Understanding the Effects of Organizational Climate and Creative Work Involvement on Readiness for Organizational Change: A Research on Shipbuilding Industry in Turkey
Department of Business Administration, Gebze Technical University, 41400 Gebze, Turkey
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Author to whom correspondence should be addressed.
Sustainability 2024, 16(15), 6382; https://doi.org/10.3390/su16156382
Submission received: 6 June 2024
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Revised: 3 July 2024
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Accepted: 24 July 2024
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Published: 25 July 2024
Abstract
:The main objective of this article is to conduct an empirical and exploratory study on the effects of organizational climate and creative work involvement on readiness for organizational change to shed light on the readiness of the board members, professional managers, and other employees of the Turkish shipbuilding sector for the trend of organizational change, the frequency of which is increasing rapidly on both a global and national basis, in order to achieve sustainable success within the framework of sustainable development. To investigate the impact of organizational climate and creative work involvement on readiness for organizational change, Turkish shipbuilding companies and leading ship design service providers were surveyed. The results showed that organizational climate and creative work involvement positively and significantly affect readiness for organizational change, where organizational climate and creative work involvement reflected the most significant positive effects, respectively, on the management support and change efficacy subdimensions of readiness for organizational change. The contribution to the literature lies in the unique approach to this relation, which has not been explored in previous studies. This research opens up a new direction for empirical research on readiness for organizational change by combining these concepts.
1. Introduction
The economic and technological developments in the world have a significant impact on the approaches that organizations adopt and continue to develop in order to sustain their existence and ensure their competitive advantage; it has become natural and inevitable for organizations to engage in change initiatives in order to survive in a changing and evolving world. In the context of sustainability, the objective is to align the organization’s vision and goals with sustainable practices and to manage the human side of the transition. Therefore, the necessity for organizational change and adaptation at various levels is a fundamental aspect of sustainability.
On the other hand, the number of unsuccessful change initiatives appears to be alarmingly high. Refs. [1,2] reported that up to 80% of change implementation efforts result in unsatisfactory outcomes. Of these, 28% are cancelled and 43% are postponed [3,4,5], and a global study conducted by McKinsey found that leaders of surveyed organizations believe only one-third of organizational change initiatives are successful [6].
To some extent, it seems impossible to expect a successful transition without making employees ready for the next step. In this sense, At the outset of the change process, it is crucial to gauge the readiness of those who will be affected by the change [7]. Therefore, we would need to look further into the organization and the employees.
The term organizational climate and its treatment in research within organizations originated in the 1960s. The concept of behavior, as defined by Lewinian, provided a fundamental framework for climate research, as it is the product of human beings. Refs. [8,9,10,11,12,13] attempted to clarify the concept of organizational climate by using various dimensions [14]. According to [13], who conducted extensive research on the concept of organizational climate, it describes the quality of the internal environment of an organization that is considered acceptable or tolerable. According to [9]’s definition, climate refers to a set of measurable characteristics of the business environment and the people who live and work in it. These characteristics are perceived directly or indirectly by the individuals and are accepted to affect their aspirations and behaviors.
From the employees’ standpoint, creative work involvement, on the other hand, is defined as the time and effort spent engaging in creative processes related to one’s work [15]. It is considered an important antecedent of creative outcomes [16]. Creative work involvement pertains to individuals’ subjective evaluations of their participation in creative tasks at work. Researchers emphasize that assessing employees’ creative engagement in organizational activities is becoming increasingly important, in addition to discussing the outcomes of their creative performance [15,17,18].
In this sense, we asked the following research questions:
- Is there a link from creative work involvement towards readiness for organizational change and its subdimensions in particular?
- How does organizational climate affect readiness for organizational change and its subdimensions?
In this study, the concepts of organizational climate, which is seen as the psychological environment of the organization, and creative work involvement, which is defined as the time and effort spent by people in organizations to be involved in creative processes related to their work, are examined in detail, and the effects of these concepts on readiness for organizational change are examined. It is assumed that shipbuilding professionals will benefit from the findings to be obtained within the scope of this research. As the population of the research, the Turkish shipbuilding sector, which has found little place in the literature, if not none in this context, and whose importance has increased even more especially during and after the pandemic period, has been taken into consideration.
2. Literature Review and Hypotheses
2.1. Readiness for Organizational Change
The literature has extensively studied the concept of readiness for change in recent years, and academic interest in this concept continues to increase. Although [19] first introduced the concept of readiness, its foundation as a distinct construct has been established through various theoretical models that explain the process of change. Readiness for change is the reflection of organizational members’ intentions, attitudes, and beliefs regarding the need for change and the organization’s capacity to implement these changes successfully [20]. Ref. [21] synthesized theories of change from different practices, providing organizational development specialists, researchers, and managers with a theoretical tool to comprehend the phenomenon better. Moreover, Ref. [22] defined readiness for change as the internal and cognitive orientation of individuals towards organizational change.
Several scholars have studied readiness for change from different perspectives, including [23,24,25]. Holt and his colleagues conducted the most comprehensive study on the factors that impact organizational change readiness [26]. This study structured readiness for organizational change based on four main subdimensions: process factors, which refer to how change occurs; content factors, which refer to what changes include; context factors, which refer to the conditions or settings in which change occurs; and individual factors, which are the personal characteristics of individuals who are undergoing a change. All of these subdimensions provide the opportunity for the separate examination of different predictors in the issue of readiness. Nevertheless, the relationship between the subdimensions of readiness (appropriateness, change efficacy, management support, and personal valence) and these variables has not been extensively discussed, despite the reported construct of total readiness.
Thus, we conducted this study with the rationale that each subdimension of readiness for organizational change should be discussed separately. This is because each subdimension, namely appropriateness, change efficacy, management support, and personal valence, represents a distinct aspect of the construct. The variables related to the factors that affect readiness for organizational change may not be exclusively associated with a single factor but may also be inclusive of other factors. However, most studies have assessed the readiness construct as a total scale without discussing its subdimensions separately. In this respect, we have touched on these subdimensions of readiness for organizational change in the literature review.
Appropriateness refers to whether or not the proposed change is a good fit for the organization [26]. The degree to which organizational members perceive a change initiative as appropriate provides the foundation for creating readiness for organizational change.
Management support refers to the extent to which an individual perceives the organization’s leadership and management as committed to and supportive of the implementation of the proposed change [26]. Employee perceptions are used to assess management support through a readiness for organizational change scale developed by [26]. The instrument measures the degree of management support for a proposed change by assessing employees’ beliefs and perceptions of their senior leaders’ involvement.
Change efficacy refers to the extent to which an individual feels capable of executing tasks and activities associated with implementing a prospective change [26]. In the change literature, change efficacy has been identified as an important factor in conveying change messages [27].
Personal valence refers to an individual’s perception of the degree to which they will benefit or not benefit from the proposed change [26]. Personal valence is considered a significant factor in delivering an effective change message [28], because individuals are less likely to reject change when they perceive personal benefits [29].
Having brought the readiness for organizational change and its subdimensions into focus, it would be noteworthy to review the literature about organizational climate and creative work involvement in order to look into the organization and employees with consideration of readiness for organizational change.
2.2. Organizational Climate
Ref. [30] developed a tool for describing organizational climate and defined it as the organization’s personality. This analogy suggests that climate is to the organization what personality is to the individual. The organization’s personality is reflected in its atmosphere or climate, distinct from the personality of individuals within it.
Ref. [31] noted that organizational climate refers to an individual’s comprehensive perception of their organization and the personal impact of their work environment. This perception affects how individuals behave at work and their attitudes towards their job. Based on their opinion, organizational climate encompasses employees’ perceptions of and emotional responses to their work environment and tasks.
Ref. [32] stated that organizations aim for optimal performance and member satisfaction. Positive and meaningful work environments are more likely to achieve this than negative and oppressive ones.
In consideration of these definitions and previous studies and findings with regards to organizational climate, we have been motivated to study and test the effects of organizational climate on readiness for organizational change. Having asked the initial research questions’ introduction section, we have postulated the following hypotheses:
H1:
Organizational climate positively affects readiness for organizational change.
H1a:
Organizational climate positively affects the appropriateness subdimension of readiness for organizational change.
H1b:
Organizational climate positively affects the management support subdimension of readiness for organizational change.
H1c:
Organizational climate positively affects the change efficacy subdimension of readiness for organizational change.
H1d:
Organizational climate positively affects the personal valence subdimension of readiness for organizational change.
2.3. Creative Work Involvement
Researchers are increasingly interested in identifying both the organizational and individual dimensions of creative work involvement due to the value of creativity in organizations [33,34,35]. Unlike traditional office work environments, creative work often requires a supportive and comfortable atmosphere to thrive. This allows creative individuals to quickly turn their ideas into reality. In essence, creative work involvement differs from daily routine tasks in that it demands more effort, consistency, commitment, concentration, and energy [17].
Creative work involvement is the subjective evaluation of an individual’s involvement in creative tasks at work. In addition to examining the outcomes of the creative performance, researchers have highlighted the growing importance of assessing employees’ creative engagement in organizational activities [15,17,18].
Defined as the time and effort spent by an individual to engage in creative processes related to their work [15], creative work involvement is considered an important antecedent of creative outcomes [16]. Therefore, we have been motivated to postulate the following hypotheses considering creative processes, and the results would be essential in the readiness for change concept.
H2:
Creative work involvement positively affects readiness for organizational change.
H2a:
Creative work involvement positively affects the appropriateness subdimension of readiness for organizational change.
H2b:
Creative work involvement positively affects the management support subdimension of readiness for organizational change.
H2c:
Creative work involvement positively affects the change efficacy subdimension of readiness for organizational change.
H2d:
Creative work involvement positively affects the personal valence subdimension of readiness for organizational change.
The theoretical model and conceptual framework of the research study are delineated in Figure 1.
3. Data and Methodology
Following the comprehensive literature review conducted as part of the research, the scales to be utilized in the study were initially identified, and pre-tests were conducted. The results of the pre-tests led to the elimination of certain scale questions, and the main data were collected with the final questionnaire. Following the examination of the final data, reliability and validity tests were conducted, as well as multiple regression and SEM analyses.
3.1. Sample and Data Collection
In the process of determining the target sample, Turkish Shipbuilders Association, which is the largest cluster of the shipbuilding industry in Turkey and has 85 active shipyards as members, and the leading ship design companies that provide design services to the shipbuilding industry were preferred. In addition, Turkish Chamber of Naval Architects and Marine Engineers, where shipbuilding engineers working in the shipbuilding industry are registered, was also utilized.
With this selection of the study population, it was aimed at including shipbuilding companies in Turkey that actually manufacture for domestic and foreign markets, have physical production facilities, and have qualified white collar personnel and management organizations competent in their fields. This is due to the fact that the shipbuilding industry is typically more conventional and conservative in its management practices, exhibiting a tendency to lag behind the changes occurring in the industry and to have family members occupying positions on the boards of directors.
The questionnaire prepared within the scope of the research was applied to the participants through emails, online surveys, and in-person interviews between November 2023 and March 2024. A total of 328 participants participated in the surveys, and as a result of the outlier controls, 6 observations with systematic outliers were identified with mahalonobis values and removed from the sample, and the research was analyzed from the data of 322 observations.
Ref. [36] stated that at least 300 samples are required for models with less than seven variables and communality values above 0.45. In this study, the common variance values of the six variables of the model varied between 0.456 and 0.794. In consequence, the study included 322 observations, which was deemed sufficient.
The study analyzed the sample using wave analysis to ensure the absence of a non-response bias [37,38]. The data obtained from the first 50 and the last 50 observations were tested with the t-test. No significant difference was found between the groups based on the results, indicating no non-response bias in the sample.
Common method variance is a problem that may arise when a single sample (source) is used to measure two or more variables in empirical research [39]. Since the same source was used in the measurement of all variables within the scope of the study, it was deemed necessary to test whether the sample did not have a common method bias problem. In order to determine this problem, Harman’s single factor test [40] was implemented. If a common method bias is present, according to this method, a single factor is expected to emerge dominantly from the unrotated factor analysis [41]. However, the unrotated factor analysis revealed that the first factor represented 28.97% of the variance. As a result, since this value was below 50% of the total variance explained, it was seen that there was no common method bias problem in the study [42].
3.2. Measurement Instrument and Measures
A two-part questionnaire was used to collect the data for the tests and analyses conducted within the scope of the research from the sample group. The questionnaire’s first section contained inquiries regarding the variables and scales utilized in this study, and the second section included questions to determine information about the participants themselves and the companies at which they are employed. The participants were asked to answer the questions related to the variables according to a 5-point Likert scale ranging from “1—Strongly Disagree” to “5—Strongly Agree”, taking into account the practices for the companies in which they work.
The organizational climate scale developed by Ref. [43] was used to measure the organizational climate, and Ref. [15]’s scale was used for creative work involvement. Ref. [26]’s scale was used to measure the dependent variable: readiness for organizational change. The readiness for organizational change scale developed by Ref. [26] has received the most attention in the literature, and its reliability has been tested. What differentiates this scale from its peers is that it is a comprehensive scale developed based on the work of the authors who introduced the concept of readiness for organizational change [20] and built up theoretical and empirical knowledge on this concept over the years. Despite the numerous studies conducted since the 1960s to assess organizational climate, the scale developed by Ref. [43] has been identified as one of the most recent and reliable studies in the literature with its comprehensive approach, and, in the field of creative work involvement measurement, Ref. [15] has been one of the most cited scales in the literature and has been demonstrated to have the highest validity. As a result of the preliminary tests, we adapted the scales developed by Refs. [15,26,43], corrected some items and their wordings to prevent misunderstandings stemming from translation, and removed some items to better reflect readiness for organizational change concepts. In this sense, six questions were excluded from the organizational climate, creative work involvement, and readiness for organizational change scales after the preliminary test results to prevent disruptions, and five questions were reworded to best summarize the notion.
Factor loadings, means, standard deviations, kurtosis, and skewness values of the data collected within the scope of the research are presented in Appendix A.
Regarding whether the data have a normal distribution, Ref. [44]’s suggestion that kurtosis and skewness values below the absolute value of three indicate a normal distribution was taken into consideration. Since the largest kurtosis value of the data set in this study was 1.088 and the largest skewness value was 2.107, it was decided that the data fit the normal distribution. In addition, outlier control was performed with SPSS 8.80, and six observations with systematic outliers were identified with mahalonobis values and removed from the sample.
4. Results
4.1. Sample Characteristics
Based on the characteristics presented in Appendix B, 75.2% of the participants are male, and 60.5% are between the ages of 26 and 45; 70.5% of the total sample is composed of respondents who work as engineers, specialists, chiefs, or low-/mid-level managers; and 88.2% of those surveyed hold a bachelor’s or master’s degree.
The survey also asked respondents to provide information about the company they work for, in addition to the characteristics listed. There are a number of issues that are worthy of attention, as 84.5% of those surveyed work in a company that employs more than 50 people, and 80.1% are in companies that have been in business for more than 10 years. In addition, 59.6% of respondents indicate that they have been with their organization for less than 5 years. Appendix B provides detailed information on the characteristics of the samples.
4.2. Factor Analysis, Validity, and Reliability
To conduct the factor analysis, the variables must have a certain degree of relationship, and the sample must be sufficient to support the structure. The integrity of the variables in the structure was tested using Bartlett’s Test of Sphericity, and the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was used to determine whether the sample size was sufficient. As can be seen in Table 1, KMO has a value of 0.903, indicating that the sample is large enough, and Bartlett’s Test of Sphericity yielded a result at a significance level of 0.001; therefore, the variables have sufficient correlation integrity to conduct the factor analysis [45]. As a result, the data set is appropriate for factor analysis.
The factor loadings obtained as a result of the factor analysis are presented in Appendix A.
According to reliability test results shown in Table 2, all variables have a construct reliability value over 0.7, and each AVE is over 0.5, indicating the study’s reliability [36,46]. Within the scope of validity, two types of validity were examined. Convergent validity assesses the extent to which scales related to the same concept are related, whereas discriminant validity assesses the extent to which two similar concepts are different from each other. In order to determine the convergent validity of the scales, it is examined whether the AVE and loading values are above 0.5 [36]. As a result of the tests, it was seen that these values for all questions were above 0.5.
Within the scope of discriminant validity, this indicator was examined using the Ref. [47] criterion. According to this criterion, the square root of the AVE values of each variable should be greater than the correlations between the variables. When the data shown in Table 2 are analyzed, it is evident that there is discriminant validity between all the constructs, as the square roots of the AVEs are greater in all cases.
As a result, all validity and reliability tests yielded favorable results for the research, and therefore, the research model is theoretically significant and statistically acceptable.
4.3. Multiple Regression Analysis
Multiple regression analysis is defined as a method used to explain the cause and effect relationships between two or more independent variables affecting a variable with a model and to determine the effect levels of these independent variables.
Based on multiple linear regression analysis, the results of which are presented in Table 3, it was seen that the independent variables creative work involvement and organizational climate explained the dependent variable readiness for organizational change by 36.6% (R2 adjusted = 0.366) and that the explanatory variables creative work involvement and organizational climate were needed to explain the dependent variable readiness for organizational change (p = 0.000 < 0.05), and it was determined that the model had statistical significance.
It is seen that organizational climate and creative work involvement have a positive and significant (p = 0.000 < 0.05) effect on readiness for organizational change.
Organizational climate has a positive significant impact on readiness for organizational change, with β = 0.315, t = 319, and p < 0.001, whereas creative work involvement has a relatively stronger significant and positive impact on readiness for organizational change, with β = 0.434, t = 319, and p < 0.001.
4.4. Structural Equation Modeling Test Results
Structural equation modeling (SEM) is a statistical technique used to examine relationships between one or more dependent or independent variable, whether continuous or discrete [48]. WarPLS 5.0 was used to solve structural equations with the partial least square (PLS) method. In order to fulfill the objectives of the study, the presence of more than one strong link between independent variables was checked before the structural equation modeling analysis was performed. In such a case, the problem of multicollinearity (multi-collinearity) comes into question. This problem may cause the path coefficients of the variables to be higher than they should be. The control of this situation is determined by the Pearson correlation coefficients between the variables being less than 0.9 and the variance inflation factor (VIF) values being less than 3 [49]. The WarPLS outputs show that both the average block and full collinearity VIF values are below the threshold of 3. Moreover, the VIF values for each variable indicate no significant collinearity, with values ranging between 1.296 and 1.969 and all below 3, and the correlation coefficients are below 0.9, indicating that the constructs are free from multi-collinearity. The Tenenhaus Goodness of Fit is 0.413, indicating that the fit of the model is strong [50]. The overall fit results are presented in Table 4.
The path coefficients determined within the framework of the structural equation modeling analysis and the significance values of these path coefficients are shown in Figure 2. The R2 coefficient shows the proportion of the dependent variable’s variance that can be explained by the independent variables [36]. The average R2 contribution was found to be 0.260 (p < 0.001). The individual R2 values obtained as a result of the structural equation modeling analysis are also shown in Figure 2.
According to the results of the path coefficients obtained in consequence of the structural equation modeling analysis, it is evident that creative work involvement has a significant effect on all subdimensions of readiness for organizational change. On the other hand, organizational climate has a strong significant effect on the management support subdimension of readiness for organizational change (p < 0.01), has a moderate significant effect on the appropriateness and change efficacy subdimensions (p < 0.05), and has no effect on the personal valence subdimension (p > 0.10).
Based on the results of the multiple regression and structural equation modeling analyses, as shown in Table 5, all the hypotheses except H1a and H1d are accepted. The H1a hypothesis is rejected, as the relationship it represents has a negative beta coefficient. On the other hand, H1d is rejected due to insignificance (p = 0.14).
5. Discussions
This paper has done exploratory research on several organizational elements and their effects on readiness for organizational change and its subdimensions: appropriateness, management support, efficacy, and personal valence. The results show that readiness for organizational change is significantly affected by these organizational climate and creative work involvement dynamics.
The effect values of organizational climate and creative work involvement on readiness for organizational change are 0.315 and 0.434, respectively, with significance (p < 0.001). Relatively creative work involvement represents a stronger antecedent of readiness for organizational change. As we previously expressed, it seems impossible to expect a successful transition without making employees ready for the next step. Ref. [31] noted that organizational climate refers to an individual’s comprehensive perception of their organization and the personal impact of their work environment. This perception affects how individuals behave at work and their attitudes towards their job. Based on their opinion, organizational climate encompasses employees’ perceptions of and emotional responses to their work environment and tasks. Ref. [32] stated that organizations aim for optimal performance and member satisfaction. Positive and meaningful work environments are more likely to achieve this than negative and oppressive ones. Unlike traditional office work environments, creative work often requires a supportive and comfortable atmosphere to thrive. This allows creative individuals to quickly turn their ideas into reality. In essence, creative work involvement differs from daily routine tasks in that it demands more effort, consistency, commitment, concentration, and energy [17].
In organizational climates that provide appropriate conditions for employees, even if the change process is painful, as long as the level of readiness of the organization and individuals for change is high with creative work involvement, the likelihood of successful change will be high as well. Therefore, the hypothesis results for the independent variables and readiness for organizational change turned out as expected and put forth: H1 and H2 are supported.
According to the results of the path coefficients obtained as a result of the structural equation modeling analysis, creative work involvement has positive significant effects on all subdimensions of readiness for organizational change. In particular, the β coefficients for appropriateness, management support, change efficacy, and personal valence are 0.38, 0.22, 0.54, and 0.31, respectively, with significance (p < 0.001). Therefore, hypotheses H2a, H2b, H2c, and H2d are supported. These results are not surprising, as appropriateness, for instance, is the degree to which organizational members perceive a change initiative as appropriate and is expected to be significant where creative work involvement exists or is motivated. Furthermore, creative work involvement represents a dominant antecedent of the change efficacy subdimension of readiness for organizational change compared to the others. Defined as the time and effort spent by an individual to engage in creative processes related to their work, it is therefore evident that the effect of such creative involvement on efficacy would be inevitable and direct.
On the other hand, organizational climate has a considerably strong positive effect on the management support subdimension of readiness for organizational change, with a β coefficient 0.59 (p < 0.01), has a moderate negative effect on the appropriateness and a positive effect on the change efficacy subdimension (p < 0.05), with β coefficients −0.11 and 0.12; however, it has no effect on the personal valence subdimension (p > 0.1). Therefore, H1b and H1c are supported, whereas H1a and H1d are rejected. Our assessment for one of the most probable reasons for the rejection of H1a and H1d would be the resistance to change notion, which has found a place in the literature of the four different factors: work-related, personal, social, and organizational. We believe that personal and organizational resistance to change might be the relevant factors in creating a level of insignificance in personal valence and negatively affecting the appropriateness subdimensions of readiness for organizational change.
6. Conclusions
The main objective of this article is to conduct an empirical and exploratory study on the effects of organizational climate and creative work involvement on readiness for organizational change in the Turkish shipbuilding sector to shed light on the readiness of the board members, professional managers, engineers, administrative staff, and field workers for the trend of organizational change.
To obtain the best of all possible valued results, we implemented the questionnaire on an exclusive sample among the Turkish Shipbuilders Association, which is the largest cluster of the shipbuilding industry in Turkey with 85 active shipyards, the Turkish Chamber of Naval Architects and Marine Engineers, and the leading ship design companies that provide design services to the shipbuilding industry.
The model presented in this article and the analysis results obtained from the research put forward several academic and managerial implications. First, this study presents a framework connecting organizational climate and creative work involvement notions to readiness for organizational change, including its four subdimensions. The contribution to the literature lies in the unique approach to this connection, which has not been explored in previous research. According to the multiple regression analysis results, organizational climate and creative work involvement have positive and significant impacts on readiness for organizational change. Other insightful findings are based on the structural equation modeling results, whereas creative work involvement has a significant positive effect on all subdimensions of readiness for organizational change. On the other hand, organizational climate has a strong significant effect on the management support subdimension of readiness for organizational change, has a moderate significant effect on the appropriateness and change efficacy subdimensions, and has no effect on the personal valence subdimension. We conclude that organizations need to pay attention to organizational climate and creative work involvement in order to be prepared for the potentially painful changes they intend to make. Therefore, we believe that these concepts are important candidates of future studies in both academic and practical terms. It is our hope that this paper will be of help to both academics and practitioners in the improvement and further development of their work.
Nevertheless, there are, of course, some limitations in the study. First, this research has been conducted on a sample that is large in size but is limited to white collar employees in the shipbuilding sector. The sample selection was exclusive to ensure that the selected individuals were relatively well educated and could accurately comprehend the concepts presented in this study. Moreover, the study can be expanded and implemented to cover other industries with a tendency to lag behind the changing trends that are highly labor-intensive and include custom manufacturing processes, such as construction and agriculture. Additionally, this study may further be extended on a global basis, taking international shipbuilding companies in the leading maritime countries such as the Republic of Korea, Italy, France, Germany, and the Netherlands into consideration, enriched by benchmarking in future studies about organizational change to provide further levels of understanding, as it has been conducted in Turkey, where collectivist culture is dominant. Comprehension pertaining to the subject could be deepened with further studies conducted in different countries with different cultural dimensions [51].
In this article, readiness for organizational change and its subdimensions have been examined through organizational climate and create work involvement notions. Nonetheless, the literature provides a wide range of inter-organization notions that can also be tested, such as openness to organizational change, organizational loyalty, and trust. On the other hand, the Turkish shipbuilding sector has found little place in the literature, if not none, in the organizational change context. Thus, further studies need to be conducted in this highly labor-intensive industry, where people and organizations are very important in terms of effectiveness and especially occupational health and safety concerns.
Having seen the effective results of creative work involvement, further research could be conducted using creative work involvement in other studies related to organizational change or other change-related topics, and finally, there might be more research areas found based on demographics such as genders and their tendencies, terms of employment, education, and so on.
In conclusion, it is worth highlighting that, in order to ensure sustainability of the shipbuilding industry, which currently lags behind other industries in terms of adopting sustainable practices and faces significant risks to the health and safety of employees and the environment, it is imperative that businesses are consistently ready for organizational change in a participatory and innovative climate. It is nevertheless noticeable that businesses which pursue continuous improvement, foster an open organizational climate for innovation, encourage creative work involvement, and are ready for organizational change will not only increase their financial benefits by manufacturing environmentally friendly products and their internal efficiency but will also contribute to environmental and social benefits through sustainable development.
Author Contributions
Conceptualization, O.U.A.; Methodology, O.U.A. and H.K.; Formal Analysis, O.U.A.; Writing—original draft preparation, O.U.A.; Writing—review and editing, O.U.A. and H.K.; Supervision, H.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
This study received approval from the Human Studies Ethics Committee of Gebze Technical University on 17 November 2023, Committee Approval No: 2023/17-03.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data used in this study are available on request from the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
Appendix A
Table A1.
Measures and items.
| Construct and Measurement Item | Factor Loading | ) | Standard Deviation (σ) | Kurtosis | Skewness |
|---|---|---|---|---|---|
| Organizational Climate = 3.5112 σ = 0.72094 | |||||
| Our company supports the personal development of employees. | 0.718 | 3.680 | 0.9473 | −0.605 | 0.010 |
| In award mechanism, employees’ performance is taken as the base criteria and evaluated. | 0.676 | 3.509 | 1.0085 | −0.493 | −0.325 |
| Bureaucratic formalities are at the least level in our company. | 0.677 | 3.311 | 0.9842 | −0.281 | −0.548 |
| There is a great rule system in work management in our company. | 0.693 | 3.460 | 0.9570 | −0.582 | 0.052 |
| Employees of our company are free to participate in all decision-making processes. | 0.708 | 3.230 | 1.0062 | −0.308 | −0.706 |
| Our employees are free in planning and managing their work. | 0.692 | 3.422 | 0.9931 | −0.504 | −0.434 |
| There is a mutual and clement relationship based on confidence among our employees. | 0.791 | 3.839 | 0.9564 | −0.983 | 0.867 |
| It cannot be considered that there is a team spirit among employees in our company. | 0.757 | 3.596 | 1.1184 | −0.552 | −0.613 |
| In general, all work activities are monotonous and have routine characteristics in our company. | 0.653 | 3.435 | 0.9940 | −0.441 | −0.547 |
| Our company in general, is open to innovation, technology and its applications. | 0.735 | 3.693 | 0.9316 | −0.771 | 0.461 |
| Creative Work Involvement = 4.0835 σ = 0.59917 | |||||
| I demonstrate originality in my work. | 0.778 | 4.217 | 0.6235 | −0.500 | 0.869 |
| I find new uses for existing methods or equipment. | 0.775 | 4.053 | 0.7449 | −0.540 | 0.179 |
| I solve problems that cause others difficulty. | 0.743 | 4.211 | 0.6643 | −0.714 | 1.567 |
| I try out new ideas and apply them while approaching to problems. | 0.835 | 4.242 | 0.6815 | −0.762 | 0.987 |
| I identify opportunities for new products and processes. | 0.795 | 4.137 | 0.6556 | −0.483 | 0.616 |
| I generate novel but operable work-related ideas. | 0.837 | 4.205 | 0.6424 | −0.641 | 1.230 |
| I generate ideas revolutionary to our field. | 0.759 | 3.590 | 0.9067 | −0.182 | −0.173 |
| I serve as a good role model for creativity. | 0.838 | 4.012 | 0.8202 | −0.807 | 0.975 |
| Readiness for Organizational Change—Appropriateness = 4.2263 σ = 0.47919 | |||||
| Changes improve our organization’s efficiency. | 0.687 | 4.180 | 0.6450 | −0.398 | 0.239 |
| It doesn’t make much sense for us to initiate changes. | 0.696 | 4.280 | 0.6764 | −0.832 | 1.174 |
| I think it will be worthwhile to adopt changes. | 0.641 | 4.301 | 0.5740 | −0.321 | 0.541 |
| I don’t believe changes help gain any advantages. | 0.651 | 4.208 | 0.7427 | −0.86 | 1.082 |
| The time we are spending on changes should be spent on something else. | 0.637 | 4.217 | 0.7379 | −0.884 | 0.936 |
| I think that our organization will benefit from changes. | 0.795 | 4.239 | 0.6230 | −0.373 | 0.148 |
| There are legitimate reasons for us to make changes. | 0.720 | 4.186 | 0.6286 | −0.391 | 0.434 |
| There are a number of rational reasons in our company for change. | 0.718 | 4.199 | 0.654 | −0.296 | −0.426 |
| Readiness for Organizational Change—Management Support = 3.6099 σ = 0.77814 | |||||
| Our organization’s top decision makers put their full support behind change efforts. | 0.710 | 3.640 | 0.9243 | −0.677 | 0.448 |
| Management clearly supports organizational changes. | 0.751 | 3.621 | 0.8996 | −0.315 | −0.408 |
| Our organization’s most senior leader is committed to change. | 0.677 | 3.733 | 0.8948 | −0.420 | −0.029 |
| Our senior managers stress the importance of change. | 0.773 | 3.547 | 0.9065 | −0.695 | 0.597 |
| Our senior leaders encourage all of us to embrace the changes. | 0.779 | 3.509 | 0.9643 | −0.645 | 0.217 |
| Readiness for Organizational Change—Change Efficacy = 4.2314 σ = 0.52478 | |||||
| I can learn everything that will be required when the changes are adopted. | 0.673 | 4.217 | 0.7294 | −1.088 | 2.107 |
| My past experiences make me confident that I will be able to perform successfully after the changes are made. | 0.675 | 4.031 | 0.6919 | −0.495 | 0.843 |
| I think I will perform better in my assigned tasks after changes are adopted. | 0.707 | 4.096 | 0.6927 | −0.583 | 1.000 |
| I think I will be able to adjust my work after changes are adopted. | 0.760 | 4.314 | 0.6097 | −0.542 | 0.708 |
| I have the skills that are needed to make the changes work. | 0.678 | 4.360 | 0.5912 | −0.399 | −0.142 |
| When we implement changes, I feel I can handle them with ease. | 0.686 | 4.370 | 0.5881 | −0.498 | 0.417 |
| Readiness for Organizational Change—Personal Valence = 4.1263 σ = 0.60509 | |||||
| My future will be limited in this job because of changes. | 0.719 | 3.981 | 0.7275 | −0.558 | 0.740 |
| I am worried I will lose of my status in the organization when the changes are implemented. | 0.827 | 4.165 | 0.7326 | −0.698 | 0.480 |
| I think changes will disrupt many of the personal relationships I have developed in the organization. | 0.766 | 4.233 | 0.7353 | −0.823 | 0.912 |
Appendix B
Table A2.
Sample characteristics.
| Frequency | Percentage | ||
|---|---|---|---|
| Gender | Male | 242 | 75.2 |
| Female | 80 | 24.8 | |
| Age | 18–25 | 22 | 6.8 |
| 26–35 | 106 | 32.9 | |
| 36–45 | 89 | 27.6 | |
| 46–55 | 74 | 23.0 | |
| 56 and over | 31 | 9.6 | |
| Education | Elementary/Secondary | 1 | 0.3 |
| High School | 30 | 9.3 | |
| Bachelor’s/Associate | 202 | 62.7 | |
| Master’s | 82 | 25.5 | |
| PhD | 7 | 2.2 | |
| Department | Research & Development (R&D) | 1 | 0.3 |
| Finance/Accounting | 15 | 4.7 | |
| HR/Administrative Affairs/Operations | 41 | 12.7 | |
| Business Dev./Sales/Marketing/COPCOM | 15 | 4.7 | |
| Quality | 24 | 7.5 | |
| Planning/Project Management | 45 | 14.0 | |
| After Sales Services | 9 | 2.8 | |
| Design | 44 | 13.7 | |
| Supply Chain/Logistics/Purchasing | 20 | 6.2 | |
| Production | 36 | 11.2 | |
| Board/Top Management | 29 | 9.0 | |
| Other | 43 | 13.4 | |
| Position | Director/Deputy Director/Manager | 82 | 25.5 |
| General Manager/Deputy GM | 17 | 5.3 | |
| Engineer/Specialist/Chief/Coordinator | 145 | 45.0 | |
| Foreman/Master/Apprentice | 3 | 0.9 | |
| Owner/Shareholder/Partner/Board Member | 9 | 2.8 | |
| Technician | 20 | 6.2 | |
| Other | 46 | 14.3 | |
| Term of Employment | Less than 1 year | 55 | 17.1 |
| 1–5 years | 137 | 42.5 | |
| 5–10 years | 68 | 21.1 | |
| 10–20 years | 45 | 14.0 | |
| 20+ years | 17 | 5.3 | |
| Operating Period of Company | Less than 1 year | 3 | 0.9 |
| 1–5 years | 15 | 4.7 | |
| 5–10 years | 46 | 14.3 | |
| 10–20 years | 153 | 47.5 | |
| 20+ years | 105 | 32.6 | |
| Number of Employees | Less than 50 | 50 | 15.5 |
| 50–250 | 103 | 32.0 | |
| 251–500 | 117 | 36.3 | |
| 500+ | 52 | 16.1 |
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Figure 1.
Theoretical model.
Figure 2.
SEM analysis results. RC: readiness for organizational change; OC: organizational climate; CI: creative work involvement; RC1_AP: appropriateness subdimension of RC; RC2_MS: management support subdimension of RC; RC3_CE: change efficacy subdimension of RC; RC4_PV: personal valence subdimension of RC; i: Number of items (survey questions) in that variable’s scale.
Figure 2.
SEM analysis results. RC: readiness for organizational change; OC: organizational climate; CI: creative work involvement; RC1_AP: appropriateness subdimension of RC; RC2_MS: management support subdimension of RC; RC3_CE: change efficacy subdimension of RC; RC4_PV: personal valence subdimension of RC; i: Number of items (survey questions) in that variable’s scale.
Table 1.
KMO and Bartlett’s Test results.
| Kaiser–Meyer–Olkin Measure of Sampling Adequacy | 0.903 | |
| Bartlett’s Test of Sphericity | Approx. Chi-Square | 8788.411 |
| df | 780 | |
| Sig. | 0.000 | |
Table 2.
Validity and reliability analyses and Pearson correlation values.
| Variable | Cronbach Alpha | AVE | Correlation between Variables and Square Roots of AVEs | |||||
|---|---|---|---|---|---|---|---|---|
| CI | OC | RC4_PV | RC3_CE | RC2_MS | RC1_AP | |||
| CI | 0.933 | 0.633 | 0.796 | |||||
| OC | 0.892 | 0.508 | 0.300 ** | 0.713 | ||||
| RC4_PV | 0.769 | 0.596 | 0.254 ** | 0.053 | 0.772 | |||
| RC3_CE | 0.891 | 0.5 | 0.536 ** | 0.249 ** | 0.431 ** | 0.707 | ||
| RC2_MS | 0.902 | 0.558 | 0.345 ** | 0.651 ** | 0.069 | 0.266 ** | 0.747 | |
| RC1_AP | 0.871 | 0.506 | 0.338 ** | 0.124 * | 0.402 ** | 0.552 ** | 0.181 ** | 0.711 |
Notes: Numbers shown in bold are the square root of the average variance extracted from each item. RC: readiness for organizational change; OC: organizational climate; CI: creative work involvement; RC1_AP: appropriateness subdimension of RC; RC2_MS: management support subdimension of RC; RC3_CE: change efficacy subdimension of RC; RC4_PV: personal valence subdimension of RC. ** p < 0.01, * p < 0.05.
Table 3.
Multiple regression analysis results.
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | Collinearity Statistics | |||
|---|---|---|---|---|---|---|---|---|
| B | Std. Error | Beta | Tolerance | VIF | ||||
| 1 | (Constant) | 2.211 | 0.136 | 16.213 | 0.000 | |||
| OC | 0.179 | 0.026 | 0.315 | 6.759 | 0.000 | 0.910 | 1.099 | |
| CI | 0.296 | 0.032 | 0.434 | 9.312 | 0.000 | 0.910 | 1.099 | |
F(2.319) = 93.54, p < 0.001, R2 adjusted = 0.366; predictors: (constant), OC, and CI; OC: organizational climate; CI: creative work involvement.
Table 4.
Overall fit results.
| Fit Definitions | Results | Acceptable Range | Reference |
|---|---|---|---|
| Average Path Coefficient (APC) | 0.292 ** | ||
| Average Adjusted R-Squared (AARS) | 0.260 ** | ||
| Average Block VIF (AVIF) | 1.134 | acceptable if ≤5, ideally ≤3.3 | [36] |
| Average Full Collinearity VIF (AFVIF) | 1.664 | acceptable if ≤5, ideally ≤3.3 | [36] |
| Tenenhaus GoF (GoF) | 0.413 | small ≥ 0.1, medium ≥ 0.25, large ≥ 0.36 | [50] |
Note: “**” indicates 01% significance.
Table 5.
Hypothesis assessments.
| Direction of Effect | Beta Coefficient | Hypothesis |
|---|---|---|
| Organizational Climate → RC (H1) | 0.315 *** | Supported |
| Creative Work Involvement → RC (H2) | 0.434 *** | Supported |
| Organizational Climate → RC—Appropriateness (H1a) | −0.11 ** | Rejected |
| Organizational Climate → RC—Management Support (H1b) | 0.59 *** | Supported |
| Organizational Climate → RC—Change Efficacy (H1c) | 0.12 ** | Supported |
| Organizational Climate → RC—Personal Valence (H1d) | −0.06 * | Rejected |
| Creative Work Involvement → RC—Appropriateness (H2a) | 0.38 *** | Supported |
| Creative Work Involvement → RC—Management Support (H2b) | 0.22 *** | Supported |
| Creative Work Involvement → RC—Change Efficacy (H2c) | 0.54 *** | Supported |
| Creative Work Involvement → RC—Personal Valence (H2d) | 0.31 *** | Supported |
Path coefficients with “***” indicate 0.01% significance, “**” 0.05% significance, and “*” over 10% significance. RC: readiness for organizational change.
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Alanc, O.U.; Kitapci, H. Understanding the Effects of Organizational Climate and Creative Work Involvement on Readiness for Organizational Change: A Research on Shipbuilding Industry in Turkey. Sustainability 2024, 16, 6382. https://doi.org/10.3390/su16156382
AMA Style
Alanc OU, Kitapci H. Understanding the Effects of Organizational Climate and Creative Work Involvement on Readiness for Organizational Change: A Research on Shipbuilding Industry in Turkey. Sustainability. 2024; 16(15):6382. https://doi.org/10.3390/su16156382
Chicago/Turabian StyleAlanc, Ozgun Utku, and Hakan Kitapci. 2024. "Understanding the Effects of Organizational Climate and Creative Work Involvement on Readiness for Organizational Change: A Research on Shipbuilding Industry in Turkey" Sustainability 16, no. 15: 6382. https://doi.org/10.3390/su16156382
APA StyleAlanc, O. U., & Kitapci, H. (2024). Understanding the Effects of Organizational Climate and Creative Work Involvement on Readiness for Organizational Change: A Research on Shipbuilding Industry in Turkey. Sustainability, 16(15), 6382. https://doi.org/10.3390/su16156382
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