomski fakultet Bujas, Z. (1964). Osnove psihofiziologije rada: Uvod u industrijsku psihologiju Zagreb: Izdava ki zavod JAZU Cigula, M i dr. (2002). In~enjerski priru nik: Organizacija proizvodnje. Zagreb: `kolska knjiga Cohen, A. R.; et. al. (1992). Effective Behavior in Organizations: Cases, Concepts, and Student Experience. Fifth Edition. Homewood & Boston. Irwinn. USA Domovi, V. (2000). Odnos izmeu akolskog ozra ja i u inkovitosti akole. Doktorska disertacija. Zagreb: Filozofski fakultet. Drobac, S. (2009). Organizacija rada: Ergonomija ra unalne i programske opreme. Zagreb: Fakultet elektrotehnike i ra unarstva Greenberg, J., Baron, R. A. (1997). Behavior in organizations. International Edition: Prentice Hall. New York. USA Kroemer, K. H. E., Grandjean, J. (2000). Prilagoavanje rada ovjeku: Ergonomski priru nik. Jastrebarsko: Naklada Slap Laird, D. A.; Laird, E.C. (1964). Prakti na poslovna psihologija. Zagreb:  Panorama McCormick, E. J., Ilgen, D. (1996). Industrial and organizational psychology. London: Routhledge Petz, B. (1987). Psihologija rada. Zagreb: kolska knjiga Platonov, K. K. (1966). Problemi psihologije rada. Zagreb: Panorama Slack, N.; et, al. (2010). Operations management. Harlow: Financial Times Stevenson, W., J. (2009). Operations management. New York: McGraw-Hill Stevenson, W., J. (1993). Operations management. New York: McGraw-Hill ARTICLES Bokovi, G. (2006). Mobbing-psihosocijalni aspekti, In: Mobbing, Druatvo psihologa Primorsko-goranske ~upanije, Rijeka, pp. 37-58 Fredriksson, K.; et. al. (2001). The impact on musculoskeletal disorders of changing physical and psychosocial work environment conditions in the automobile industry. International Journal of Industrial Ergonomics. 28 (28), pp. 31-45 Fischer, F., M.; et. al. (1998). Working conditions, work organization and consequences for health of Brazilian petrochemical workers. International Journal of Industrial Ergonomics. 21 (21), pp. 209-219 Frieling, E.; et. al. (1997). Effects of team work on the working conditions of short cycled track work: A case study from the European automobile industry. International journal of Industrial Ergonomics. 20 (20), pp. 371-388 Gavhed, D.; Toomingas, A. (2007). Observed physical work conditions in a sample of call centre in Sweden and their relations to directives, recommendations and operators comfort and symptoms. International Journal of Industrial Ergonomics. 37 (37), pp. 790-800 Jablonska, B.; et. al. (2006). Pain among women: Associations with socio-economic and work conditions. European Journal of Pain. 10 (10), pp. 435-447 Laitinen, H.; et. al. (1998). Improving physical and psychosocial working conditions through a participatory ergonomic process: A before-after study at an engineering workshop. International Journal of Industrial Ergonomics. 21 (21), pp. 35-45 Ostry, A., S.; et. al. (2001). Effects of de-industrialization on unemployment, re- employment, and work conditions in a manufacturing workforce. BioMed Central. 1 (1), pp. 1-11 Rasanen, K.; et. al. (1997). Perceived work conditions and work-related symptoms among employed finns. Social Science & Medicine. 45 (45), pp. 1099-1110 Saurin, T., A.; Ferreira, C., F. (2009). The impact of lean production on working of condition: A case study of a harvester assembly line in Brazil. International Journal Industrial Ergonomics. 39 (39), pp. 403-412 Skargren, E.; Oberg, B. (1999). Effects o fan exercise programme on organizational/psychosocial and physical work conditions, and psychosomatic symptoms. Journal of Rehabilitation Medicine. 31 (31), pp. 109-115 Veljovi, F.; et. al. (2006). Agilna proizvodnja u funkciji odr~avanja sigurnosti i kvalitete. Sigurnost. 48 (48), pp. 19-25 }ugaj, M. (1996). Osvrt na racionalizaciju rada, In: }ugaj, M., Bojani-Glavica, Upravljanje organizacijama- lanci, Vara~din: Fakultet organizacije i informatike, pp. 93-115 OTHER SOURCES 30. Interviews with employees of manufacturing companies surveyed. Appendix 1. Please state: NEVER=0; SELDOM=1; SOMETIMES=2; OFTEN=3; VERY OFTEN=4; ALWAYS=5 your agreement with the following statements: NoStatement0123451.In the company it is too hot/cold.2.In the company the air is quite bad.3.In the company it is sultry.4.The lighting in the company is very good.5.The colours make the premises a pleasant place to work in. 6.It is noisy in the company.7.Appliances and engines create vibrations. 8.Electrical appliances and computer equipment emit radiation.9.Workspace is quite clean. 10.Workspace is well arranged.11.Work organization is adequate.12.Workspace should be tidied up. 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excellent 3. To what extent do the employees in your company use the available resources (people, capital, equipment), i.e. how efficiently do they do their work? a) very inefficiently; b) inefficiently; c) with average efficiency; d) very efficiently; e) extremely efficiently 4. How well are possible problems predicted in your company in order to reduce or prevent their negative consequences? a) very poorly; b) poorly; c) averagely; d) very well; e) excellently 5. How well are employees in your company informed about innovations that could affect the manner of working? a) not at all; b) to some extent; c) averagely; d) very well; e) excellently 6. When there is change in your company how fast do employees accept them and adapt to them? a) very slowly; b) slowly; c) neither slowly nor quickly; d) quickly; e) at once 7. How many employees in your company, in your opinion, readily accept change and adapt to it? a) hardly anybody; b) less than a half; c) about half of them; d) significantly more than a half; e) almost everybody 8. How would you evaluate the performance of employees in your company when faced with sudden crises and disruptions? a) very poor; b) poor; c) average; d) very good; e) excellent Appendix 3. Please state your basic socio-demographic characteristics SexMale FemaleAge<19 19-30 31-40 41-50 51-60 >60QualificationsIncomplete elementary school Elementary education Secondary education Post-secondary professional education University degree Higher university degrees (MrSc, PhD) Other:Hierarchy Blue-collar worker White-collar worker Manager Net monthly salary a) up to 3,000 kn b) 3,000-5,000 kn c) 5,000-7,000 kn d) 7,000-9,000 kn f) 9,000-11,000 kn g) 11,000-13,000 kn h) > 13,000 kn  M. Bogdanovi, dr. sc., dipl. oec., prof. psih., Senior Assistant at the Faculty of Economics, University of Split, Matice Hrvatske 31, Split, Republika Hrvatska, e-mail: mario.bogdanovi@efst.hr.  }. Mateljak, mag. oec., Assistant at the Faculty of Economics, University of Split, Matice Hrvatske 31, Republika Hrvatska, Split, e-mail: zeljko.mateljak@efst.hr.  Average is here derived from the school grades scale (1-5), which is the grade good ranging from 2.50 to 3.49.  This perception of working conditions could be confirmed by the personal experience of researchers when visiting some of these companies.  As the level of significance depends on the chosen criterion that in social research is most frequently defined on the risk level of p<0.05, smaller deviations from the settled level are here termed as marginal or weakly significant differences, as the settled statistically significant difference could have been e.g. the risk of p<0.055 or 0.75. Although some norms have to be complied with, the term marginal/weakly significant difference denotes the difference which de facto exists with a somewhat higher risk of making wrong general conclusions based on the sample.  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