Organisational control systems, such as quality assurance and corporate governance, configure an organisation’s internal environment to manage the velocity of change and pro-actively stabilise disturbances. Resilience in a socio-technical system is a multi-disciplinary approach to instil a system’s transformability and adaptive capacity to achieve desirable outcomes and continuous improvement. This study confirms theoretical postulations that detachment between the disciplines of quality assurance and corporate governance reduces resilience in a socio-technical system. Coherence between these disciplines in a complex socio-technical system is achieved through four components of organisational resilience: strategic management and company culture, monitoring and awareness, exposure management and responsive adaptation.
This study aimed to explore stakeholders’ perceptions of the relationship between the components of organisational resilience and organisational control systems in the South African aviation industry.
A cross-sectional survey was used to collect data from 203 stakeholders in the South African aviation industry. The data set was subjected to descriptive and inferential statistical analyses.
A strong positive linear relationship exists between organisational control systems and organisational resilience and its four components: Strategic management and company culture, Monitoring and awareness, Exposure management and Responsive adaptation.
This study revealed that a harmonised application of organisational control systems, such as quality assurance and corporate governance, stimulates organisational resilience in a socio-technical system through the autonomous advancement of four components of organisational resilience. Furthermore, the robustness of organisational control systems activates an organisation’s capacity to adapt sustainably, whilst maintaining stakeholder value within complex socio-technical systems, such as the aviation industry.
The aviation system consists of various interactive and interdependent components including manufacturing and engineering, the operation of aircraft, infrastructure, personnel licencing and organisational certification that enables organisations to provide a service to society (The Department of Transport
Continual growth in the international air transport system requires developing and implementing policies and practices to increase mutually beneficial value for all stakeholders (Njoya
The aviation industry remains a diverse environment where various components play a vital role in the overarching realisation of an efficient and reliable transportation solution (Lazur et al.
Organisational resilience, as a desired capacity of an organisation’s sustainability, supports the discourse to dynamically reinvent business models and organisational strategies in response to circumstantial changes before such adaptation becomes critical (Hamel & Välikangas
The South African aviation industry provides scheduled and non-scheduled air transportation through the utilisation of all the components of the aviation system (eNCA
The aviation industry can be described as a system of systems with interrelationships on multiple levels (Harris & Stanton
Hickford et al. (
A socio-technical system is not merely an aggregation of people, technology, organisations and institutions to produce outputs, but intentional hybrids (Amir & Kant
Reliability in the aviation system depends on the outcome and condition of all participating system components, the external environment and the critical complexity of interaction between the system elements and the environment (Patriarca et al.
Organisational resilience and competitive advantage in the marketplace are directly related to each other, and the relationship between organisational resilience and competitive advantage is embedded in an organisation’s ability to ‘maintain above-average returns even after absorbing the shocks of the competitive environment’ (Teixeira & Werther
The characteristics of a resilient organisation include the ability to manage internal and external complexities and changes through holistic thinking, acknowledgement of multiple perspectives and reframing the complexities and changes as moving targets (Teixeira & Werther
Although various definitions of corporate governance have been coined in the past three decades, its essence remains ‘the system by which companies are directed and controlled’ to ensure all-inclusive sustainability and value (Marx & Mohammadali-Haji
Dutta, Lanvin and Wunsch-Vincent (
Consistent with this view, Chialastri and Pozzi (
The risks that emerge from detachment between quality assurance and corporate governance include reduced stakeholder reputation, reduced competitiveness and the inability to adapt to the rapidly changing macro-environment (Amankwah-Amoah
Previous research suggests the need to further interrogate the relationship between management control processes that address commercial management and technical outcomes (Lazur et al.
This study aimed to explore the relationship between organisational control processes, such as quality assurance and corporate governance, and organisational resilience in the South African aviation industry through stakeholders’ perception.
This article represents the quantitative survey of a more extensive mixed-method study that was conducted to explore the interface between organisational control systems (quality assurance and corporate governance) and organisational resilience properties in the South African aviation industry (Serfontein & Govender
The qualitative phase of the larger sequential mixed-method study by Serfontein and Govender (
Organisational resilience properties embedded in organisational control systems.
Through the application of quantitative data analysis, a variable, or individual identifiable attribute of a subject, can be examined and explained (Agresti & Finlay
Variables are structured according to temporal order and observatory measurement (Creswell
As such, organisational control systems are denoted as the IDV and organisational resilience as the DV. The DV consisted of four subcategories, namely Strategic management and company culture (DV1), Monitoring and awareness (DV2), Exposure management (DV3) and Responsive adaptation (DV4).
Yin (
The shared characteristic of the target population was based on The Department of Transport’s (
Categories of stakeholders to the South African civil aviation system.
Stakeholder category | Description |
---|---|
Governance stakeholder | Responsible for policy and regulation development to simultaneously maintain economic viability and technical operating standards compliant to municipal, governmental and international requirements. |
Commercial stakeholder | Associated with scheduled and/or non-scheduled economic activity and supply chain within the aviation system, inclusive of entities that provide or procure services/goods such as fuel, aircraft maintenance services, air travel services, training and staff certification, airports, air traffic organisations, etc. |
Support stakeholder | Direct and indirect facilitation of commercial stakeholders’ operation and service provision, such as insurance organisations, financing institutions, travel agents, cargo and shipment organisations, etc. |
Society stakeholder | Stakeholders who do not directly participate in the civil aviation system’s service provision activities but who have a direct interest in the civil aviation system’s economic, safety, security and environmental performance. |
Security stakeholder | Responsible for the development and implementation of policy that enables regulating instruments relating to national security. Security stakeholders also include the South African Police Service and military veterans. |
Considering the accessibility of possible participants from the population (Martínez-Mesa et al.
Because Alvi (
To maintain the applicability of the survey in relation to the phenomenon of interest, the questionnaire design and content mirrored the embedded organisational resilience properties that the authors (Serfontein & Govender
The questionnaire embodied a Likert-type rating scale to realise numeric values associated with the level of agreement to each survey item (Greener
A preliminary pilot study is advisable to validate the instrument in support of criterion validation and benchmarking (Brough 2009; Kothari
The layout of the survey used for data collection purposes consisted of eight sections. The first section included ethical considerations and obtained informed consent from the participants. The second section included general instructions on the completion of the questionnaire. The third section included a screening question not only to ensure that participants represent the study sample, but also to classify the participant into the stratified sample described in
Because the respondents were purposively selected from the study population, participants were knowledgeable on the phenomenon of interest and committed to the voluntary completion of the survey. For increased accessibility, this study used the online platform SurveyMonkey to host the survey questionnaire between 28 January and 11 February 2020. After 14 days, the survey’s unique identifier provided to voluntary research participants was deactivated to cease data collection.
Data were extracted from the online platform, retained in an electronic database and reworked to remove redundant information by isolating participant responses to the survey questions. This sanitised version of the database was provided to a statistical consultant for analysis. Data collected from 203 respondents were analysed by using Microsoft Excel 2016 and STATA 15 (software for statistical and data science). This data set exceeded the intended sample size.
The measurement and analysis of each item in a survey questionnaire are not advisable if there is not a specific methodological rationale for the detailed and cumbersome approach (Boone & Boone
The Cronbach alpha was applied to determine internal consistency through value measurement (Saunders et al.
Data analysis followed a two-dimensional approach to address descriptive and inferential statistics. Whilst descriptive statistics allow numeric description and comparison of quantitative data (Saunders et al.
The introductory page of the survey questionnaire included pertinent information about anonymity and voluntary participation. Participants could only proceed to the subsequent sections of the survey once informed consent was acknowledged (Yin
Data were collected from 203 participants representing the different strata of the homogenous study population defined in
Stakeholder response frequency from the study sample.
Stakeholder type | Frequency ( |
% |
---|---|---|
Commercial | 121 | 59.61 |
Governance | 21 | 10.34 |
Security | 3 | 1.48 |
Society | 43 | 21.18 |
Support | 15 | 7.39 |
This study followed a composite approach to report aggregated descriptors for each variable in the relationship structure.
Organisational control systems (independent variable) descriptors.
Variables | Mean | Standard deviation | Minimum | Maximum | Factor loading |
---|---|---|---|---|---|
IDV1: Nature of the aviation industry | 4.31 | 0.43 | 2.83 | 5 | 0.43 |
IDV2: Quality assurance and corporate governance | 3.78 | 0.45 | 2.17 | 5 | 0.43 |
Note: Scale score = 8.55 out of a maximum of 10 and Cronbach alpha = 0.66.
IDV, independent variable.
The factor loading results for the IDV yielded an acceptable level of construct validity (Beckett et al. 2017) and indicate that the measurement tool employed for this study examined the construct as intended for a sample size exceeding 200 participants (Taherdoost
The valid and reliable research instrument indicates a scale score of 8.55 out of 10 for the statements that constituted the IDV. The scale score indicates the degree of agreeability of the participants to the questionnaire statements (Kothari
Organisational resilience (dependent variable) descriptors.
Variables | Mean | Standard deviation | Minimum | Maximum | Factor loading |
---|---|---|---|---|---|
DV1: Strategic management and company culture | 4.43 | 0.38 | 3.05 | 5 | 0.86 |
DV2: Monitoring and awareness | 4.33 | 0.38 | 3.26 | 5 | 0.92 |
DV3: Exposure management | 4.24 | 0.38 | 3.29 | 5 | 0.87 |
DV4: Responsive adaptation | 4.31 | 0.39 | 3.25 | 5 | 0.91 |
Note: Scale score = 17.31 out of a maximum of 20 and Cronbach’s alpha = 0.94.
DV, dependent variable.
The descriptive results for the DV yielded an acceptable construct validity as indicated by the respective factor loading results (Beckett et al. 2017) and suggest that this section of the data collection instrument is an accurate measurement of the subject matter within its setting (Taherdoost
Therefore, the survey content associated with the IDV is an accurate and reliable reflection of the topic analysed. The valid and reliable data collection tool yielded a scale score of 17 out of a maximum of 20 for the IDV and indicates an 86.55% of respondent agreement with the statements included in this section of the survey.
The above-mentioned results form the basis on which the relationships between the variables were analysed through inferential statistics. The inferential statistics methods used are correlation and regression analysis.
As a prerequisite to correlation and regression analysis, statistical assumptions such as normality, multicollinearity, heteroskedasticity and autocorrelation must be tested (Zaid
This study employed the variance inflation factor (VIF) to assess collinearity, and the VIF results were 3.55 (DV1), 5.07 (DV2), 3.85 (DV3) and 4.80 (DV4), respectively. As none of the variables indicated a VIF above 10, the possible adverse effects of significant multicollinearity can be eliminated (Agresti & Findlay
Heteroskedasticity, or the ‘extent to which data values for the dependent and independent variable have unequal variance’ (Saunders et al.
Reliability in regression analysis results can also be impacted by autocorrelation, which refers to the degree of similarity between the different values of variables (Saunders et al.
The above-mentioned analytical outcomes indicate the appropriateness of the data set for correlation and regression analysis (Zaid
To indicate the intensity of the relationship between variables, Cohen (
The relationship between the IDV of organisational control systems (IDV) and the DV of organisational resilience in a socio-technical system (DV) was tested. Also, the relationship between organisational control systems (IDV) and each of the four composite categories of the DV, namely organisational resilience (DV1, DV2, DV3 and DV4), were subjected to the same examination. Calculations from Pearson’s correlation method revealed the results reflected in
Pearson’s correlation results indicating significance.
Independent variable | Dependent variable | Significance ( |
|
---|---|---|---|
IDV: Organisational control systems | DV: Organisational resilience | 0.59 | < 0.001 |
DV1: Strategic management and company culture | 0.63 | < 0.001 | |
DV2: Monitoring and awareness | 0.51 | < 0.001 | |
DV3: Exposure management | 0.53 | < 0.001 | |
DV4: Responsive adaptation | 0.52 | < 0.001 |
IDV, independent variable; DV, dependent variable.
The results indicate a significance (
Through the same criteria, the data also indicate a >99% certainty that a statistically significant relationship exists between the IDV (organisational control systems) and each of the individual DVs, namely Strategic management and company culture (DV1), Monitoring and awareness (DV2), Exposure management (DV3) and Responsive adaptation (DV4). This not only indicates that a statistically significant relationship was identified between organisational control systems (quality assurance and corporate governance) and organisational resilience in the South African aviation industry, but it also indicates a relationship between organisational control systems (quality assurance and corporate governance) and each of the components of organisational resilience.
Following the determination that a statistically significant relationship exists between the IDV and each of the DVs, the collective data set was further examined to determine the nature of these relationships by conducting regression analysis (Zaid
The linear relationship between a combination of a DV and IDVs can be positive or negative (Joshi et al.
Nature of relationship between variables.
Independent variable | Dependent variable | Nature of correlation | Coefficient |
---|---|---|---|
IDV: Organisational control systems | DV: Organisational resilience | Positive | 0.62 |
DV1: Strategic management and company culture | Positive | 0.62 | |
DV2: Monitoring and awareness | Positive | 0.50 | |
DV3: Exposure management | Positive | 0.52 | |
DV4: Responsive adaptation | Positive | 0.49 | |
Constant coefficient | - | - | 1.62 |
IDV, independent variable; DV, dependent variable.
Through the application of analytical rules, the data revealed a positive relationship between the IDV and DV in all the variations examined (Harpe
Similarly, an increase in the behavioural measurement of organisational control systems is expected to stimulate an elevation of the measurement values for each of the components of organisational resilience (Strategic management and company culture – DV1, Monitoring and awareness – DV2, Exposure management – DV3 and Responsive adaptation – DV4). The degree of the expected change is informed by the value of the coefficient (Bonett & Wright
The predictive value of a regression model is dependent on its confidence and significance levels (Beckett et al. 2017). As a measurement of central tendency, the standard error informs the confidence level of the predictive power embedded in a regression model (Beckett et al. 2017). The confidence level (
Regression results of organisational resilience and organisational control systems.
Variable to IDV: Organisational control systems | Coefficient | Standard error | | |
Confidence interval |
|
---|---|---|---|---|---|
Lower limit | Upper limit | ||||
DV: Organisational resilience | 0.62 | 0.60 | < 0.001 | 0.50 | 0.73 |
DV: Constant coefficient | 1.62 | 0.26 | < 0.001 | 1.11 | 2.14 |
DV1: Strategic management and company culture | 0.62 | 0.54 | < 0.001 | 0.52 | 0.73 |
DV1: Constant coefficient | 1.52 | 0.24 | < 0.001 | 1.05 | 1.99 |
DV2: Monitoring and awareness | 0.50 | 0.06 | < 0.001 | 0.38 | 0.61 |
DV2: Constant coefficient | 2.13 | 0.26 | < 0.001 | 1.62 | 2.63 |
DV3: Exposure management | 0.52 | 0.60 | < 0.001 | 0.40 | 0.64 |
DV3: Constant coefficient | 2.08 | 0.25 | < 0.001 | 1.58 | 2.57 |
DV4: Responsive adaptation | 0.49 | 0.57 | < 0.001 | 0.37 | 0.60 |
DV4: Constant coefficient | 2.19 | 0.25 | < 0.001 | 1.70 | 2.68 |
IDV, independent variable; DV, dependent variable.
The
Resilience aids in managing uncertainty in a complex socio-technical system (Lee et al.
This study explored the relationship between the IDV organisational control systems (quality assurance and corporate governance) and the indicators of organisational resilience (DV) in the South African aviation industry through the perception of the stakeholder defined in
The nature of these relationships identified by correlation analysis was also examined to verify previous research that the effective application of organisational control systems autonomously promotes organisational resilience (Govuzela & Mafini
Therefore, Strategic management and company culture (DV1), Monitoring and awareness (DV2), Exposure management (DV3) and Responsive adaptation (DV4) will respectively increase in response to an improved measurement in the behaviour of organisational control systems (IDV).
Although all DVs showed a strong positive relationship between the IDVs,
This study revealed a positive linear relationship between organisational control systems (IDV) such as quality assurance and corporate governance and organisational resilience (DV) in the South African aviation industry. This confirmation is not limited to the relationship between organisational resilience (DV) and organisational control systems (IDV), but this study confirmed a relationship between organisational control systems (IDV) and each of the respective categories associated with organisational resilience, namely Strategic management and company culture (DV1), Monitoring and awareness (DV2), Exposure management (DV3) and Responsive adaptation (DV4).
Apart from identifying a statistically strong relationship between these variables, this study provided insight into the nature of these relationships. A positive linear correlation was found for each of the relationships examined. Therefore, as the effectiveness and robustness of quality assurance and corporate governance in the local aviation industry increase, the same company’s organisational resilience evolves autonomously.
The Strategic management and company culture (DV1) showed the strongest relationship with quality assurance and corporate governance. Whilst Exposure management (DV3) ranked second in the intensity of the relationships with organisational control systems, Responsive adaptation (DV4) presented itself in the third position. Although Monitoring and awareness (DV2) ranked fourth in terms of intensity of the relationship with the IDV, the intensity of this relationship is still deemed strong and statistically significant.
Whilst previous studies focussed on either a specific organisation or specific group of stakeholders, this study focussed on the South African aviation industry as a cohesive socio-technical entity and collected data from all strata of the homogenous stakeholder group as indicted in
This study further indicates the integration of organisational control procedures related to situational monitoring, exposure management and controlled adaptation into organisational and strategic planning to avoid a polarised manifestation of organisational control systems. This study shows the benefits of consciously integrating quality assurance and corporate governance within organisations to stimulate collective assurance for all stakeholders.
Therefore, it is concluded that the benefits of organisational resilience emerge from a synergy between organisational control systems such as quality assurance and corporate governance in the South African aviation industry. The robust application of these organisational control processes increases an organisation’s embedded capacity to yield favourable results, whilst autonomous adaptation to disruptions occurs. Similar to the socio-technical nature of the aviation system, a multi-disciplinary approach to pro-active excellence instead of reactive management of occurrences is necessary to ensure a robust implementation of organisational control systems.
The results of this study imply that organisations should continuously increase the robustness of quality assurance and corporate governance principles and practices. To increase organisational resilience in a complex socio-technical system, quality assurance and corporate governance should operate congruently as part of the organisation’s internal control systems. Although the organisational resilience framework consisting of Strategic management and company culture, Monitoring and awareness, Exposure management and Responsive adaptation encompasses organisational control systems (quality assurance and corporate governance), the framework shown in
Future research opportunities also exist to examine the relationship between organisational control systems and organisational resilience perpetually within a specific organisation. The statistically strong positive linear relationship between organisational control systems and organisational resilience provides insight and recommendations on adaptability in support of ongoing sustainability and growth of organisations within the South African aviation industry. The insight provided suggests integrating organisational control systems such as quality assurance and corporate governance to stimulate the embedded resilience of an organisation.
The authors wish to acknowledge the Commercial Aviation Association of Southern Africa for its assistance in the recruitment of specialist participants meeting the criteria of the study population.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
E.S. designed the project, developed the theory, the data collection instrument and performed data collection and analysis under the academic supervision of K.K.G. All authors discussed the results and contributed to the final manuscript.
This study did not receive any funding and was conducted independently from any institution apart from the academic institution, which provided ethical clearance and research supervision support.
This study generated its raw data. Derived data supporting the findings of this study are available from the corresponding author, K.K.G., upon reasonable request.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.