Developing rightly culture on TQM - evidence from SMEs in the context of emerging economy

Abstract

Purpose

Total quality management (TQM) must include orientation towards quality awareness in the overall organisational processes in a firm. A successful TQM needs a supportive culture that can adapt to alterations and strengthen innovation. This study aims to confirm the association between the style of management known as organisational culture (OC) and TQM practices in manufacturing Small and Medium Enterprises (SMEs).

Design/methodology/approach

Data-driven research was drawn from self-assessment inquiries among 772 managers/owners of manufacturing SMEs of the Saudi Arabia Kingdom (KSA). The dominant culture was detected by means of a cross-sectional technique.

Findings

The findings enrich the literature by revealing a positive effect of OC on TQM execution in the manufacturing SMEs of KSA.

Research limitations/implications

Prior to the execution of TQM operations, administrators of manufacturing SMEs should be aware of the culture within organisations so that TQM may be implemented.

Practical implications

The study suggests that organisations, particularly manufacturing SMEs, should constantly strive to enhance the TQM culture.

Social implications

Amid intense competition among manufacturing SMEs, it is crucial to guarantee their high performance. This research assists society in evaluating the strength of a particular SME sector and further enables it to assess which SMEs really have a good OC–TQM relation.

Originality/value

The paper creates and presents various platforms of the OC and TQM as a unified body of knowledge.

Citation

Gorondutse, A.H., Ali, G.A. and Hilman, H. (2021), "Developing rightly culture on TQM - evidence from SMEs in the context of emerging economy", RAUSP Management Journal, Vol. 56 No. 4, pp. 465-481. https://doi.org/10.1108/RAUSP-11-2020-0264

1. Introduction

Globally, firms face increasing pressure to apply innovative and low-cost techniques to improve products and processes to respond to customers’ needs and desires (Patyal & Koilakuntla, 2018; Ebrahimi & Sadeghi, 2013). In addition, in the past few years, establishments of different types experienced radical alterations in their operating contexts brought about by different circumstances, such as ever-increasing consumer awareness of quality, rapid technological shift, global proliferation and cheaper rivalry (Patyal & Koilakuntla, 2018). Alkhoraif and Mclaughlin (2017) asserted that lower cost, better quality and timely delivery have emerged as more significant challenges for Saudi Arabia Kingdom (KSA) small-sized businesses. Simple inspection operations have been supplemented by quality control and quality assurance ethics. In this regard, several firms are being motivated to accept and put into place new operation management procedures, such as TQM and active quality enhancement programmes to subsist in this ever-changing business atmosphere (Valmohammadi & Roshanzamir, 2015; Psomas & Antony, 2015). Firms have widely accepted TQM as a tool for achieving excellent performance (Patyal & Koilakuntla, 2018; Gambi, Boer; Gerolamo, Jørgensen, & Carpinetti, 2015). However, several studies have also reported a high rate of failures and problems in implementing TQM processes (Srinivasan & Kurey, 2014; Abdolshah & Abdolshah, 2011; Sila, 2007).

This view was supported by Valmohammadi and Roshanzamir (2015), as they indicated that a significant number of TQM have created serious problems or have failed entirely, enough to threaten an organisation’s survival. This paper shows that organisational culture (OC) and total quality management (TQM) are conventionally connected (Atuahene & Baiden, 2017), so that, to improve the quality of the small and medium enterprises (SMEs), a comprehension of OC is essential (Patyal & Koilakuntla, 2018). Furthermore, numerous studies agree that an OC which does not support TQM is a crucial reason for the failure or a barrier to the implementation of TQM (Haffar, Al-Karaghouli, Djebarni, & Gbadamosi, 2017; Kaluarachchi, 2010). This means that cultural transformation is fundamental to bring about successful operations of TQM in SMEs (Rad, 2006). Hence, there is a need for a better understanding of the role that OC plays in the successful implementation of TQM, specifically in SMEs.

In the case of Saudi SMEs, the challenge is innovation on OC and the difficulty of accepting changes among employees in various organisations (Alkhoraif & Mclaughlin, 2017; Albliwi, Antony, Arshed, & Ghadge, 2017). The fact is that the SME sector occupies a very significant position in the expansion and growth of the economy in most emerging nations due to job creation, contribution to modernisation and technological development (OECD, 2017; Rodríguez-Gutiérrez, Moreno, & Tejada, 2015). In addition, they signify more than half of the added value and employment in both the advanced and developing nations (Rodríguez-Gutiérrez et al., 2015; Valmohammadi, 2011). Like other economies, in KSA, SMEs account for almost 90% of all business initiatives, are responsible for 25% of total employment and contribute up to 20% of gross domestic product (Kingdom of Saudi Arabia, 2016; Jeddah Chamber of Commerce & Industry, 2015).

Even with the extensive literature on the link concerning OC and TQM in developing countries, the empirical research investigating the effect of OC on TQM implementation in developing and Arab countries, specifically in KSA SMEs, is relatively rare (Patyal & Koilakuntla, 2018; Ali, Abdullah, & Gorondutse, 2017). More importantly, there is a lack of studies examining the mechanics of this nexus between OC and TQM. It is indispensable for SMEs to embark on productivity and quality initiatives to be more competitive in the international market. There is an absence of organised data-driven evidence regarding the effects of OC concerning TQM application within KSA SMEs. This research aims to understand the effect of OC on successful TQM implementation, particularly in manufacturing SMEs, thus adding value to the rare body of literature about Arab countries. This research is planned as follows: Section 2 shows the literature examination and establishes the study’s hypotheses. Section 3 brings the methodology, results and analysis. Results derived from this study are discussed in the middle of Section 4. In the end, the conclusions, limitations and propositions for upcoming research studies are presented in Section 5.

2. Literature review and hypotheses

2.1 Organisational culture

In literature, OC has been mentioned as the collective definitions or assumptions, beliefs and comprehensions which are effortlessly noticeable (Cameron & Quinn, 2006). Culture addresses people matters, and thus becomes the crucial factor in effective TQM implementation (Valmohammadi & Roshanzamir, 2015). In the organisation theory, OC has become a very important subject (Sinha & Dhall, 2018). OC encompasses the group’s values, beliefs, assumptions and norms that describe an organisation and are shared by an organisation’s members (Cameron & Quinn, 2006; Schein, 1984). OC serves as a tool used by managers to shape the direction of their organisations and provides individuals with norms for behaviour in the firm (Daft & Lane, 2005; Smircich, 1983). As such, OC affects people's behaviours and decisions, the organisation’s style of work, and then enhance firm performance (Wu, Zhang, & Schroeder, 2011). OC also assists organisations in adapting both internally and externally to motivate employees, improve productivity and develop a higher impact on all functions of organisations (Deal & Kennedy, 1982). Thus, managers should build and develop OC to direct the employees’ efforts to realise the organisation’s aims (Morgan, Rapp, Richey, & Ellinger, 2014; Asree, Zain, & Rizal Razalli, 2010). This means that ignoring the effect of OC is one of the most severe obstacles to change, as it impacts the new initiatives that are to be implemented (Cameron & Quinn, 2006).

This paper uses the Competing Values Framework (CVF) introduced by Cameron and Quinn (2006). CVF has been developed in four proportions, namely, clan, adhocracy, market and hierarchy culture. This model denotes whether an entity has a major inside or outside concentration and endeavours for elasticity and individuality or stability and control. The CVF has been accepted by numerous researchers to investigate the influence of OC on different cases, such as TQM practices (Haffar, Al-Karaghouli, & Ghoneim, 2013; Sinha, Garg, Dhingra, & Dhall, 2016). Furthermore, the urgencies for performance by these cultures are the construction of human strength and possibilities, attainment of new market and properties for advancement, efficiency and proficiency and control and constancy (Hilman, Ali, & Gorondutse, 2019), correspondingly. In this case, each association reveals a mixture of diverse cultural types, although one does have the potential to supersede the other (Cameron & Quinn, 2006; Ali, Abdullah, & Gorondutse, 2019).

2.2 Total quality management

Literature reveals that numerous organisations globally have profited from the application of TQM (Kuo & Kuo, 2010). In operation management literature, the initially combined theoretical and data-driven outline of TQM as a tactical asset was provided by Powell in 1995 (Sinha & Dhall, 2018). Before that, TQM depended on case studies, concepts, practices of the recognised quality experts like Deming, Juran, Crosby, Feigenbaum and Ishikawa (Black & Porter, 1996). TQM was widely accepted as the primary key to business excellence for several organisations around the world later on (Gambi et al., 2015; Kuo & Kuo, 2010; Schein, 1984). TQM can be described as:

[…]an all-inclusive organisational thinking that endeavours for constant upgrading in all purposes of an establishment, and can be realized only if the total quality idea is used from the attainment of assets to customer service after the sale (Ali et al., 2020).

Similarly, according to Powell (1995), TQM is organisational thinking that supports organisations to achieve a wide range of benefits, such as greater employee commitment and motivation, better inside communication, improved solution-providing, comprehension of consumer’s needs, improved fulfilment of customer, more solid dealings with contractors, waste reduction and fewer errors. This definition is in line with Wang, Chen, and Chen (2012), who defined TQM as an organisational technique that emphasises unceasing upgrading inside firms to achieve the needs of consumers and provide greater purchaser worth. Accordingly, process management of practice can support continuous improvement in the QM principle, which includes many tools, such as Pareto analysis and statistical process control (Sousa & Voss, 2002). Previous studies have also widely recognised that OC occupies a major position in the success of TQM implementation (Sinha & Dhall, 2018; Haffar et al., 2017; Hilman et al., 2019). TQM work recognises an all-inclusive list of quality management norms, specifically, top management leadership, process management, human resource management, quality information and communication and customer and supplier relationship management (Haffar et al., 2017; Talib, Ali, & Idris, 2014). The operative application of TQM in the building sector can be achieved by combining these quality management activities. Consequently, in this research, six frequently used practices of applying TQM are considered.

Various scholars have endeavoured to identify TQM practices (Talib et al., 2014; Sadikoglu & Zehir, 2010; Sila & Ebrahimpour, 2002; Black & Porter, 1996; Ali et al., 2019). In this regard, all TQM practices are currently in the frameworks applied in the national quality awards, such as European Foundation for Quality Management, Malcolm Baldrige National Quality Award (MBNQA), Deming Prize and also in ISO-9000 quality certification (Amin, Aldakhil, Wu, Rezaei, & Cobanoglu, 2017; Ali et al., 2019). The present study used the MBNQA model performance excellence conditions to recognise six TQM practices to examine the implementation of TQM in KSA SMEs’ context. More importantly, authors in operations management have linked cultural beliefs and values and perform of operations management, such as TQM and manufacturing strategy (Flynn & Saladin, 2006; Bates, Amundson, Schroeder, & Morris, 1995). Many studies confirm the vital role of OC; hence, additional investigation of the link concerning OC and TQM in developing countries is required.

2.3 Relationship between organisational culture and total quality management

Culture occupies an important position in the positive application of quality management plans within an organisation. As OC produces an organisational climate, it impacts quality management practices to back excellence enhancement proposals (Haffar et al., 2013; Prajogo & McDermott, 2005). The existing literature reveals several novel problems linking to the process of TQM implementation and how they impact its results (Valmohammadi & Roshanzamir, 2015). OC is considered an essential factor for the successful implementation of TQM; in fact, is among the factors listed at the top (Baird, Jia Hu, & Reeve, 2011; Prajogo & McDermott, 2005). That means unsupportive OC is a major barrier to the failures in the practicability of TQM (Haffar et al., 2013; Rad, 2006). Within a firm, making a critical culture change to correspond to TQM is a key requirement for the positive application of TQM (Rad, 2006). As reported by Quinn and Cameron (1999), TQM ideas did not work in organisations as a result of two major reasons: partial publishing of TQM activities and failure to incorporate TQM and culture change. In this regard, within the range of 20% to 35% of the organisations that have implemented TQM achieved competitiveness because of a lack of comprehending the fitness of OC (Rad, 2006).

In the TQM domain, literature indicates that a positive link exists between OC and TQM (Valmohammadi & Roshanzamir, 2015; Hilman et al., 2019; Ali et al., 2019). However, Panuwatwanich and Nguyen (2017) found that both market and hierarchy cultures could not offer a likeable atmosphere for positive TQM application. Furthermore, Gimenez-Espin, Jiménez-Jiménez, and Martínez-Costa (2013) revealed that activities related to clusters, growth and diverse cultures have a significant impact on TQM applications, while pecking order and coherent cultures give contrary results. Conversely, research by Zu, Robbins, and Fredendall (2010) encouraged that cluster and coherent cultures had a positive impact on TQM activities, while development and hierarchical cultures were revealed not to have associations with TQM practices (Hilman et al., 2019; Soares & Perin, 2019; Ali et al., 2019). On the other hand, the same does not happen with those subsumed by both clan and adhocracy cultures. This research determines the strength of OC as a driver of “fertile soil” and its influence on TQM. That means it is important to balance and incorporate all types of culture, and that no cultural types are more significant than the others (Giritli, Öney-Yazıcı, Topçu-Oraz, & Acar, 2013; Denison & Spreitzer, 1991). Therefore, the following study hypothesis is posited:

H1.

OC positively influences TQM in manufacturing SMEs.

3. Material methods

3.1 Research design

This paper used a quantitative approach to estimate the relationship between OC (market, adhocracy, clan and hierarchy) and TQM (customer focus, leadership, human resource management, strategic planning, process management and information analysis), as Figure 1 shows:

3.2 Population and sample

Data collection was carried out using self-administered questionnaires to manufacturing SMEs managers/providers in Riyadh, Mecca and Eastern KSA. The population during the research was 5,820 (Ministry of Commerce & Investment, 2016) and Krejcie and Morgan (1970) guide to achieving the sample size in this context was 361. We used a cross-sectional design technique for the survey. Data collection was performed at a specific point in time (six months in 2017) and the calculated sample size was doubled to reduce errors and non-response problems (Hair, Celsi, Ortinau, & Bush, 2008). Therefore, 722 was the total number of questionnaires administered.

3.3 Common method bias and non-response bias

As self-reported questionnaires were used to collect data, they were tested for common method bias-variance, particularly necessary when both the predictor and criterion variables are obtained from the same person (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). In this case, Podsakoff and Todor (1985, p. 65) warned that: “Invariably, when self-reported measures obtained from the same sample are applied in research, concerns over same-source bias or general method variance arise”. To tackle this issue, the paper used Harman 1-factor on the three constructs for detecting common method variance bias (CMV); the first factor only explained 40.95% of the variance, so CMV is not a relevant problem in this study. Furthermore, to estimate the existence of the non-response bias in the data, a t-test was used to test the statistical difference between the early and delayed responses. Test results showed that no significant values were higher than 0.05, which indicates that the variances were presumed to be approximately impartial. Consequently, no substantial dissimilarities exist between the two groups (early and late respondents) in terms of all the variables under investigation (p < 0.05). Moreover, the issue of non-response bias was absent, and the samples obtained represented the total population of the study (Pallant, 2010; Armstrong & Overton, 1977).

3.4 Measures

In this paper, the OC instrument was adapted from Cameron and Quinn (2006). It contains 24 items in a one-dimensional array, and numerous scholars have confirmed the apparatus alias instrument and have established its reliability and validity (Hilman et al., 2019; Ali et al., 2019; Haffar et al., 2017; Hilman et al., 2019; Ali et al., 2019). The paper used a seven-point Likert-type scale starting from “strongly disagree (=1)” up to “strongly agree (=7)” to measure the instruments. The TQM actions come about by measurement using the six criteria of the MBNQA, which have earlier been widely used in numerous findings for TQM application of measuring (Hilman et al., 2019; Ail et al., 2019; Haffar et al., 2017; Ali et al., 2019; Lam, Lee, Ooi, & Lin, 2011; Prajogo & Hong, 2008). The study adapted measurement 36 items for TQM as a single entity from the research works done by Samson & Terziovski, 1999; Wang et al., 2012; Prajogo & Sohal, 2006. These items have a good theoretical foundation and a strong indication of construct reliability and validity (Ail et al., 2019; Haffar et al., 2017: Ng, Zhao, Fan, & Rungtusanatham, 2014). To estimate the suggested model, the partial least square-structural equation model (PLS-SEM) was used to create the measurements’ validity and reliability and examine the assumed hypothesis as described in the subsequent segments.

4. Data analysis

To test the PLS path models, this research used Chin’s (1998) suggestions. The PLS model is tested and explained in two steps: firstly, the measurement model evaluation reliability and validity are tested prior to hypotheses testing (Hair, Black, Babin, Andersen, & Tatham, 2010). Secondly, the structural model (SM) evaluation (R² and predicative relevance of the model) was conducted after bootstrapping to confirm the research hypothesis.

4.1 Measurement model

The measurement model (MM) was evaluated through construct validity, content validity and discriminant validity as explained in the following sections.

4.2 Construct validity

Construct validity denotes how outcomes gained from appropriate theories measure the test calculated (Sekaran & Bougie, 2016). The MM content validity can be achieved by paying attention to items like factor loading (Hair et al., 2013). Here, items should be larger than the hypothesized construct and other constructs (Chin, 2010). For that purpose, if items load is larger than their own construct, then the items will be removed (Hair et al., 2013). The significant cut-off threshold for this study is 0.7 (Hair, Hult, Ringle, & Sarstedt, 2014). As illustrated in Table 1 below, all the items loaded are larger and more substantial on their hypothesized factor than on other factors, consequently confirming the content validity of the MM.

4.3 Convergent validity

In this section, convergent validity with multiple items that relate to the same idea are in consonance and referred to as CV (Ramayah, Lee, & In, 2011). Hair et al. (2010) reported that this can be established by testing the factor loadings, average variance extracted (AVE), composite reliability (CR) and approximate convergence validity. Thus, the factor loadings of all items surpassed the suggestion value of 0.7 (Hilman et al., 2019; Hair et al., 2014). Furthermore, all alpha coefficients, CR and AVEs are better than the cut-off values and characters 0.7 and 0.5 correspondingly (Hilman et al., 2019; Hair et al., 2014) as shown in Table 1. Thus, all constructs are in line with the threshold value and were reflected to have met the average endorsed for convergent validity.

4.4 Discriminant validity

Discriminant validity is evaluated by calculating the square root of the AVE as recommended by Hair et al. (2014) and Fornell and Larcker (1981). Based on the latter, the square root of the AVE is personified on the diagonal line in the construct correlation matrix and should be greater than the off-diagonal elements in the corresponding rows and columns (Ali et al., 2019). In the results shown in Table 2, all the square roots of the AVE characters surpassed within its own rows and columns, suggesting the discriminant validity can be thus confirmed in the current study.

4.5 Structural model evaluation

After confirming the validity and reliability of the MM, our study followed by analysing the hypothesized association via the PLS algorithms and bootstrapping in Smart PLS 3.2.7 (the results of this analysis can be seen in Figure 2 and Table 3). As suggested by Hair et al. (2014), the average for the estimation of the SM is the R², as the objective of the prediction-oriented PLS-SEM method is to illustrate the dependent latent variables’ discrepancy, thus R² as one of the essential purpose variables has to be substantial. In line with Hair et al. (2017); Hilman et al. (2019), in management research, the R² value can be thus categorised: 0.75, 0.50, 0.25 as substantial, moderate and weak, respectively. Based on this research, after PLS algorithm analysis R² was revealed to be 0.473, signifying that OC accounted for 47.3% of the variance in TQM, which is between weak and moderate.

For assessing the model, the blindfolding method was used (Henseler, Ringle, & Sinkovics, 2009). When the blindfolding approach is used to obtain the Q2, the cases amount in the raw fact must not be a multiple numbers of the oversight coldness d or else the blindfolding method would be incorrect, and a number from 5 to 10 should be selected (Hair et al., 2014). Therefore, we chose 9 as the number of the d to govern the cross-validated redundancy actions for every endogenous factor. Following the recommendations by Hilman et al. (2019) and Hair et al. (2017), the result of this research reports a predictive quality if the cross-redundancy value is more than zero; if not, the predictive relevance of the model may not be concluded. As presented in Table 3, the results showed that the cross-validated redundancy for TQM was found to be 0.223.

The final step in the SM enquiry also involves evaluating the path coefficients that explain the powers of the connection between the independent variable (IV) and dependent variable (DV). The final step in the SM assessment also involves evaluating the path coefficients, which simplify the power of the connection in respect to the IV and DV. Based on the suggestion by Hilman et al. (2019) and Hair et al. (2014), this research used 5,000 samples. Table 4 includes the path coefficients and bootstrapping results.

5. Discussion

OC is among the most important intangible resources that can assist an organisation to bring about the competitive edge, thus differentiating the firm from its competitors (Barney, 1986). This is a critical factor for the organisation, helping with the implementation of business stratagems. TQM is a management philosophy covering all the business operations and pursues advancing quality in all organisational procedures (Gimenez-Espin et al., 2013). That means OC can facilitate the successful implementation of TQM (Hilman et al., 2019; Sinha & Dhall, 2018; Ali et al., 2017; Haffar et al., 2017). Founded on the conceptual model verified and reinforced in this research, we contend that OC may improve and provide the appropriate environment to implement TQM in any firm, improving performance. To the authors’ knowledge, this study represents the first data-driven research to examine the effect of OC on TQM in the context of Saudi SMEs manufacturing.

The statistical results indicated that the assumed study hypothesis was supported and sustained. In particular, a significant and positive association between OC and TQM was confirmed at the 0.001 level of significance (b = 0.688, t = 15.172), see Table 4. This research result is consistent with the findings of preceding studies obtained by Ali et al. (2019), Sinha and Dhall (2018), Valmohammadi and Roshanzamir (2015), Gimenez-Espin et al. (2013), Haffar et al. (2013) and Baird et al. (2011). A preponderance of empirical studies tends to concentrate on the relationship between OC and TQM in big organisations, especially in developed economies. This study produces an exclusive contribution to the existing literature by authenticating the impacts of OC on TQM in the framework of manufacturing SMEs in a developing country, such as KSA, where SMEs function in comparatively more explosive atmospheres with high reservations.

Meanwhile, a firm should operate towards modifying current OC so that it can be more amenable to proactivity, risk forward-thinking and accept new strategies, such as TQM practices (Leavengood, Anderson, & Daim, 2014). Furthermore, to create a supportive OC that leads to continuous improvement where all employees can contribute and disseminate quality assurance in all organisational operations; which, in turn, will be conducive to the successful implementation of TQM (Hilman et al., 2019; Ali et al., 2019; Sinha & Dhall, 2018).

6. Theoretical implications

This research adds meaningful knowledge to the body of literature in several ways. Firstly, this study will become a body of reference for the manufacturing SMEs in an emerging country, such as KSA and government agencies for the promulgation of guidelines, promotion and application of suitable OC. Subsequently, the outcomes of this research may help improve the theory of OC and TQM implementation in the background of manufacturing SMEs. Finally, the results of the study are deemed to present a significant contribution to the TQM field.

6.1 Managerial implications

In the KSA, SMEs are facing competitive pressures in the local market to survive; they need to improve their product quality standards. This result supports the successful implementation of TQM. To accept the implementation of a change process like TQM in KSA manufacturing SMEs, owners/managers must understand the sequence of the influence of OC and make sure their workers accept the change process. In this case, administrators should avoid hierarchical or bureaucratic management because it does not lead to the successful execution of TQM. On the contrary, administrators of SMEs must concentrate on democratic management and flexible policies and regulations to encourage firm members to be innovative and creative to improve TQM, and thus increase the effectiveness of their organisation. More importantly, SMEs should create and develop a supportive OC as a fertile environment to prepare employees to accept change and then commit to TQM implementation. Therefore, the findings acquired from the current research would assist KSA manufacturing SMEs to align their TQM interventions with their respective OC adequately.

6.2 Limitations and future research

As in other data-driven studies, the present research has its limitations and the results here should be deliberated accordingly to give a chance for future studies. Firstly, this study used a survey design with cross-sectional data, where data were collected at one single point in time. Hence, data acquired only indicate the degree of linkage between variables; while the causal associations are inferred regarding the findings gained, it cannot be strictly ascertained. A comprehensive review revealed that changes in OC or implementation of TQM are long term processes, which is sometimes difficult and slow (Gimenez-Espin et al., 2013). Therefore, to analyse changes in the OC of the organisation over time, to assist in successful TQM implementation, this research suggests that a longitudinal study should be considered. The second limitation is linked to the generalisability of the results in this research. Due to the fact that the current research was conducted in manufacturing SMEs, the results may not be generalisable to other industries. To raise the external validity of the results, future studies should consider other climes, specifically in-service companies and other developing countries, such as Kuwait, Bahrain, Egypt and Yemen for the sake of comparison. Finally, the present research only investigated the associations between OC and TQM. Upcoming work of research should examine other constructs that may affect OC–TQM implementation relationships.

Figures

Figure 1.

Research framework

Figure 2.

Results for the proposal model

Table 1.

Convergent validity

Constructs	Items	Factor loadings	Cronbach’s alpha	Composite reliability (CR)	Average variance extracted (AVE)
OC	Clc1	0.852	0.921	0.939	0.719
(organisational culture)	Clc2	0.881
	Clc3	0.865
	Clc4	0.879
	Clc5	0.829
	Clc6	0.778
	Adc7	0.802	0.920	0.938	0.715
	Adc8	0.862
	Adc9	0.886
	Adc10	0.882
	Adc11	0.834
	Adc12	0.804
	Mac13	0.768	0.897	0.921	0.662
	Mac14	0.828
	Mac15	0.846
	Mac16	0.852
	Mac17	0.847
	Mac18	0.736
	Hic19	0.781	0.907	0.928	0.683
	Hic20	0.827
	Hic21	0.860
	Hic22	0.858
	Hic23	0.839
	Hic14	0.791
TQM (total quality management)	Lep1	0.888	0.949	0.959	0.798
	Lep2	0.912
	Lep3	0.918
	Lep4	0.902
	Lep5	0.883
	Lep6	0.856
	Cuf7	0.824	0.938	0.951	0.764
	Cuf8	0.889
	Cuf9	0.895
	Cuf10	0.905
	Cuf11	0.883
	Cuf12	0.847
	Stp13	0.828	0.918	0.937	0.713
	Stp14	0.864
	Stp15	0.898
	Stp16	0.890
	Stp17	0.844
	Stp18	0.732
	Hrs19	0.816	0.920	0.938	0.715
	Hrs20	0.846
	Hrs21	0.873
	Hrs22	0.880
	Hrs23	0.873
	Hrs24	0.781
	Ina25	0.819	0.938	0.950	0.730
	Ina26	0.861
	Ina27	0.856
	Ina28	0.877
	Ina29	0.872
	Ina30	0.861
	Ina31	0.835
	Prm32	0.842	0.921	0.941	0.761
	Prm33	0.894
	Prm34	0.900
	Prm35	0.893
	Prm36	0.832

Notes:

Lep = leadership; Cuf = customer focus; Stp = strategic planning; Hrs = human rescuer management; Inf = information and analysis; Prm= process management; Clc= clan culture; Adc = adhocracy culture; Mac = market culture; Hic = hierarchy culture

Table 2.

Discriminant validity

Constructs	Adc	Clc	Cuf	Hic	Hrs	Ina	Lep	Mac	Prm	Stp
Adc	0.846
Clc	0.541	0.848
Cuf	0.424	0.433	0.874
Hic	0.528	0.455	0.485	0.827
Hrs	0.452	0.388	0.605	0.464	0.846
Ina	0.442	0.442	0.641	0.536	0.597	0.854
Lep	0.466	0.425	0.674	0.496	0.596	0.592	0.893
Mac	0.522	0.420	0.428	0.581	0.391	0.399	0.384	0.814
Prm	0.488	0.409	0.556	0.499	0.540	0.612	0.604	0.406	0.872
Stp	0.492	0.489	0.658	0.502	0.666	0.636	0.588	0.425	0.575	0.844

Table 3.

Predictive relevance of the model

Total	SSO	SSE	1 – SSE/SSO
TQM	13,104	10,184.4	0.223

Table 4.

Hypothesis test results

Hypotheses	Path coefficient	Standard error	t. statistic	p. value	Results
OC -> TQM	0.688	0.045	15.172	0.000	Supported

Author contributions are as follows:

Gorondutse, Abdullahi Hassan – Conceptualization (Supporting). Data curation (Supporting). Formal analysis (Lead). Funding acquisition (Equal). Investigation (Supporting). Methodology (Lead). Project administration (Equal). Resources (Equal). Software (Lead). Supervision (Supporting). Validation (Supporting). Visualization (Lead). Writing-original draft (Supporting). Writing-review & editing (Lead). Hilman, Haim – Conceptualization (Supporting). Data curation (Equal). Formal analysis (Equal). Funding acquisition (Equal). Investigation (Lead). Methodology (Supporting). Project administration (Supporting). Resources (Equal). Software (Supporting). Supervision (Lead). Validation (Lead). Visualization (Equal). Writing-original draft (Supporting). Writing-review and editing (Equal). Ali, Gamal Abdualmajed – Conceptualization (Lead). Data curation (Lead). Formal analysis (Supporting). Funding acquisition (Equal). Investigation (Lead). Methodology (Supporting). Project administration (Equal). Resources (Equal). Software (Supporting). Supervision (Supporting). Validation (Equal). Visualization (Equal). Writing-original draft (Lead). Writing-review and editing (Equal).