Cybernetic Theory as a New Approach to Studying Workers' Well-being

Abstract

The aim of the present research is to explain why well-being in the workplace is a theme of increasing interest and why many studies have analyzed its functioning and diffusion. From the literature on well-being it is evident that the findings of previous research are sometimes discordant and theoretical models particularly use diverse variables according to different needs and objectives. Despite the influence of a number of different factors, well-being can be studied by looking at three main aspects: physical well-being, mental health, and job satisfaction. The variables influencing it, however, are numerous and often analyzed from different perspectives. Methods of analysis vary across national and disciplinary contexts. The present work is based on a local survey of a small Italian district that investigates two hypotheses about the correlation between locus of control and variables determining work well-being (Spector et al., 2002) and the possibility of using perceptions and desires on the variables influencing well-being as predictors of it. We use the concepts of cybernetic theory and feedback loop (Edwards, 1992). Findings of statistical correlation and hierarchic regression are discussed; limitations and suggestions for further research are presented. [PUBLICATION ABSTRACT]

Headnote

Abstract

The aim of the present research is to explain why well-being in the workplace is a theme of increasing interest and why many studies have analyzed its functioning and diffusion. From the literature on well-being it is evident that the findings of previous research are sometimes discordant and theoretical models particularly use diverse variables according to different needs and objectives. Despite the influence of a number of different factors, well-being can be studied by looking at three main aspects: physical well-being, mental health, and job satisfaction. The variables influencing it, however, are numerous and often analyzed from different perspectives. Methods of analysis vary across national and disciplinary contexts. The present work is based on a local survey of a small Italian district that investigates two hypotheses about the correlation between locus of control and variables determining work well-being (Spector et al., 2002) and the possibility of using perceptions and desires on the variables influencing well-being as predictors of it. We use the concepts of cybernetic theory and feedback loop (Edwards, 1992). Findings of statistical correlation and hierarchic regression are discussed; limitations and suggestions for further research are presented.

Keywords: work well-being, cybernetic theory, desires and perceptions

JEL classifi cation: L00

(ProQuest: ... denotes formula omitted.)

1 Introduction

In recent years well-being has gained growing attention from many disciplines. It is a fundamental theme in the study of health, diet, emotions, beauty, and work. This increasing attention on global well-being (especially of individuals) can be attributed to social, psychological, and health motivations that are exogenous to the organizational context. These disciplines, however, also have great infl uence on organizational science and condition its researches and studies. Thanks to private strategies, organizations promote and improve well-being in order to achieve goals and high performance. It is common to see diff erent new amenities off ered by corporations to their own workers in terms of services, such as laundry, baby-sitting, nursery, fi tness or wellness centers: these are initiatives aimed at benefi tting workers and improving their health status. It should be noted as well that strong legislation is in force to guarantee at least safety in the workplace. Both these aspects help to maintain or improve workers' health status, and to make their working conditions acceptable. The positive feedback in terms of economic results, performance, activities, communication, and teamwork shows that it is profi table for both public administration and private companies to implement corporate policies aimed at promoting organizational well-being. In Italy, as the Department of Public Functions observes, organizational well-being is part of the overall well-being of individuals and every organization must consider it (Presidenza del Consiglio dei Ministri Dipartimento della Funzione Pubblica Direttiva 24 marzo 2004 n. 4). To evaluate working conditions it is important to consider very diff erent aspects related to characteristics and conditions of the job, health and safety, work organization, learning and career opportunities, and balance between private and working life. Across European countries, diff erent methods and approaches have been followed to investigate these issues and their many diff erent aspects. The main diff erence between them is their concept of working life quality: a good or bad job is determined by elements that vary in relation to the values of the geographical context. This means that some countries focus their attention on working conditions such as health, safety, or physical characteristics of the workplace; others give attention to working life and its relation to private life (Giovine et al., 2004).

Therefore, it is somewhat diffi cult to give a comprehensive picture of results, and the methods and tools used. First of all, there is no consensus on the defi nition of well-being: in the present study we try to understand how researchers defi ne and analyze this concept. After the literature review we identify the main variables which authors use to measure well-being and the most relevant evidence which demonstrates the variables that infl uence it. In the fi rst part of the article we highlight some aspects of the dependent and independent variables that are often used.

A second diffi culty relates to the measurement of well-being. Generally researchers ask only for the perceptions of workers about the diff erent aspects of their job; they do not ask for aspirations. This method does not consider that aspirations can give more information about the importance of the topic under study. For instance, if workers are asked to evaluate the comfort of their workplace they will only give the perception they currently have. If, however, they are also asked about their preferences for the future, it can be better understood whether comfort is indeed important. Furthermore, if we fi nd a strong diff erence between perceptions and desires, where perceptions are constantly lower than desires, we can hypothesize that workers will be aff ected by stress. Finally, if employers do not give their authorization for information on particular aspects regarding health status to be sought from their workers or if the workers themselves do not want to answer on these issues, we should fi nd a way to measure well-being without using questions related to mental and physical health. This is the reason behind the concept of cybernetic theory, which is based on discrepancy between perceptions and desires (Edwards, 1992).

2 Organizational Well-being Variables and Cybernetic Theory

For a more comprehensive picture of the literature on well-being we refer to the work of Danna and Griffi n (1999). The term "organizational well-being" refers to a wide concept that includes diff erent aspects of non-working life (such as satisfaction in private and social life), working life (job satisfaction regarding pay, career development, the job itself, and colleagues) and general health (this aspect is composed of two characteristics, namely mental and physical well-being). Health and well-being are infl uenced by three typologies of factors (or antecedents as the authors Danna and Griffi n called them), and for each typology we have a series of variables. The fi rst type concerns the work setting, that is, how the workplace is structured and organized in terms of health and safety hazards or other perils that can have negative consequences on workers' health and well-being. The second type concerns personality traits. In this case the authors consider the variables dealing with worker attitudes: Type A behavior or an internal (or external) locus of control, and other typical personality traits. Finally, the third type of factor comprises the stress categories deriving from intrinsic work characteristics, role in organization, social relationships on the job, career development, structure and organizational climate, the relation between home and work, and other stressful factors. Given these as antecedents we can analyze the consequences that the worker's wellbeing and health can have on the workplace. The fi rst typologies of consequences directly concern the individual, because they deal with the implications of his/her physical, psychological, and behavioral health. The second typology mostly refers to the organizational structure, the costs that the employer should meet for health insurance, productivity and absenteeism, legal costs, and compensation for injuries and illnesses. In the following paragraphs we explain the main aspects of some antecedents of well-being such as job demand, job control, social support, rewards (as variables regarding work characteristics), and locus of control (as personality traits). We also explain the factors that comprise organizational well-being such as job satisfaction and physical and mental health. Finally, we show the functioning of cybernetic theory.

2.1 Demand Control Model

In the study of organizational well-being we cannot leave the Karasek model (1979) aside. It is important to understand particular aspects of this model because the present research follows it closely. In previous years it has been shown that organizational and personal tensions increase in situations in which workers with a high workload are heavily supervised. In his fi rst work, Karasek takes into consideration two independent variables on the orthogonal axes: job demand and decision latitude. The fi rst refers to the job eff orts required in terms of hours worked, incongruent requests, or the binding nature of organizations. We can also defi ne job demand as the sum of psychological stressors (where a stressor is the stressful stimulus that changes the individual's balance and conditions him/her to give an answer as a reaction) deriving from requests to work fast and hard, and to carry out numerous tasks without suffi cient time. The second (decision latitude or control) is composed of two parts: skill discretion, i.e., the possibility to acquire new competences, routine tasks, repetitiveness, and learning new things, and decision authority that refers to the possibility of organizing and programming own work with complete autonomy. If we match high job demands and low decision latitude, we have a "high strain" job, with fatigue, depression, exhaustion, anxiety, and then absence owing to illness. If both job demands and decision latitude are high, the job is "active", i.e., a job with low level of stress, learning, growth, and increasing motivation to develop own work. Conversely, when job demands are low and decision latitude is high, the job is "low strain" because of the individual's perception of a low level of demand and high level of control of his/her own work. Finally, if both job demand and decision latitude are low, the job is "passive" and workers may not have any stimulus, they may be dissatisfi ed, and they may not be solution-oriented (Fox, Dwyer and Ganster, 1993).

2.2 Social Support

Karasek's demand-control model was completed by a third dimension, or independent variable, social support. This element was then analyzed and discussed in several following studies. Social support is represented by the feeling of belonging to a real net of aff ective links that ensures reciprocal aid among colleagues and supervisors. According to Karasek and Theorell (1990), the diff erent combinations of the three variables create two distinct hypotheses. If individuals are simultaneously subjected to a high level of demand and a low level of control, and are socially isolated, these individuals will show adverse reactions to stress, such as anxiety, depression, and psychosomatic pathology symptoms (iso-strain hypothesis). On the other hand, if individuals are subjected to high levels of demand but at the same time they have a high level of control in carrying out their tasks and their environment gives them support, they will show satisfaction and a high level of motivation (active learning hypothesis).

A more recent trend of studies (McIntosh, 1991) highlights that social support is composed of two diff erent dimensions well identifi ed and determined: the source of sustenance (that is, someone who gives support) and the type of sustenance (functional or emotional) (Cohen and Wills, 1985). In this respect, McIntosh identifi es three main theoretical reviews, each of them taking into consideration further aspects of the variable. Thoits (1982) suggests that social support can be operative if it is used despite its structure or function; Cohen and Wills (1985) conclude that measures of social support typically evaluate both social relationship structure and function of social support. Even if the terminology used in the diff erent reviews is often similar, defi nition of structure, network, and function is quite diff erent. For instance, support structure sometimes means the existence of relations, integration in a social network, depth of relations, homogeneity or width of relations, or contents or quality of the relations net. The support function is defi ned in terms of how and what it does (Cohen and Wills, 1985).

2.3 Rewards

Workers perform tasks and activities for the organization and then they receive rewards: this is an additional aspect that is worth investigating. The theme of rewards was, of course, treated by motivational theory but the level of analysis was primarily economic and monetary, linked to incentive systems and wages. There are, however, other considerations strictly related to individual satisfaction which derives from less tangible rewards.

Loscocco and Spitze (1990) suggest that the importance of work rewards is related to attitude work models because individuals desire some particular characteristics for their own ends. It may be that workers will be negatively infl uenced by a lack of adequate bonuses. Some authors (Lowe and Northcott, 1988) underline that the lack of intrinsic rewards such as complex, varied, or challenging tasks aff ects emotional well-being.

2.4 Personality Traits

As previously noted, among the antecedents that infl uence well-being at work we fi nd personality traits. Through the term locus of control we try to identify if a subject has a tendency to perceive a situation as favorable, whether determined by luck or by own skills and competences. In the fi rst case we say that the subject has an external locus of control, that is, poor disposition to growth and interaction with favorable situations. In the second case, on the other hand, locus of control is defi ned as internal; it is a characteristic of subjects who trust in themselves and their possibilities. These subjects act in such a way that the useful situation keeps on being realized. If there is a negative condition that is unfavorable and diffi cult to manage, the confi dent subject attributes to him/herself the responsibility for failure. This model identifying two types of subjects based on where control is located was introduced by Rotter (1966). He highlights that if a subject has a lot of trust in his/ her ability to control fate, it could be the case that s/he will pay attention to every aspect of the environment in order to capture useful information to form his/her future behavior. Furthermore, this subject will try to improve the conditions of his/ her environment, s/he will aim to reinforce his/her capabilities, examining his/her abilities and shortcomings, and s/he will resist external factors that could condition him/her. Research shows that not only is perception of control important but also what individuals think about control. Some authors suggest that an internal locus of control is an important component of emotional adjustment and ability to manage stressful states in private life as well (Kobasa, Maddi and Kahn, 1982), whereas locus of control in the workplace (if the subject is able to achieve control) is strongly linked to workers' well-being (Spector and O'Connell, 1994). Looking at these studies, it seems to us that there is a positive relation between internal locus of control and well-being.

There are many scales for measuring this characteristic: Kirscht (1972) developed a scale for perceived control regarding own health state; Reid and Ware (1974) developed a scale composed of three subscales for fatalism, socio-political infl uence, and self-control; Levenson (1973) proposed a scale composed of 24 items subdivided into a further three scales. More recently, Henry (1997) developed a scale with three subscales for internal control, external control, and control by other authoritative subjects, and using Structural Analysis of Social Behavior (SASB). Broadly speaking, there are a good number of studies that suggest that well-being and job satisfaction are infl uenced by control. Ganster and Fusilier (1989) observe that control is an essential element of well-being. Finally, managerial practices that give more control to workers are defi ned as humane and eff ective (Lawler, Mohrman and Ledford, 1995). On the basis of this, we develop our fi rst hypothesis aimed at verifying if locus of control as a variable for personality traits is correlated with well-being (Spector et al., 2002).

H1: There is a correlation among locus of control (the variable for personality traits of interviewees), job satisfaction, and physical and mental well-being (variables which measure workers' well-being).

2.5 Organizational Well-being

Well-being is composed of diff erent aspects. It is infl uenced by numerous variables that also vary across countries (Spector et al., 2002), owing to diff erent cultures, diff erent ways of considering work activity, diff erent ways of living. In many studies we fi nd the use of constructs related to job satisfaction, and physical and mental well-being in order to measure the level of workers' well-being. For this reason researchers often investigate the absence or presence of stressful factors at a physical or mental level. They also use diff erent scales to measure job satisfaction, a very well-known theme. Job satisfaction, defi ned formally as "emotional or aff ective response of a person to various diff erent aspects of his/her work" (Kreitner and Kinicki, 2004: 184), means thinking about how a subject considers his/her own work. Furthermore, considerable diff erences owing to workers' nationality may mean students of organizational behavior spend a lot of energy trying to understand the functioning of job satisfaction.

Many studies use psychosomatic symptoms of workers to analyze health status at a physical level. For instance, Logan and Ganster (2005) in their study on job stress use a scale of seventeen items; they ask about the frequency (from 1=never to 4=very often in last month) of symptoms such as headache, gastrointestinal problems, sleeplessness, palpitations, or dizziness. They found that these symptoms are caused by stressful work situations; the worker somatizes these negativities and s/he displays some diffi culties (through a tangible and evident reaction). In the Cantieri Program the scale used to measure physical health investigates eight diff erent psychosomatic symptoms (it asks about frequency in the last six months: never, seldom, sometimes, often). The Cantieri Program is run by an Italian laboratory which studies well-being in public administration in collaboration with the Department of Public Functions and the Faculty of Psychology of the University La Sapienza (Avallone and Bonaretti, 2003).

If physical well-being is measured through real psychosomatic symptoms and problems, mental well-being is strictly connected with how an individual feels about his/her general health status. This aspect of well-being refers to the emotional sphere of the worker, and the tension or anxiety caused by his/her work (Spector et al., 2002) and all the other stressful factors that put pressure on the individual and make him/her react positively or negatively depending on the situation. In many studies when authors deal with mental well-being they often use terms such as "emotional exhaustion" caused by burnout and therefore measured through stress index or job strain index (De Jonge and Schaufeli, 1998) such as the Maslach Burnout Inventory (MBI-NL); sometimes mental well-being is measured through many dimensions, as in the study of Ouchi and Johnson (1978) that uses six scales corresponding to diff erent dependent variables: positive aff ect, negative aff ect, hostility, anomie, perceived effi cacy, and anxiety. Loscocco and Spitze (1990) use a single item: they ask the interviewee directly how s/he generally feels and how happy s/he is.

2.6 Cybernetic Theory

Crucial to the study of organizational well-being is the cybernetic theory of stress that analyzes the functioning of self-regulating systems. The main construct of this theory is a negative feedback loop which acts to minimize the discrepancies between environmental characteristics and relevant reference criteria (Edwards, 1992). We can fi nd many studies in the literature on cybernetics, for example Kahn et al. (1964), focusing on the role of expectations and coping mechanisms. Beehr and Newman (1978) estimated psychological and physical processes which fi lter personal and environmental characteristics. According to Cummings and Cooper (1979), discrepancies between actual and desired states lead to the implementation of a change situation. French, Caplan and Van Harrison (1982) explained that the worker's perceptions of discrepancies derive from his/her personal characteristics; they cause illness and disturbance and s/he will need to counter them with defense mechanisms. The transactional model of Lazarus and Folkman (1984) states that if an individual evaluates his/her environment as dangerous, s/he will cope. If s/he achieves positive results, s/he will not cope any longer, otherwise s/he will show somatic disturbance. All these models have in common the feedback mechanism and feedback loop concept, but they are diff erent in terms of consideration of stressful factors and their moderator mechanism or the type of illness included in the model.

Edwards says that the distance between perceived and desired states causes stress for workers; each employee attributes a subjective weight to this distance, also called discrepancy or diff erence. According to Edwards, "perceptions are defi ned as the non-evaluative subjective representation of any situation, condition, or event" (1992: 247). This means that perceptions are a personal representation of how an individual sees something. This also indicates that it is not important what variables are included in the model, but what counts in the analysis is the use of factors that are important for the employee. Desires are contrapuntal to perceptions; they refer to any state or condition to which a worker aspires.

Desires can include optimal pay for example (or a range of acceptability) and they belong to the same concept of goals, values, and interest: they are considered as a consciously desired state. As we see in Figure 1, perceptions derive from four types of factor: physical and social environment, personal characteristics, cognitive construction of reality, and social information (A, B, C, D). Desires are infl uenced by social information, individual early life experiences, coping (D, E, F), and the hierarchical arrangement of multiple feedback loops (maintained by the worker). Thus, the stressful situation (deriving from discrepancy between perceptions and desires) may act directly on worker well-being, infl uencing the physical and psychological states of the worker. It can also act indirectly in activating the coping mechanism.

In other words, the worker can reduce the discrepancy in his/her perceptions and desires or reduce the importance of the discrepancy. Discrepancy theory is largely used to compare desired states and perceived states. For example, Boyd et al. (2007) say the diff erence between perceptions and desires leads one to expect that satisfaction is highest when performance matches expectations. Coetzer and Bushe (2006) examine the degree of similarity between perceptions of what currently exists (knowledge) and what is preferred (belief), so they fi nd that evaluative cognitive structures have the potential to evoke eff ect, infl uence motivation, and impact outcomes. Brown et al. (2009) base their study of discrepancy theory on the existing traits, status, or possessions of individuals. After analysis of variables for well-being and cybernetic theory, we can produce a second hypothesis:

H2: Gaps between perceptions and desires in variables which infl uence organizational well-being are better predictors of it than the perceptions of interviewees. Gaps can be directly used as a variable for well-being without the need to ask specifi c questions about mental and physical health.

3 Method

3.1 Research Context and Sample

The empirical analysis is drawn from the administration of a specially structured questionnaire issued to eight diff erent companies located in a small Italian region. The district is Campobasso in the Molise region. All eight companies participated in the study and every employee was recruited: only two employees did not answer the questionnaire. The companies that gave their consent to participation in the survey also requested us to take some privacy measures to ensure their anonymity. This is an important indicator of how organizational well-being, despite gaining credibility in recent years in companies, fi rms, and other business organizations, is still a thorny subject. In addition, sometimes companies do not give permission to share their data and information, so the questionnaire obviously protects the anonymity of the employees themselves. The companies were intentionally chosen in diff erent sectors, and therefore they perform diff erent activities: torrefaction, dairy products, distributive trades, hotel services, health services, building, services for tires. The questionnaire was given to 200 employees. Among them we have not considered the ones with a rate of response lower than 95 percent; other questionnaires suffi ciently completed have been included in the analysis because it was possible to correct missing responses with further investigations. The questionnaires included in the empirical research total 191. We have collected data through two interviewers who asked every single employee to answer questions. The interviewers then sent us the completed questionnaires.

3.2 Data Collection

From the analysis of literature and scales used in previous researches it was possible to develop a specifi cally structured questionnaire aimed at investigating organizational well-being. The uniqueness of this tool derives from the attempt to combine the use of some main variables which infl uence well-being and the double concept of perception and desire introduced by Edwards (1992). The selection of independent variables included in the questionnaire derives from the need to consider economic and organizational measures. More specifi cally, the developed questionnaire is composed of seven sections: the fi rst includes individual characteristics of interviewees; the second section investigates aspects of environmental comfort and safety; the third section is based on Karasek's model about job demand, job control and social support; the fourth section analyzes intrinsic and extrinsic rewards that the workers receive thanks to their work activity; the fi fth section is quite specifi c because it refers only to the quality of leadership; the sixth section has been included in order to identify the interviewees' locus of control; and the last section observes organizational well-being as the dependent variable. Each scale has been translated (if it was not available in the Italian language) and readapted to the specifi c aim of the present research.

3.3 Independent Variable: Measures

3.3.1 Demand Control Support Model

As noted above, Karasek's model is composed of three scales which evaluate social support, job demand, and job control. In this analysis, social support is measured through six items that are used to investigate the relationships with colleagues and supervisors, for example: "There is a quiet and pleasant atmosphere at my place of work." The second scale refers to job demand, as in the following example: "I do not have suffi cient time to do all my tasks"; for this scale there are fi ve items. The third scale measures job control and it is composed of six items regarding creativity, opportunity to learn new things, and chance to decide how to carry out own work. An example is: "I have the possibility to decide for myself how to carry out my work." The propositions are formulated as statements, and respondents must indicate how much they are true in the present and how much they would like them to be true in the future (the response can vary in a range of four modalities, one to four). All the three scales were translated and adapted from the shorter original version of Karasek's model used by Sanne et al. (2005). Another measure used to complete this model is the number of overtime hours per month which we called "work overtime" (Loscocco and Spitze, 1990).

3.3.2 Rewards

In the questionnaire we have also introduced a section which allows us to evaluate the rewards that a worker receives, and as already noted we refer to both intrinsic and extrinsic rewards. Also, in this case the items are statements; the interviewee must indicate how much s/he thinks the statement is true in a range from one to four. There are six items regarding intrinsic rewards, which ask the interviewee if his/her work is interesting, and if s/he exploits his/her abilities and competencies. For instance: "My job is interesting to do." Items related to extrinsic rewards total four and they are about career development, promotion, and prestige: "In my job the chances for advancement and promotion are good." Both scales were translated and adapted from a version used by Marini et al. (1996).

3.3.3 Leadership

A section of the questionnaire focuses exclusively on leadership; the responses vary from one to fi ve, and there are eight items which evaluate the supervisors' abilities to plan or resolve confl ict situations and his/her communication capabilities: "My superior is good at solving confl icts." The scale measures the qualities of leaders with respect to their relationships with their colleagues. This scale is a translation and readjustment of the second edition of the Copenhagen Psychosocial Questionnaire (COPSOQ) (2003).

3.3.4 Environmental Comfort and Safety

As regards the working environment we used two scales: the fi rst considers if the workplace is comfortable and it asks the interviewee to evaluate aspects of the physical work setting; the scale is composed of four modalities, with regard to both the present and the future. The fi rst represents the lowest score, the fourth the highest. There are eight items regarding cleanliness, lighting, temperature, and noise: "How do you evaluate the comfort of your workplace with respect to noise today?" The second scale asks the interviewee about perceptions and desires regarding physical safety of the workplace: for this scale there are also four modalities but seven items with regard to electrical systems, dust, smoking, and video terminals. A sample item is: "How do you evaluate the safety of your workplace compared with the overall electrical system today?" These scales were based on the questionnaire used in the Cantieri Program.

3.3.5 Personality

The section which evaluates the personality of the interviewee has the aim of fi nding the locus of control, and whether it is internal or external. In a sequence of seven items we ask the respondent to indicate how much s/he agrees or disagrees with the proposed statements, in a range from zero to fi ve. With this scale we can associate a high score with an internal locus of control, that is, to the feeling that success or failure derives from one's own capabilities, not from luck or destiny (Craig, Franklin and Andrews, 1984). For this specifi c scale we do not observe desires, but only subject perceptions of proposed statements. An example is: "It is up to me to solve my problems or errors."

3.4 Dependent Variable: Measures

3.4 Dependent Variable: Measures

The last unit of the questionnaire evaluates the organizational well-being as described in the literature, that is, through three variables: physical well-being, mental wellbeing, and job satisfaction. Physical well-being is measured on a scale composed of eight items where we ask the interviewee to indicate the frequency (never, seldom, sometimes, or often) of a series of psychosomatic complaints such as headache, stomach ache, or muscle ache. An example is: "In the last six months how often did you feel anxiety?" This scale is also used in the Cantieri questionnaire.

3.4.2 Mental Well-being

Mental well-being is evaluated through a single item which asks the interviewee to indicate, on a scale from one to fi ve, how happy s/he feels, at both a physical and mental level, regarding his/her job. The decision to use a single item to evaluate this aspect of well-being was reached for two reasons: fi rst of all, we did not want to provoke interviewees with a lot of personal questions; second, Loscocco and Spitze (1990) also used a single item to investigate this aspect. The original version of the item ("How happy would you say that you are these days?") is modifi ed, so the item used in the present work is slightly diff erent, responding to specifi c requirements of the analysis.

3.4.3 Job Satisfaction

The scale which measures job satisfaction is composed of eight items. The interviewee must indicate in a range from one to fi ve (very dissatisfi ed to very satisfi ed) how satisfi ed s/he is regarding certain aspects of his/her job, such as career prospects, colleagues, or work conditions. The items are taken from COPSOQ (2003), and have been translated and adapted to the specifi c needs of the present research. An example is: "How satisfi ed are you with the way your department is run?"

3.4.4 Control Variables

Control variables included in the present research are age and gender of interviewees.

3.4.5 Cronbach's Alpha

We calculated Cronbach's alpha index (Table 1) for scales which measure perceptions and desires. Although the scales used were already validated in previous studies and researches, we considered it appropriate to verify the reliability of each series of items because we had translated and adjusted the scale. The test we conducted to verify the reliability uses Cronbach's alpha as acceptability parameter. Generally practitioners agree to accept alpha values higher than 0.6 as a minimum acceptable level of internal coherence and adequacy of the elaborated test (Likert, 1932). Although we found a relatively low index for these scales, very near to the acceptability level, each scale results coherent and higher than 0.6.

3.4.6 GAP Variables

The gap between perceptions and desires has been calculated as follows:

...

where "n" indicates the number of items for the used scales (D=desires, P=perceptions).

4 Results and Discussion

Table 2 shows descriptive statistics related to variables used for 191 interviewees. We have verifi ed the fi rst research hypothesis based on the consideration that locus of control is a universal component of well-being through statistical correlations between the variables of interest (locus of control, job satisfaction, and mental and physical well-being) as Spector et al. (2002) described (Table 3). In their study, they wanted to verify if locus of control infl uenced workers' health independently of their nationality. This debate has expanded because it is assumed that, depending on nationality, people tend to be individualist or collectivist and so this further factor can buff er the eff ect of locus of control on well-being. The study was conducted on 24 geopolitical units which included a wide sample of managers; Italian managers were not, however, included. This present research does not pretend to the same universalistic scope because of its much more limited boundaries and it cannot verify the diff erent eff ect of locus of control among diff erent countries (the reference sample belongs to a small geographic area). Furthermore, even if the variables used measure common aspects, we have used diff erent scales; so we have to verify our fi rst hypothesis with a correlation matrix.

Spector et al. (2002) show a signifi cant correlation for most variables and almost all the countries included in the research. The correlation that is most consistent with our expectation is the one between locus of control and job satisfaction. In their study every sample shows a signifi cant and negative correlation except for France, but it has a smaller sample in respect to the others. Furthermore, correlation between locus of control and mental well-being shows a slight dispersion; three samples have no signifi cant correlation and four samples have a signifi cantly weaker correlation with respect to the United States. Conversely, regarding physical wellbeing only seven correlations do not result as signifi cant and ten are less signifi cant than those of the United States.

This present study seems to be quite in line in terms of fi ndings with those obtained by Spector et al. (2002) because the highest correlation among locus of control and other variables which measure well-being is the one between locus of control and job satisfaction.

According to the scale used by Spector et al. (2002), the correlation is indirect, which means that higher job satisfaction is linked to an internal locus of control. Conversely, in the case of the present research the correlation is direct, but it has the same meaning because the scale we used to measure the locus of control associates a high score with an internal locus of control. Also, general well-being is signifi cantly correlated with the studied variable, but the result is not the same for physical wellbeing. We can hypothesize that our sample is equivalent to the seven of Spector's study with the same result. Also, other studies show the same result. Kulshrestha and Sen (2006) fi nd signifi cant negative correlation between subjective well-being and locus of control. This means that internals have signifi cantly better subjective well-being than externals. Other researchers suggest that having a coherent sense of one's personality and acting in accordance with that personality is positively related to well-being (Sheldon et al., 1997). Daniels and Guppy (1994) found that an internal locus of control can buff er the eff ects of stressors upon well-being.

We have verifi ed the second hypothesis through hierarchic regression. This type of statistical analysis is most commonly used in studying the relation between wellbeing variables (Janssen, 2001; Tuomi et al., 2004) and it is also our preferred choice. We made two types of regression; one uses perception variables, the other one uses gaps. For each type we found nine models because we replicated three models (to use the diff erent formed blocks) for each dependent variable measuring wellbeing. The fi rst type (the fi rst series) considers variables related to the perceptions of physical and mental well-being and job satisfaction (Table 4). The second model (the second series, Table 5) considers instead the variables constructed through the GAPs (these variables measure the distance between desires and perceptions as a diff erence). Generally these results are positive because desires are almost always higher than perceptions.

The fi rst model includes as control variables the demand-control-support (DCS) model and overtime. The second model also includes scales on environment, rewards, and leadership; the third model includes gender, level of study, and personality. The reasoning behind the formed blocks derives from our necessity to separate the demand-control-support model from the other variables; we have added other variables which consider both perceptions and desires. Finally, we have included the latest variables. The two control variables were specifi cally included, one in the fi rst block and one in the last block. This type of hierarchic regression was performed for both the fi rst and second series. The regression analysis which uses perception variables does not show all the variables that have an infl uence on wellbeing components. Age infl uences physical well-being; this means that younger workers seldom show psychosomatic complaints, but this result is quite normal. We can fi nd this result for all three models which consider physical well-being and perceptions and also GAPs. Another signifi cant relation is that between overtime and job satisfaction; it is signifi cant for the three models and for perceptions and GAPs.

This relation suggests that those who work overtime are more satisfi ed, which may seem contradictory, but we assume that those who work overtime gain more. In the third most complete model which considers physical well-being, social support also seems to be important for health. The relation suggests that workers with lower levels of physical health perceive higher levels of social support. We can explain this result with the fact that the subjects who show many psychosomatic symptoms are also the oldest; they are likely to carry more seniority and enjoy more satisfactory relationships because of their time with the company. Environmental comfort seems to infl uence both mental health and job satisfaction. The relation is positive; it means that if workers feel a high level of comfort they will be more satisfi ed with their job, and the level of overall well-being will be higher as well. Furthermore, leadership and rewards infl uence job satisfaction positively. Finally, personality in the third model is signifi cant for physical well-being: this relation implies that the subjects who tend to an external locus of control often show psychosomatic symptoms. The beta coeffi cient is interesting: for leadership, it is 0.356 in the model with job satisfaction as dependent variable, which means that if leadership increases by one unit then job satisfaction will increase by about 35 percent.

The regression analyses which consider the GAP variables between perceptions and desires show better results than the previous. We can analyze the results in two ways: we can compare the single measures of well-being considering both perceptions and GAPs to evaluate which variables infl uence in turn each component; but we can also consider the number of variables which infl uence the component of well-being in the two series of regressions. In the fi rst case, physical well-being for the models which consider perceptions is infl uenced only by three variables (age, social support, and personality); in the models which consider GAPs, however, we fi nd four other variables that infl uence this component of well-being (overtime, environmental comfort, safety, and gender).

Overall well-being is infl uenced only by environmental comfort if we consider perceptions, whereas if we consider GAPs it is conditioned also by personality and extrinsic rewards. Finally, job satisfaction is infl uenced by four variables in the models with perceptions, and by six variables (which include job demand and personality) in the models with GAPs. We have also included the level of education as an independent variable infl uencing well-being. We can hypothesize that generally an employee who has a high level of education is also more exigent or demanding in respect of own health status. In our study, in both series of regressions the variable which considers the education of interviewees does not emerge as relevant, so we have not dwelt on this aspect. We have no interest in the type of variable but it is important for us if it is diff erent using only perceptions or gaps. We can only underline that generally this variable results as signifi cant (Loscocco and Spitze, 1990) but has not so appeared in our research.

We have also made statistic correlations to exclude problems with multicollinearity. As Tables A1 and A2 (Appendix) show, we can fi nd only a few signifi cant correlations among variables.

This result suggests that variables measure many diff erent aspects of the same object and they do not seem to be redundant. Furthermore, we can note that there are fewer signifi cant correlations among GAP variables than perceptions. In the fi rst matrix, environmental comfort is correlated with environmental safety and job satisfaction and in the second only with safety. Social support is correlated with leadership, locus of control, and job satisfaction, whereas it is correlated with no variables for GAPs. Job control is correlated with leadership, and intrinsic and extrinsic rewards, whereas in the second matrix only with intrinsic rewards. Intrinsic rewards are correlated with extrinsic rewards and leadership; in the GAP matrix they are correlated only with extrinsic rewards. Extrinsic rewards in the matrix of perceptions are correlated both with leadership and job satisfaction, whereas in the second they are correlated only with job satisfaction. Leadership is correlated with one variable in the fi rst matrix and with two variables in the second one. The other correlations regarding locus of control and well-being variables are already seen in the test of the fi rst hypothesis. Also, in the case of correlations, results obtained with GAP variables are better than those of perceptions.

Therefore, we must consider that organizational well-being is made up of job satisfaction and physical and mental well-being at the same time, and the model which includes perceptions shows that only seven variables alternately infl uence well-being. On the other hand, as regards GAPs, the number of variables that infl uence well-being increases from seven to ten. This confi rms that GAP variables are more accurate than perceptions. This may be because they contain another part of information given by the importance that interviewees attribute to every aspect (Edwards, 1992). Finally, we can conclude with the acceptance of the second hypothesis, given that if we use only perceptions and desires we can obtain a more exact measure of well-being without directly investigating its components.

5 Conclusions

The present research is based on an analysis of literature on organizational wellbeing. It is quite specifi c and its consideration of both private and public practices derives from the importance of obtaining high performance and protecting public health. It is a very complex construct because it is measurable through a series of variables and it is conditioned by numerous factors. This research tests two hypotheses. The fi rst concerns the universal eff ect of locus of control as a personality trait on three variables measuring well-being. We verify this hypothesis with the correlation among four variables: locus of control, job satisfaction, and physical and mental well-being, as Spector et al. proceeded (2002). The result of correlation shows eff ects not far from that reached by Spector. The results detect a strong correlation between locus of control with both job satisfaction and overall wellbeing. They demonstrate that those who tend to have an internal locus of control also have a higher level of mental well-being and satisfaction. Physical well-being is not correlated with locus of control, as shown by Spector et al. (2002) for seven of 24 samples analyzed (for another ten samples they found a weak correlation).

The second hypothesis concerns the eff ectiveness of GAP variables in measuring well-being in respect of perception variables only. We tested this hypothesis with regression analysis. The aim of this test is to verify if GAPs are better predictors than perceptions, and analyses show that for the regression model with GAPs the number of variables which in turn infl uence the three components of well-being increases from seven (if we consider only perceptions) to ten. Therefore, if in the fi rst series of regressions the signifi cant variables are age, overtime, social support, environmental comfort, extrinsic rewards, leadership, and personality, in the second series of regressions job demand, environmental safety, and gender are also important for workers' well-being and health status.

Limitations of the study exist with regard to the variability of workers' well-being in relation to the company they belong to. Results may be disrupted by this variable, but it is also true that the same factors can infl uence well-being in one organization but not in others, so it depends on context. This result suggests that future research should explore the organizational context to identify its characteristics because some factors must be included in one context but excluded in others. Furthermore, a subsequent phase of qualitative analysis should identify the specifi c needs and exigencies of the particular organization, so diff erent aspects which were not considered in the past can emerge. Another important fact emerging in this research concerns the diff usion of a well-being culture in a local area: organizations are as yet quite closed regarding this practice; they do not promote it and they do not implement well-being practices.

The present research does not explain how eff ectively well-being acts on individual behavior and organizational performance, because these data are not recorded. Finally, the time variable is not considered: an optimal analysis must be repeated in subsequent cycles in order to compare data, and especially to verify the feedback loop of well-being. Nor does this research consider non-working life satisfaction as Danna and Griffi n (1999) suggest, because it is a more specifi c social aspect of life.

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Appendix

(ProQuest: Appendix omitted.)