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Article

Exploring the Impact of Sustainability Control Systems on Employees’ Green Creativity: The Mediating Role of Psychological Empowerment and Sustainability Learning Capabilities

by
Dasuni Nirmani Pandithasekara
1,*,
Erabaddage Ayoma Gayathri Sumanasiri
1 and
Áron Perényi
2
1
Department of Commerce, Faculty of Management Studies and Commerce, University of Sri Jayewardenepuara, Nugegoda 10250, Sri Lanka
2
Department of Business Technology and Entrepreneurship, School of Business, Law and Entrepreneurship, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 4806; https://doi.org/10.3390/su15064806
Submission received: 31 December 2022 / Revised: 16 February 2023 / Accepted: 23 February 2023 / Published: 8 March 2023
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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Abstract

:
This paper investigates how sustainability control systems (SCSs) drive employees’ green creativity (EGC) with the purpose of assisting organisations in the Sri Lankan manufacturing sector to improve their environmental sustainability performance. Managers and staff of manufacturing firms often lack awareness of environmental issues, which leads to unsustainable strategies. EGC has been identified as an important resource for devising sustainable strategies. SCSs drive employee behaviour and support EGC by fostering a creative workplace. Utilising Simons’ Levers of Controls (LoC) framework, a mediation model incorporating psychological empowerment (PE) and sustainability learning capabilities (SLCs) is tested to provide insights on how SCSs influence EGS. Survey data collected from 239 organisations in the Sri Lankan manufacturing sector were analysed using the PLS-SEM method. The results confirm the full mediating roles of PE and SLCs on the link between SCSs and EGC. This demonstrates the importance of empowering employees and enhancing their learning capabilities to encourage EGC. This study contributes to Simons’ LoC framework by incorporating sustainability dimensions into management control systems (MCSs), and extends the extant body of knowledge by providing a specific understanding of the mechanisms driving EGC through PE and SLCs.

1. Introduction

Awareness of corporate failures has grown globally due to enhanced environmental concerns (e.g., Coca-Cola, Pepsi, and Nestle [1,2]). Similar concerns have emerged in Sri Lanka, a developing country in South Asia facing numerous sustainability challenges [3,4,5,6,7]. This is evidenced by the failure of certain well-known Sri Lankan manufacturing corporations to implement green practices in recent years, including Dipped Products PLC, a subsidiary of Hayley’s Group [8], and Coca-Cola in the local context [9]. To tackle sustainability challenges, managers implement different green strategies, such as corporate governance policies [10,11,12,13] and capital structure [14,15,16,17], as potential solutions for the prevention of corporate failures. Although these solutions might assist in mitigating corporate failures in the short term, employees’ green creativity (EGC) has received substantial interest in the recent literature [18,19,20,21] as a potential solution. The compilation of literature presented in Table 1 demonstrates that fostering EGC is one of the major strategies explored by researchers that will help in achieving long-term sustainability and survival of businesses.
EGC has been identified as one of the most influential drivers of organisational sustainability [25,26,27,28], and developing effective and innovative solutions for preventing business failure has been regarded as a key outcome of creativity [28,29].
Businesses all over the world encourage their staff to engage in EGC, mainly due to an increased focus on environmental concerns driven by rapid technological breakthroughs [19,20,21,27]. Furthermore, in the contemporary political environment, consumers’ environmental sensitivities are intensifying. Consequently, consumers prefer green products, even if they must pay higher prices for them [30]. These strong claims from diverse stakeholders have encouraged businesses to adapt to policy requirements and consumer expectations. By encouraging EGC, businesses can successfully address these environmental concerns, leading to the emergence of this new concept [26]. According to Chen and Chang [31], EGC is critical for green product design, and organisations need to incorporate green concepts into their design processes to facilitate business sustainability. Moreover, Al-Ghazali and Afsar [32] and Shah et al. [18] emphasise that organisations must actively stimulate EGC to reduce pollution and achieve sustainable development. As a result, researchers have started examining potential factors that nurture EGC in different corporate settings. Consequently, green transformational leadership [33,34,35,36], green dynamic capabilities [37,38,39], and management control systems (MCSs) [4,40,41] have been identified in the literature as popular driving forces that promote EGC (see Table 2).
MCSs are one of the factors managers need to consider when establishing an appropriate work environment that will stimulate employees’ creativity [42,43]. Simons’ Levers of Control (LoC) framework [24,44] provides a theoretical basis to examine the association between sustainability control systems (SCSs) and EGC. Furthermore, it provides a framework to validate the significant mediating roles of psychological empowerment (PE) and learning capabilities of employees in the context of promoting employees’ creativity by implementing MCSs [43]. While examining the use of MCSs, scholars identified the possibility of adjusting Simons’ LoC framework to incorporate green concepts [45,46] and thus developed a new model of SCSs [47,48]. SCSs are a specialised application of MCSs that integrate environmental, social, and economic sustainability elements to drive sustainability outcomes [49]. Considering the growing concern with corporate sustainability, especially in developing countries such as Sri Lanka [3,7], the current study engages in an examination of how the implementation of SCSs can enhance EGC through the mediating roles of PE and sustainability learning capabilities (SLC) in businesses in the Sri Lankan manufacturing sector.
Table 2 suggests the lack of empirical evidence on SCSs as a driver of EGC. However, empirical evidence on MCSs driving EGC is available [4,40,41]. Although this gap in the body of knowledge is present globally, our study focuses on the Sri Lankan manufacturing sector for several reasons. First, the literature review confirms a sustainability performance gap in the Sri Lankan manufacturing sector. Although SCSs and green creativity practices can be applied in other industries in Sri Lanka as well, we focus on the manufacturing sector because of its growing importance in the Sri Lankan economy [50]. Second, the Sri Lankan manufacturing sector has a substantial environmental impact [51,52], and this industry is vulnerable to a wide range of environmental challenges [53]. Compared to other sectors, such as agriculture or services, the manufacturing sector has a higher degree of visibility regarding environmental issues in general [50]. Finally, since the manufacturing sector is heavily dependent on non-renewable resources, it is under substantial external pressure to improve its environmental performance [54]. These arguments highlight the need for and the benefits of becoming greener and applying innovative and creative solutions to address environmental sustainability issues in the developing economic context of Sri Lanka. Therefore, our first research objective is to explore the impact of SCSs on EGC in the Sri Lankan manufacturing sector.
Table
Table 2. Drivers of employees’ green creativity (EGC).
Table 2. Drivers of employees’ green creativity (EGC).
Factors
Green Transformational LeadershipGreen Dynamic CapabilitiesManagement Control Systems (MCSs)Sustainability Control Systems (SCSs)
Theories
used		Leadership theoriesChen and
Chang [31]
Human resource functions Rugman and Verbeke [42]
Management accounting practices Simons [24]Simons [24]
Empirical
validation/context		Developed economiesLi et al. [34]Singh et al. [38]Knardal and Pettersen [40]GAP
Developing economiesMansoor et al. [35]Yousaf [39]Ong et al. [4]GAP
Asian economiesMittal and Dhar [33]Joshi and Dhar [37] Wijethilake et al. [41]GAP
Sri LankaSenarath and Bartholomeusz [36]Wijethilake and Upadhaya [46]Wijethilake et al. [41]GAP
Source: Authors’ compilation.
This study uses Simon’s LoC framework by incorporating the sustainability dimensions recommended by Ogbeibu et al. [27] and Widener [55] to examine the impact of SCSs. In the context of promoting EGC by implementing SCSs, extant literature supports the significant role of the PE of employees and enhancing employees’ SLCs [43,56,57,58,59,60].
Organisational studies scholars found that PE inspires employees to improve their creativity [56,57,58] and recognised PE as an essential motivating factor for individuals [43,59]. Previous research provided evidence on the mediating role of PE in explaining the relationship between MCS and employee creativity [43,61]. However, whether and how SCSs influence EGC through the mediating role of PE after incorporating sustainability dimensions into MCSs remains open to empirical examination. This constitutes our second research objective, to investigate the mediating role of PE in the relationship between SCSs and EGC in the Sri Lankan manufacturing sector.
Furthermore, organisational learning has been identified as part of a supportive workplace, highlighting the potential importance of SLCs in fostering EGC [43,60,61]. Appuhami [43] and Grafton et al. [62] provided evidence for organisational learning capabilities as a mediating factor between MCSs and employee creativity. We extend their research to explore how SCSs drive EGC through the mediating role of SLCs. Therefore, our third research objective is to examine the mediating role of SLCs in the relationship between SCSs and EGC in the Sri Lankan manufacturing sector.
A cross-sectional empirical study was designed and conducted to examine these research objectives. A survey was carried out to collect primary data from 505 respondents in 239 manufacturing organisations. The data were first analysed using SPSS to provide descriptive statistics and SmartPLS 3.0 to test a PLS-based structural equation model for assessing the hypotheses.
This paper is divided into four sections. Section 2 provides the theoretical framework and hypothesis development (materials) and introduces the methodology applied (methods). Section 3 presents the analysis of the data (results). Finally, Section 4 comprises the discussion and conclusions.

2. Materials

2.1. MCSs Theories

A variety of theoretical frameworks for conceptualising MCSs have been proposed by researchers, as shown in Table 3. These theoretical approaches are important to understand, as they provide guidance on the selection of the most appropriate framework to be integrated into our analysis, with the purpose of connecting MCSs and employee creativity.
Simons’ [24] LoC framework captures four key domains of control. (1) Belief systems represent the organisation goals and values. (2) Boundary systems are the formal rules and policies governing the behaviour of its members. (3) Diagnostic control systems are predominantly performance measurement and incentive systems that provide tangible data on outcomes. (4) Interactive control systems cover areas of innovation and interaction between employees. The dimensions of this framework are present at the organisational level of aggregation, but cover distinctly different concepts in terms of the mechanism, type, and scope of control.
Whiteley [63] provides a similar categorisation of the characteristics of MCSs: (1) the extent of dependence on formal rules and procedures, (2) control over the performance of economic activities, (3) subordinates’ involvement, and (4) influence over the control systems and scope. This framework, however, has not been linked to sustainability and employee creativity.
Gerdin [64] provides a practical classification, dividing MCSs into three major groups: rudimentary, broad-scope, and traditional (narrow) controls, based on their reporting frequency and level of detail provided. While this classification provides a practical opportunity to assess the application of MCSs, the dimensions are mutually exclusive and therefore not appropriate for constructing a higher-order multidimensional scale for the purpose of assessing the construct for the purpose of modelling.
In response to a variety of conceptualisations and models, Malmi and Brown [65] developed a new, broader definition for MCSs, as follows: “Those systems, rules, practices, values and other activities management put in place to direct employee behaviour should be called management controls” (p. 290). Based on this definition, they proposed a new conceptualisation of MCSs, which comprised five control systems: (1) planning, (2) cybernetic, (3) reward and compensation, (3) administrative, and (5) cultural control systems. This direction of development for MCSs theory, however, failed to address the sustainability challenge.
Therefore, as we describe in more detail below, we selected Simons’ LoC framework for further analysis, because it is a well-established framework with validated metrics. Prior research indicated its link to employee creativity [24,66,67], and further research has developed its alignment with sustainability [68].

2.2. Simons’ Levers of Controls Framework

Simons’ LoC framework was selected as the theoretical foundation of this study because it focuses on how to exert control within an organisational setting to enable employees’ innovation, creativity, and flexibility.
According to Simons’ LoC framework, to improve employees’ creativity, employees must be psychologically empowered enough to be more creative to address client demands and provide better offers to clients, eventually resulting in improved outcomes of the organisations and creative performance [24,44]. Further, the literature supports that firms prioritising SLCs are able to enhance their employees’ green creativity [24,55].
Simons proposed that each of the four control levers is distinct in fostering employee creativity. The belief lever of the LoC framework focuses on organisations’ core values. Organisations’ boundary systems are concerned with risk-aversion behaviour. The interactive lever focuses on strategic uncertainty and serves as an incentive for continuous discussion about the organisations’ underlying assumptions and action plans. The diagnostic control lever of the LoC framework monitors progress while concurrently assessing goal accomplishments at each corporate level, relieving managers of the strain of constantly monitoring personnel [24]. The LoC framework was employed in this study because it offers a structured approach and a platform for extending the analysis into the impact of SCSs [45,46,47,48].
Simons’ LoC framework [24] was critiqued by Ferreira and Otley [66] and by Tessier and Otley [67] for not incorporating informal (socio-ideological) controls. Despite this critique, the focus of the LoC framework aligns well with the focus of our research on formal controls and sustainability efforts, making it a suitable theoretical basis for this research study.
Another weakness of the LoC framework is the dispute over the definitions of levers [66,67], although the operationalisation of the metrics has been empirically validated [24]. The literature on sustainability and management has devoted considerable attention to the LoC framework. Authors have emphasised the importance of this framework in evaluating the development and implementation of sustainable development initiatives [68,69]. Therefore, the LoC framework provides a holistic perspective on control systems and provides a basis for the extension of MCSs [67] into SCSs [68].
While previous studies have investigated the use of single controls such as performance measurements [43,48,60], our research employs all four levers of Simons’ LoC framework simultaneously, as the importance of using multiple levers together has been emphasised by several researchers [3,44,46,70]. This is consistent with the manner in which Widener [55], Speklé, Van Elten, and Widener [61], Revellino and Mouritsen [70], and Mundy [71] applied the LoC framework, operationalising the use of four levers of control systems as a second-order construct.

2.3. Introducing Sustainable Control Systems (SCSs) and Employees’ Green Creativity (EGC)

The literature confirmed the role of MCSs as one of the main factors managers consider when creating a work environment that will stimulate EGC [43,72,73]. Researchers highlight the need to include sustainability requirements and demands of non-shareholder stakeholders because MCSs are perceived to facilitate only financial decision making [45,68,73]. In response to this demand, SCSs are defined in the literature as “all devices and systems that managers build and utilise to guarantee that their workers’ behaviours and choices are aligned with the organisation’s sustainability goals and strategy” [45] (p. 6). SCSs aim to meet the changing demands faced by conventional MCSs, bringing more sustainability to the increasingly sustainability-driven agenda of today’s complex corporate settings [74].
With the growing attention to environmental issues triggered by extensive technological changes, organisations worldwide are now looking towards encouraging EGC [27]. The notion of EGC is derived from the concept of creativity [27,31,75] and is defined as “the generation of new ideas concerning green goods, services, processes, or behaviours that are regarded to be creative, innovative, and valuable.” [31] (p. 113). Furthermore, consumers’ interest in environmental protection is peaking, and they prefer to embrace green ideas and green products and are even ready to pay a higher price for those products. As a result, organisations today are prepared to follow green practices that motivate EGC [30,76].

2.4. The Impact of Sustainable Control Systems (SCSs) on Employees’ Green Creativity (EGC)

Although Simons’ LoC framework was proposed to enable employee creativity [24], there is a lack of substantial empirical evidence to support this claim [43,77]. Kruis, Speklé, and Widener [78] agree with Simons [24] that the four control levers operate in coordination and suggest that a system with all four control levers is linked to greater employee creativity. Crutzen, Zvezdov, and Schaltegger [45] suggest extending the LoC model by integrating sustainability dimensions into MCSs. Thus, Simons’ LoC framework was extended by incorporating sustainability dimensions into the MCSs, thereby creating the SCSs [46,48,59]. SCSs are a specialised application of MCSs, incorporating dimensions of sustainability outcomes [49].
Our study builds on empirical evidence from previous research on the relationship between MCSs and employee creativity [43,61,77] and further extends the LoC framework from MCSs to SCSs. Prior research examining the connection between MCSs and employee creativity found a positive relationship between the two [43,77]. Reviewing prior empirical research, we hypothesise the relationship between SCSs and EGC as follows:
Hypothesis 1 (H1).
The intensity of the application of SCS Levers is positively associated with EGC.
H1 is supported by Simons [24], Appuhami [43], Moulang [59], and Lill et al. [77], presenting conceptualisation and empirical evidence linking MCSs to employee creativity (see Table 4).

2.5. Mediating Role of Psychological Empowerment (PE)

PE refers to the internal motivation of employees and their sense of control over their own work [43,56,57,58,59,60]. Organisations with employees having greater self-assurance and autonomy will enjoy greater flexibility to pursue their objectives and opportunities [44]. Mundy [71] provided evidence to support this claim and emphasised that employing MCSs most often leads to enhanced clarity and a better grasp of the work environment that inspires creativity. The relationship between PE and EGC is also documented in the literature, implying that the emotions of ownership and control over one’s work stimulate employee creativity [78]. According to Sun et al. [80], employees’ feelings about PE encourage them to experiment with new methods of accomplishing their tasks, which leads to more creative behaviours. We build on the previous work of Appuhami [43] and Moulang [59], which found that PE has a significant mediating effect on the relationship between the components of MCSs and employee creativity. We extend this observation to the mediating role of PE in the relationship between SCSs and EGC. Therefore, we hypothesise that:
Hypothesis 2 (H2).
PE mediates the relationship between SCS and EGC.
H2 consists of sub-hypothesis H2a and H2b for the purpose of testing mediation, supported by the findings of Appuhami [43], Spreitzer [56], and Moulang [59] (see Table 4).

2.6. The Mediating Role of Sustainability Learning Capabilities (SLCs)

The literature on organisational theory and management provides evidence to demonstrate the mediating role of employees’ learning capabilities in the relationship between MCSs and employee creativity [24,55,79]. Appuhami [43] confirms that organisational learning promotes employees’ creativity in their work. Furthermore, employees’ work experience and training attained through the organisation’s learning process are essential tools managers use to promote employee creativity and innovation [43,81].
Organisational learning is one of the key components of sustainable initiatives, including green creativity, in firms [82]. SLCs are therefore understood as capabilities for individual and collective learning withing the context of an organisation, targeting sustainability-related skills and capabilities [46].
By enhancing sustainability learning capabilities, organisations can pursue proactive sustainability strategies that build capabilities related to sustainability [46]. Appuhami [43] and Grafton, Lillis, and Widener [62] recognised the importance of organisational learning capabilities as a mediator in understanding the relationship between MCSs and employee creativity. Although researchers of EMC acknowledge the value of learning as an essential component of achieving employee creativity, the role of SLC has only been addressed conceptually, not empirically [46]. To fill this gap in empirical knowledge, we investigate the mediating role of SLC in explaining the relationship between SCSs and EGC by developing the following hypotheses:
Hypothesis 3 (H3).
SLC mediates the relationship between SCSs and EGC.
H3 consists of sub-hypothesis H3a and H3b and is supported by the findings of Simons [24], Appuhami [43], Wijethilake and Upadhaya [46], Moulang [59], Chenhall [60], Amabile [75], Lill, et al. [77], and Henri [79].
Table 4 provides a summary of hypotheses, sub-hypotheses, and sources of literature used to establish the hypotheses. The conceptual framework of this research study is presented in Figure 1, showing how the relationships between the constructs are hypothesised.
Figure 1 presents the conceptual framework, including the above hypotheses.

3. Methods

3.1. Methodology

The quantitative approach is frequently applied in management accounting research, especially in examining MCSs [7,43]. In line with this, our study also adopts the quantitative approach to test hypotheses presented in the conceptual framework (see Figure 1). Our unit of analysis is defined as the participating organisations, and organisational level response values were calculated as the average of respondents belonging to the same organisation, as customary in management accounting research [43,78,83,84,85]. Furthermore, we believe that the organisational level is the most appropriate to reflect the implications of sustainability in this research context.
We used SPSS and PLS-based structural equation modelling (PLS-SEM) with SmartPLS 3.0 software [86]. The descriptive analysis was performed using SPSS software. SmartPLS is often used in management accounting research [86] and to examine the role of MCSs and SCSs in different organisational contexts [7,43]. We used the SmartPLS 3.0 software to validate the measurement model, assess the structural model, and test the hypotheses in the two-stage approach recommended by Henseler, Ringle, and Sinkovics [87,88,89,90,91,92,93,94,95].
The Preacher and Hayes method using PLS-SEM [88] was used to examine the mediating effects. The first step of testing the mediating effect was the direct relationship between the dependent (EGC) variable and the independent (SCSs) variables [89,90,91,96,97]. The second step was testing the association of the predictor (SCSs) with the mediators (i.e., PE and SLCs). Third, after controlling for the predictor, the mediators must be significantly related to the outcome (EGC). Finally, if the relationships between the independent and dependent variables are no longer significant after introducing the mediators, the association is identified as fully mediated; otherwise, it is possible to conclude the presence of partial mediation.

3.2. Instruments

Table 5 provides basic details of the scales used to measure the key constructs in the model. SCSs and PE are multidimensional, higher-order constructs, and SLCs and EGC are single-dimensional scales. The literature provides Cronbach’s alpha scores for each of the validated scales, noted in the table, providing a benchmark for our research.
Following the literature, the independent variable (SCSs) is identified as a higher-order construct composed of four low-order constructs: belief systems (BLIEF), boundary systems (BOUND), interactive systems (INTER), and diagnostic systems (DIAG) [3]. This construct was measured using the scale developed by Wijethilake [3], consisting of 23 items. The dependent variable EGC is measured using the scale developed by Chen and Chang [31]. The first mediating variable, PE, is measured using the scale developed by Spreitzer [56], consisting of 12 items. The literature presents PE as a higher-order construct composed of meaning (ME), competence (COM), self-determination (SD), and impact (IM). The second mediating variable, SLC, is measured using the scale developed by Wijethilake and Upadhaya [46], consisting of six items. All four constructs in the study are measured using a five-point Likert-type scale ranging from “strongly disagree (1)” to “strongly agree (5)”.

3.3. Data Collection

Similar to research carried out by Wijethilake [3] on MCSs and SCSs, sustainability managers and other senior-level and middle-level managers engaged in sustainability initiatives were chosen as participants in this study. Participation was voluntary, and respondents indicated their perceptions about the sustainability practices [98] of their organisations. Purposive sampling was utilised in this study to ensure the selection of relevant respondents. Manufacturing organisations were selected in the sample from reference databases provided by key institutional stakeholders, such as the Colombo Stock Exchange, the Ceylon Chamber of Commerce, the International Chamber of Commerce in Sri Lanka, and the Board of Investment in Sri Lanka, due to the lack of one single comprehensive database of manufacturing businesses in Sri Lanka. Wijethilake [3], Rupasinghe and Wijethilake [7], and Wijethilake and Upadhaya [46] have all followed similar methodology for recruiting respondents. The potential respondent companies were screened for a strong public profile and dedication to sustainability, such as having a webpage and publishing sustainability reports or other similar forms of sustainability disclosures in annual reports or on their websites. This was to ensure the validity [99] of the responses, and to meet the sampling criteria (manufacturing sector). Managers from selected organisations were identified from the databases or the company websites and were invited to participate in the study by emails and follow-up phone calls.
The Sri Lankan manufacturing sector was selected for this study for several reasons. Firstly, compared to other similar developing economies in the South Asian region, such as Pakistan, Maldives, and Bangladesh, Sri Lanka’s CO2 emission levels from manufacturing industries have outgrown those from the agricultural and service sectors over the past decade [98,100]. Secondly, the manufacturing sector made a significant economic contribution to the Sri Lankan national economy [100], as well as to the carbon emissions of the country [101]. Thirdly, the contribution of the manufacturing sector to international trade [102] has been outstanding. Finally, growing public concerns about unsustainable practices [3] have drawn our attention to the manufacturing sector in Sri Lanka [53].
An online survey [92] was used to collect data, where each manufacturing organisation was assigned a unique ID number and a separate survey form was developed for each organisation to facilitate the anonymous collection of responses per organisation. After selecting the manufacturing organisations, telephone calls were made to confirm the accuracy of the contact details of the respondents and to encourage the managers to participate in the survey. The e-mail invitations, including a cover letter explaining the research objectives and describing the conditions of participation (confidentiality of responses, voluntary participation) and unique survey response links, were provided to potential participants. This strategy allowed the researchers to quickly and accurately calculate average response scores for every organisation. Accordingly, 315 form links were produced and sent to 824 respondents from 315 organisations, of which 505 responses were returned from 244 organisations. After cleaning the data from outliers, responses from 239 organisations remained. This resulted in an individual response rate of 61.3%, with the information provided on 77.4% of organisations selected for the study.

4. Results

4.1. Demographic Analysis

The survey received 505 individual responses from 244 organisations. The data from 244 organisations were screened for outliers using SPSS. Five outliers were discovered and removed, resulting in 239 organisations considered for further analysis. Table 6 provides further descriptive statistical information on the distribution of the organisational level unit of analysis and response numbers.
The majority of respondents (84.6%) were male, and 69.1% were between the ages of 28 and 45. A total of 56.8% of respondents had, at most, a first-degree academic qualification, and middle-level managers were represented by the majority of respondents (66.1%).
In order to control for the impact of demographic characteristics on the dependent variable (EGC), we tested the correlation with selected organisational demographic variables. Our findings showed no significant relationships between EGC and the number of employees (β = −0.013, t = 0.307, p = 0.759), industry sub-groups (β = 0.045, t = 0.996, p = 0.319), and the nature of the organisation (β = −0.018, t = 0.382, p = 0.703), as defined in Table 6. Therefore, we excluded the demographic variables from further analysis.
The representativeness of the sample is illustrated by the alignment between the distribution of respondents from different industries and the relative contribution of these industries to the national GDP (sourced from [100,101,102]). Considering the lack of publicly available sector-specific organisational information, this remains the only accessible means of demonstrating representation. It is clear that industries with higher representation in our sample have also contributed a greater proportion to Sri Lanka’s GDP, indicating some degree of representation.

4.2. Reliability and Validity of Lower-Order Constructs

Following the suggestions of Sarstedt et al. [93], we used the reflective indicator loadings and internal consistency indices to test the reliability of the scales and AVE scores to test convergent and discriminant validity. Composite reliability and Cronbach’s alpha were employed to examine internal consistency [93]. Hair, Ringle, and Sarstedt [94] recommend eliminating items with loadings below 0.4, while Falk and Miller [95] suggest that a minimum of 0.55 is necessary for indicator loadings.
Figure 2 presents the standardised indicator loadings and path coefficients of the final PLS-SEM model. This figure provides an overview of details necessary to validate the measurement model and to respond to our hypotheses. In our study, none of the items needed to be discarded due to low loadings (below 0.5). Therefore, the initial measurement model was used to calculate Cronbach’s alpha, composite reliability, and AVE (as reported in Table 7).
All the lower-order constructs in this model have exceeded the threshold level for AVE of 0.708 [94], confirming that the constructs of this model have adequate reliability and convergent validity. The results of the statistical validation of scales align with the findings from the previous works of Appuhami [43], Moulang [59], Wijethilake and Upadhaya [46], and Speklé, van Elten, and Widener [61].
We used the Fornell–Larcker criterion to establish the discriminant validity of the scales. According to the Fornell–Larcker criterion, the square root of AVE needs to be greater than the correlation with the other latent variables [87]. Following this method, we confirmed discriminant validity for all reflective, lower-order constructs (see Table 8).

4.3. Reliability and Validity of Higher-Order Constructs

SCS and PE are higher-order constructs in our model. Hair et al. [94] suggest that the validity and reliability of higher-order constructs are derived from their related lower-order constructs. The higher-order constructs of SCS and PE have AVE values of 0.518 and 0.680, which are greater than the criterion of 0.5, demonstrating validity [94]. Moreover, the composite reliability of these higher-order constructs, SCS (0.800) and PE (0.887), are greater than the suggested criterion of 0.7, which confirms that they are reliable [94].

4.4. Structural Model Analysis

The VIF values for all variables in the model are less than 5, suggesting that multicollinearity is not a significant issue in the study [88]. The results show an R2 value of 0.548 for the dependent variable EGC, which is a satisfactory level recommended by Hair et al. [88]. Furthermore, we evaluated the model results based on the effect size (f2) as well. By removing constructs from the model one by one, the effect sizes (f2) of the relevant model components were calculated, as suggested by Hair et al. [88]. The results show that the effect size of PE (f2) of 0.080 is minor. The effect size (f2) of SLC indicates a moderate impact of 0.332, and the effect size (f2) of SCS is 0.07, which is considered low.

4.4.1. Hypothesis Testing for Direct Relationships

Table 9 presents the findings related to hypothesis testing for the direct relationships between SCSs and EGC (using bootstrapping with 5000 subsamples). The results reveal that SCSs do not have a significant direct impact on EGC (β = −0.039, t = 0.361, p = 0.718). Hence, H1 was rejected. Moreover, the lack of a significant direct relationship between SCSs and EGC suggests that the direct effect of SCSs on EGC may be mediated by other factors. Furthermore, the results revealed that SCSs have a significant association with PE (β = 0.672, t = 17.091, p = 0.000) and SLC (β = 0.770, t = 20.397, p = 0.000). Hence, H2a and H3a were accepted. The results also confirmed that PE (β = 0.265, t = 4.750, p = 0.000) and SLC (β = 0.564, t = 6.085, p = 0.000) have a significant, positive association with EGC, whereby H2b and H3b were supported.

4.4.2. Hypothesis Testing of Mediating Relationships

Responding to Hypotheses 2 and 3 requires mediation testing. The mediating effects were tested using the Preacher and Hayes model for PLS-SEM [88]. The results revealed a significant total effect of SCSs on EGC (H1: β = 0.574, t = 8.447, p = 0.000). With the inclusion of the mediating variables of PE and SLC, the direct effect of SCS on EGC lost significance (β = −0.039, t = 0.367, p = 0.713). The indirect effect of SCSs on EGC through the mediating variable PE is significant (β = 0.178, t = 4.788, p = 0.000). Hence, H2 was accepted, as the full mediation of PE was proven. The indirect effect of SCSs on EGC through the mediating variable SLC was also found to be significant (β = 0.434, t = 5.829, p = 0.000). This shows that PE and SLC fully mediate the relationship between SCSs and EGC. Table 10 provides a summary of the statistical test results of the path coefficients (direct and indirect path coefficients, significance levels) related to our hypotheses.

5. Discussion and Conclusions

Our study’s first objective was to examine the influence of SCSs on EGC. The second and third research objectives were to test the respective mediating effects of PE and SLC on the relationship between SCSs and EGC. The results of this study confirm that SCSs do not directly enhance EGC but enhance EGC indirectly through the full mediation of PE and SLC in the case of Sri Lanka’s manufacturing organisations.
This study contributes to the management accounting literature by filling the theoretical gap identified by Moulang [59] and Widener [55] in terms of Simons’ LoC framework. By incorporating the sustainability dimensions into the traditional MCSs concept [47,48], the extension of the framework is validated in the Sri Lankan context. Hence, our study concludes that Simons’ traditional LoC framework can be further improved by integrating sustainability dimensions, as suggested by Wijethilake [3].
As specified in Table 4 by hypotheses H2, H2a, and H2b and H3, H3a, and H3b, PE and SLCs fully mediate the relationship between SCSs and EGC. This suggests that SLCs and PE are essential strategic components facilitating the effectiveness of SCSs in achieving EGC in Sri Lankan manufacturing organisations. Supporting the findings of this study, the crucial role of SLCs has been highlighted in the literature. For example, Grafton, Lillis, and Widener [61] and Appuhami [43] emphasised the importance of organisational learning capabilities as a mediator in understanding the relationship between MCSs and EC in the workplace. Furthermore, Siebenhüner and Arnold [82] pointed out that sustainability may be implemented into controls to increase employees’ SLC to promote desired outcomes, such as EGC. Moreover, our results are consistent with the findings of previous empirical studies such as Appuhami [43], Speklé, van Elten, and Widener [61], Mundy [71], and Henri et al. [79], who state that individuals who feel psychologically empowered are more likely to be creative within their work roles. By providing evidence for the full mediating role of PE in the relationship between SCSs and EGC, we contribute to the body of knowledge by empirically validating the extension of MCSs to SCSs, and provide evidence for the application of EGC instead of the more generic green creativity concept.
Our findings align with the extended LoC theory. However, our result regarding the direct effect between SCSs and EGC (H1) seemingly contradicts previous empirical results [24,43,61,71]. This, however, needs to be understood in the context of the presence of mediating factors. While the lack of a significant, direct relationship without mediators involved would be contrary to our expectations, by introducing factors that fully mediate the relationship, we have methodologically predetermined the failure of the direct relationship. Findings similar to ours are presented, for instance, by Webster [97], who tested Simons’ LoC framework and came up with similar results, namely the lack of a direct relationship between MCSs and employee creativity. Some other studies also used middle-level managers [43,61,71] and found neither a direct nor a mediated association between MCSs and employee creativity.
Considering the similarity between our results and some prior empirical research regarding the lack of a significant, direct relationship between MCSs (SCSs) and employee creativity (EGC), we feel that we have provided a substantial contribution to the body of knowledge by the introduction of mediating variables. Considering prior research, especially those results that found no significant relationship between MCSs and employee creativity, the lack of relationship may have been due to model misconfiguration (missing the appropriate mediating factors). By extending the conceptualisation with mediating factors relevant to SCSs and EGC, in the Sri Lankan context, we were able to demonstrate the link between MCSs and employee creativity.
We believe that the difference in the research context had an influence on our findings, because those prior studies that confirmed the strong direct association between MCSs and employee creativity were undertaken in developed countries [43,59]. Moreover, the literature confirms that organisations in more developed nations use more sophisticated SCSs than their developing nations’ counterparts [96]. Considering the context of SCSs in the Sri Lankan manufacturing sector, which is similar to that in other developing nations [4], the mediating factors provide the additional explanation needed to create the link between MCSs and employee creativity.
These results provide grounds for specific managerial implications. Organisations in Sri Lanka could foster a better internal environment that facilitates SCSs that support EGC by psychologically empowering and encouraging employees’ SLCs. These green managerial strategies can reduce business failures in the Sri Lankan manufacturing context due to the lack of EGC. Furthermore, managers can incorporate SLCs into the organisation’s core values, considering sustainability learning as an investment that ensures corporate sustainability. Managers can also disseminate information about the manufacturing industry’s sustainability expectations and encourage learning through internal experiments and external links to generate greener and more creative employee skills and mindsets through implementing SCSs. The findings of this study further confirm the possibility for managers to foster environmentally conscious and creative employees in the Sri Lankan manufacturing sector by encouraging the latter to believe that their tasks are significant and have an impact on others while simultaneously providing them with greater independence and empowerment.
Future research could extend this study by examining the relationship between SCS and EGC in different industrial and geographical contexts. Comparative studies could also be carried out on different industries or countries at varying levels of economic development. Furthermore, this study used only two mediators, whereas future researchers could introduce some other potentially context-specific mediating variables, such as the role of organisational leadership, culture, or mindset.
Further research in other contexts (developed economies and other Asian countries) could assist with exploring the relationships between SCSs and EGC. A repeated validation of our findings, considering specific metrics regarding the sophistication of control systems and the nature of sustainable development objectives, could also allow us to examine specifically why our findings regarding the significance of the direct relationship differ from the expectations based on the LoC framework. However, this may be better explored by utilising qualitative methodologies, where specialised managers from control, innovation, and HR areas could provide deeper insights into the reasons for specific employee motivations and green creativity practices.

Author Contributions

Conceptualisation, D.N.P., E.A.G.S. and Á.P.; methodology, D.N.P., E.A.G.S. and Á.P.; formal analysis, D.N.P.; investigation, D.N.P. and E.A.G.S.; writing—original draft preparation, D.N.P.; writing—review and editing, Á.P., D.N.P. and E.A.G.S.; visualisation, D.N.P.; supervision, E.A.G.S.; project administration, E.A.G.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to formal ethical authorisation not being required for survey-based research on non-sensitive topics in Sri Lanka.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data for this research are held by the researchers.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 04806 g001 550
Figure 1. Conceptual framework.
Figure 1. Conceptual framework.
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Figure 2. PLS-SEM model.
Figure 2. PLS-SEM model.
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Table
Table 1. Corporate failure prevention strategies.
Table 1. Corporate failure prevention strategies.
Possible Strategies/Solutions
Internal PoliciesCapital StructureEGC
Theories
used		Corporate GovernanceCore et al. [22]
Capital Asset Pricing Model Elbannan [23]
Creativity and Innovation Simons [24]
Empirical
context		Developed EconomiesElsayed et al. [12]Chan et al. [14]Lyu et al. [19]
Developing EconomiesMulili and Wong [10]Altay and Çalgıcı [17]AlQershi et al. [20]
AsiaGoyal and Kumar [13]Rasool et al. [16]Shah et al. [18]
Sri LankaLakshan and Wijekoon [11]Samarakoon and Lanka [15]Sivashanker [21]
Source: Authors’ compilation.
Table
Table 3. Theoretical frameworks of MCS.
Table 3. Theoretical frameworks of MCS.
Theoretical FrameworkKey Aspects of the FrameworkSource
Simons’ Levers of Controls (LoC) FrameworkBelief systemsSimons [24]
Boundary systems
Diagnostic control systems
Interactive control systems
Bureaucratic, Output, Delegated, and Patriarchal Control SystemsBureaucratic control systemsWhiteley [63]
Output control systems
Delegated control systems
Patriarchal control systems
Rudimentary, Broad Scope, and Traditional ControlsRudimentary controlsGerdin [64]
Broad scope controls
Traditional (narrow) controls
MCSs as a PackagePlanning controlsMalmi and Brown [65]
Cybernetic controls
Reward and compensation controls
Administrative controls
Cultural controls
Source: Authors’ compilation.
Table
Table 4. Summary of hypothesis.
Table 4. Summary of hypothesis.
HypothesesSub-HypothesesSources
H1 Appuhami [43]; Lill et al. [77]; Moulang [59]; Simons [24]; Spreitzer [56]
H2H2a: The intensity of the application of SCSs levers is positively associated with PE.Appuhami [43]; Moulang [59]
H2b: PE is positively associated with EGC.Appuhami [43]; Moulang [59]; Spreitzer [56]
H3H3a: The intensity of the application of SCSs levers is positively associated with SLCs.Appuhami [43]; Chenhall [60]; Henri [79]; Wijethilake and Upadhaya [46]
H3b: SLC is positively associated with EGC.Amabile [75]; Appuhami [43]; Jimenez and Sanz (2011); Moulang [59]; Spreitzer [56]
Source: Authors’ compilation.
Table
Table 5. Measurement scales.
Table 5. Measurement scales.
ConstructDimensionsNo. of Scale ItemsCronbach’s AlphaSource
Sustainability Control Systems (SCSs)BLIEF60.885Wijethilake [3]
BOUND60.900
INTER50.934
DIAG60.878
Psychological Empowerment (PE)ME30.919Spreitzer [56]
COM30.759
SD30.888
IM30.863
Sustainability Learning Capabilities (SLCs)-60.896Wijethilake and Upadhaya [46]
Employees’ Green Creativity (EGC)-60.913Chen and Chang [31]
Source: Authors’ compilation.
Table
Table 6. Demographic profile of organisations.
Table 6. Demographic profile of organisations.
VariableCategoryFrequency%
Nature of organisationLocal20184.1%
Multinational Enterprises (MNEs)3815.9%
TOTAL239100%
Number of employeesBelow 100135.4%
100–100010744.8%
1001–10,0009740.6%
Above 10,000229.2%
TOTAL239100%
IndustryIndustry sub-groupsFrequency%GDP% *
Basic Metals and Fabricated Metal Products
Chemical Products and Basic Pharmaceutical Products
Coke and Refined Petroleum Products
Food, Beverages, and Tobacco Products
Furniture
Machinery and Equipment
Other Manufacturing, and Repair and Installation of Machinery and Equipment
Other Non-Metallic Mineral Products
Paper Products, Printing and Reproduction of Media Products
Rubber and Plastic Products
Textiles, Wearing Apparel, and Leather-Related Products
Wood and of Products of Wood and Cork, except Furniture		93.8%0.5%
31.3%1.0%
31.3%0.3%
6627.6%7.4%
125.0%1.0%
166.7%0.6%
239.6%0.9%
93.8%0.6%
93.8%1.1%
125.0%0.5%
7029.3%5.1%
72.9%0.6%
TOTAL239100%19.1%
Number of respondents in participating organisationsNumber of respondents per organisationInvitedResponded
Frequency%Frequency%
0 respondents00%7122.5%
1 respondent00%00%
2 respondents10332.7%22872.4%
3 respondents13442.5%144.4%
4 respondents6721.3%10.3%
5 respondents113.5%10.3%
TOTAL315100%315100%
Source: Based on survey results and * latest available years for GDP distribution [100,101,102].
Table
Table 7. Measurement model assessments for lower-order reflective scales.
Table 7. Measurement model assessments for lower-order reflective scales.
ConstructsCronbach’s AlphaComposite ReliabilityAVE
BELIEF0.8790.9090.63
INTER0.8850.9130.635
BOUND0.8630.9030.652
DIAG0.8830.9110.633
ME0.8210.8930.736
COM0.880.9270.812
SD0.8440.9070.765
IM0.8760.9240.803
EGC0.9340.9480.752
SLC0.8760.9060.617
Source: Based on survey results.
Table
Table 8. Discriminant validity (Fornell–Larcker Criterion).
Table 8. Discriminant validity (Fornell–Larcker Criterion).
BELIEFBOUNDCOMDIAGEGCIMINTERMESDSLC
BELIEF0.794
BOUND0.0740.807
COM0.4760.2510.901
DIAG0.3230.2350.5040.795
COM0.4070.2030.4700.3870.867
EGC0.3990.2020.6080.3610.5510.896
INTER0.4660.2600.5590.640.5740.5780.797
ME0.2790.3750.5530.4060.5270.5610.3920.858
SD0.3870.2280.5240.3570.5220.6560.470.5370.875
SLC0.4520.2920.5760.6470.7160.5680.7240.6040.520.786
Source: Based on survey results, the diagonal contains the square root of the average variance extracted.
Table
Table 9. Hypothesis testing of direct relationships.
Table 9. Hypothesis testing of direct relationships.
HypothesisRelationshipΒSDT Statisticsp ValuesLower 2.50%Upper 97.50%Decision
H1SCS → EGC−0.0390.1070.3630.716−0.2390.182Rejected
H2aSCS → PE0.6720.03917.1180.0000.5810.738Accepted
H2bPE → EGC0.2650.0564.6990.0000.1390.366Accepted
H3aSCS → SLC0.7700.03720.6910.0000.6870.833Accepted
H3bSLC → EGC0.5640.0946.0140.0000.3780.746Accepted
Source: Based on survey results.
Table
Table 10. Assessment of total effects, direct effects, and specific indirect effects.
Table 10. Assessment of total effects, direct effects, and specific indirect effects.
EffectPathPath Coefficientt StatisticsSignificanceHypothesis
Total EffectSCS → EGC0.5748.4220.000H1
Direct EffectSCS → EGC−0.0390.3630.716H2c
Specific Indirect EffectSCS → PE → EGC0.1784.8800.000H2
SCS → SLC → EGC0.4345.6320.000H3
Source: Based on survey results.
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Pandithasekara, D.N.; Sumanasiri, E.A.G.; Perényi, Á. Exploring the Impact of Sustainability Control Systems on Employees’ Green Creativity: The Mediating Role of Psychological Empowerment and Sustainability Learning Capabilities. Sustainability 2023, 15, 4806. https://doi.org/10.3390/su15064806

AMA Style

Pandithasekara DN, Sumanasiri EAG, Perényi Á. Exploring the Impact of Sustainability Control Systems on Employees’ Green Creativity: The Mediating Role of Psychological Empowerment and Sustainability Learning Capabilities. Sustainability. 2023; 15(6):4806. https://doi.org/10.3390/su15064806

Chicago/Turabian Style

Pandithasekara, Dasuni Nirmani, Erabaddage Ayoma Gayathri Sumanasiri, and Áron Perényi. 2023. "Exploring the Impact of Sustainability Control Systems on Employees’ Green Creativity: The Mediating Role of Psychological Empowerment and Sustainability Learning Capabilities" Sustainability 15, no. 6: 4806. https://doi.org/10.3390/su15064806

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