The Link Between Overwork and Not Enjoying The Job Execution. An application to the case of small industrial entrepreneurs

The Link Between Overwork and Not Enjoying The Job Execution. An application to the case of small industrial entrepreneurs

Pellejero Silva, Mónica Sánchez-Medina, Agustín J. Blázquez Santana, Félix.

Department of Economics and Management, University of Las Palmas de Gran Canaria, The Canary Islands, Spain

Abstract

The role played by entrepreneurs in small businesses is crucial to its success. In this sense, if the businessman develops an addiction to work, this will undoubtedly affect the future of the company. Therefore, the purpose of this study is to analyze the relationship between the two components of workaholism: overwork and not enjoying the job. With this aim, 153 surveys were conducted to entrepreneurs of small industries on the island of Gran Canaria.

1. Introduction

   The fact that the entrepreneur has a decisive influence on the development of newly created firms appears to be in little discussion. That is why some authors even consider these companies as extensions of their founders [1,2,3,4]. So if these people go on to develop workaholism, the viability of the company can be conditioned as a result of the deteriorating health of its founder.

   The purpose of this paper is to try to determine the relationship between two of the components of workaholism, overwork as an enterprising and not enjoying the job. The importance of this research is that it provides a better understanding of one of the possible reasons for failure in entrepreneurship, workaholism. In this work we have studied 153 entrepreneurs of small industries. These companies had an age between 3 and 42 months at the time of data collection. The above companies were all located on the island of Gran Canaria.

   In addition to this introduction, the structure of this paper has the following sections: a. theoretical framework and research hypothesis b. methodology, c. results and d. conclusions.

2. Theoretical framework and study hypotheses

   For Moreno-Jiménez et al. [5]. although addictions are often ill-considered, this is not the case when they refer to work, because in this case it even gets

   to have social and economic reinforcements, despite having consequences on

   health and production quality for those who suffer it. Thus, while authors as Korn et al. [6]., Naughton

   [7] and Sprankle and Ebel refer to workaholism as positive behavior which may even favor the organization, according to Del Libano et al. [8], most do negatively with the same consideration that they can give to any other addiction [9,10,11,12].

   Oates [13], who is recognized as the author who coined the term workaholism, defines it as the compulsion or the uncontrollable need to work incessantly. This is, according to the author, a type of behavior that was observed in the worker's conduct and has some similarities with drinking behavior, for its compulsive and control exempt nature and which also may constitute a risk to personal health, happiness, relationships, and social development of the individual. In this line, Schaufeli et al. [14] believes that it is "the tendency to work excessively hard compulsively". Killinger

   [15] defined workaholism as the gradual loss of emotional stability that leads to an addiction to the control and power in a compulsive attempt to achieve approval and success. In this line, Robinson [16] states that it is a continuous workload, voluntary and compulsory, so that the employee is unable to regulate his work habits and ends excluding other fields of interest and activity. Spence and Robbins [17] consider it a high involvement in work due to internal pressure and with a low capacity to enjoy it. Similarly Snir and Harpaz [18] considered it as the assignment by the individual to his work of many hours of his time and thoughts without it being due to external demands. Salanova et al. [19] consider workaholism as "a psychosocial damage characterized by overwork mainly due to a compelling need or urge to work constantly." Finally, it can be mentioned that according to Pietrowski and Vodanovich [20] workaholism syndrome affects the individual's satisfaction, both in the family and labor sphere. Thus sufferers may have negative effects on the performance of their work [21,22,23]. As a consequence of this it has been established the following hypothesis:

   H1: The Entrepreneur's overwork positively influences not enjoying his work as he performs it.

3. Methodology and proposed model

   Sample and procedure

   In the present study, the survey was the method used to obtain the necessary information to fulfil the proposed objectives, and its basic observation instrument was the questionnaire [24]. The target public consisted the target public consisted of small industrial entrepreneurs living on the island of Gran Canaria. A total of 153 valid surveys were obtained.

   Measures

   The questionnaire was divided into two parts. The first part included questions about the basic profile of the person surveyed, such as sex, age, educational level, etc. The second block contained a total of 10 questions designed to measure the two constructs included in the proposed model (Overwork, NoEnjoy).

   Moreover, we used a seven-point Likert type scale for all the items. Response categories ranged from 1 (strongly disagree) to 7 (strongly agree).

   Data analysis

   After the field work had been done, the data obtained were codified and tabulated. The program used for this purpose was version 19 of the SPSS (Statistical Package for Social Sciences) for Windows. To study the data, structural equations analysis was performed using the Partial Least Squares (PLS) technique. This methodology, which uses the Ordinary Least Squares (OSL) algorithm, was designed to reflect the theoretical and empirical aspects of social qualities and behavioural sciences, where there are generally situations with sufficient empirical support and little information available [25]. PLS was chosen because the present study focuses on predicting dependent variables [26], and this technique is effective with small samples [27,28]. This study specifically used the SmartPls version of software 02.00 [29].

4. Results

   Analysis of the measurement model

   To evaluate the measurement model, first the individual reliability of each item is observed. This

   procedure is performed by examining the loadings or simple correlations of the measures or indicators with their respective constructs. According to Carmines and Zeller [30], to accept an indicator as part of a construct, it must have a load 0,707, which implies that the shared variance between the construct and its indicators is greater than the variance of the error. However, other authors [31,32] consider this criterion too restrictive, arguing that indicators should not be eliminated that, although not reaching the value of 0.707, exceed the value of 0.65. As Table 1 and Figure 1 show, all of the indicators fulfil the condition of exceeding the value of 0.707, except one corresponding to the NoEnjoy construct having a value of 0.642. As a value quite close to 0.65 we decided to keep it in the model.

   Table 1. Outer model loadings and cross loadings

   Source: Own elaboration

   	Overwork	NoEnjoy
   OvWo1	0.829	0.508
   OvWo2	0.829	0.507
   OvWo3	0.805	0.440
   OvWo4	0.810	0.423
   OvWo5	0.797	0.533
   NoEj1	0.371	0.756
   NoEj2	0.556	0.836
   NoEj3	0.574	0.788
   NoEj4	0.282	0.642
   NoEj5	0.329	0.718

   A second condition to take into account is the internal consistency, which involves evaluating how rigorously the manifest variables are measuring the same latent variable. For this purpose, the composite reliability must be > 0.7. As Table 2 shows, in all cases the value of 0.865 is surpassed. This table also shows that the Cronbachs Alpha is above 0.811 in all cases, which indicates that the constructs are reliable. As the third step in evaluating the validity of the scales used, we studied the Average Variance Extracted (AVE). Fornell and Larcker [33] recommend a value superior to 0.5, in order to establish that more than 50% of the constructs variance is due to its indicators. As Table 2 shows, this requirement is also met.

   Finally, the discriminant validity is analysed, which tells us to what degree a construct of the model is different from the models other constructs. One way of testing this circumstance is to demonstrate that the correlations between the constructs are lower than the square root of the AVE. Table 2 also shows the matrix of correlations between the constructs, having substituted on the diagonal the value of the correlation with that of the square root of the AVE. As the values on the diagonal are the greatest values in each row and column, the existence of discriminant validity is confirmed.

   Table 2. Construct reliability, convergent validity and discriminant validity

   Source: Own elaboration

   AVE	Composite Reliability	Cronbachs Alpha		Cynicism	EmotExhaus
   0.663	0.908	0.873	Overwork	0.814
   0.564	0.865	0.811	NoEnjoy	0.597	0.751
   			The elements located on the diagonal, in bold are the square root of average variance extracted (AVE). The elements located outside the diagonal are the correlations between constructs. For there to exist discriminant validity, the diagonal elements should have a higher value than those that are outside of this.

   As all the tests performed previously were positive, it can be stated that the measurement model used is valid and reliable. Therefore, next we will evaluate the proposed model, which is the object of the study.

   Evaluation of the model

   After studying the validity of the measurement model, next the causal relations proposed in the model will be evaluated. In this way, an attempt will be made to observe what amount of variance of the endogenous variables is explained by the constructs that predict them. One measure of the predictive power of a model is the value of R2 for

   the latent dependent variables. Figure 1 shows that the value of the R2 of OverWork is 0.356, which means that the model explains approximately 35% of the variance of this construct (see Table 4).

   Figure 1. Structural model results

   Source: Own elaboration

   To evaluate the validity of the different relations proposed in the model, the Bootstrap Technique was used, which offers the standard deviation and the T. Thus, the stability of the estimations is examined using a t-Student distribution with a tail obtained by means of the Bootstrap Test with 500 subsamples [34]. Table 3 shows that Hypothesis 1 is accepted with a significance level of 0.01.

   Table 3. Structural model results

   Source: Own elaboration

   Hypothesis	Suggested effect	Path coefficients	t-value (bootstrap)	Support
   H1: OverWork -> NoEnjoy	+	0.597***	8.032	Yes
   *p < 0.05; **p < 0.01; ***p < 0.001; ns: not significant (based on t(499). one-tailed test) t(0.05; 499) = 1.64791345; t(0.01; 499) = 2.333843952; t(0.001; 499) = 3.106644601

   In addition, to test the models validity, the Stone- Geisser – Crossvalidated Redundancy (Q2) Test was performed. This test is used as a criterion to measure the predictive relevance of the dependent constructs. If Q2>0, the model has predictive relevance; otherwise, it does not. As Table 4 shows, in all cases the values of Q2 are positive, which certifies the predictive relevance of the model.

   Table 4. Effects on endogenous variables

   	R2	Q2	Direct effect	Correlation	Variance explained
   NoEnjoy	0,356	0,484
   H1: Overwork			0,597	0,597	0,356

   	R2	Q2	Direct effect	Correlation	Variance explained
   NoEnjoy	0,356	0,484
   H1: Overwork			0,597	0,597	0,356

   Source: Own elaboration

5. Conclusions

Discussion

The main conclusion of this study has to do with the implications of the support found for the proposed hypothesis. Así, cuando existe un exceso de trabajo, los emprendedores no disfrutan con su labor, lo cual puede conllevar repercusiones negativas para la empresa. De este modo, se puede observar que en el colectivo estudiado, se cumplen las afirmaciones teóricas realizadas a lo largo de este estudio.

Limitations and future research

Regarding the weak points of this study, it should be mentioned that a transversal methodology was used, thus increasing the probability of bias due to the use of only one method/source of data.

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