Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Contents lists available at ScienceDirect Int J Production Economics journal homepage: www.elsevier.com/locate/ijpe The impact of hard and soft quality management on quality and innovation performance: An empirical study$ Jing Zeng a,n, Chi Anh Phan b, Yoshiki Matsui c a International Graduate School of Social Sciences, Yokohama National University, 79-4 Tokiwadai, Hodogaya-ku, Yokohama 240-8501, Japan University of Economics and Business – Vietnam National University, Hanoi 144 Xuan Thuy, Cau Giay, Hanoi, Vietnam c Department of Business Administration, Yokohama National University, 79-4 Tokiwadai, Hodogaya-ku, Yokohama 240-8501, Japan b art ic l e i nf o a b s t r a c t Article history: Received 17 June 2014 Accepted July 2014 This study examines the conflicting relationship between quality management (QM) and innovation on a global basis using a multidimensional view of QM QM is divided into two dimensions: hard QM and soft QM Quality performance as an intended consequence of QM implementation is also examined as a potential mediator between QM and innovation A conceptual framework is developed to postulate causal linkages between soft/hard QM, quality performance, and innovation performance Data collected from 283 plants in eight countries and a technique of structural equation modeling are used to test this framework The results indicate different paths to innovation from different dimensions of QM Hard QM affects innovation performance directly and indirectly through its effect on quality performance Soft QM has indirect effect on innovation performance through its effect on hard QM This means that quality performance depends directly on hard QM which can be promoted by soft QM Quality performance shows a partial mediating effect on the relationship between hard QM and innovation performance Quality and innovation are not a matter of trade-off, but they can coexist in a cumulative improvement model with quality as a foundation Firms have no need to abandon QM endeavor to achieve innovation Instead, they should devote continuous efforts to maintain a solid quality system in place integrating a set of QM practices and corresponding performance measures Managers are advised to emphasize on quality control tools and techniques and use teamwork, training, employee empowerment and problemsolving approaches as an underlying support & 2014 Elsevier B.V All rights reserved Keywords: Soft QM Hard QM Quality performance Innovation Introduction In the more and more competitive marketplace, both quality and innovation are playing crucial roles in securing a sustainable competitive advantage Quality-based competition is regarded more as an “order qualifier” criterion, while competition based on flexibility, responsiveness and particularly innovation is viewed as one of “order winner criteria” (Tidd et al., 1997) To survive in a dynamic environment, organizations need to be ambidextrous – ☆ This article was selected from papers presented at the 4th World Conference on Production and Operations Management (P&OM Amsterdam 2012), co-organized by the European Operations Management Association (EurOMA), The Production and Operations Management Society (POMS) and the Japanese Operations Management and Strategy Association (JOMSA) The original paper has followed the standard review process for the International Journal of Production Economics The process was managed by Jose A.D Machuca (POMS-EurOMA) and Andreas Groessler (EurOMA) and supervised by Bart L MacCarthy (IJPE Editor, Europe) n Correspondence to: 20-402, 1500 Kamisugeta-cho, Hodogaya-ku, Yokohama, 2400051, Japan Tel.: ỵ 81 453393734 E-mail addresses: zengzx1028@yahoo.co.jp (J Zeng), anhpc@yahoo.com (C Anh Phan), ymatsui@ynu.ac.jp (Y Matsui) aligned and efficient in managing today's market demands, while adaptive enough to environmental changes coming tomorrow (Gibson and Birkinshaw, 2004) However, this does not seem to be an easy thing, as manifested by Toyota's recall crisis In the early 1990s, Toyota has earned itself the reputation for an amazing and unprecedented record of quality Later, Toyota tried to move toward innovation by developing core technology, pathbreaking vehicles and new routines of product development for 21st century (Nonaka and Peltokorpi, 2009) In 1997, Toyota launched the world's first commercialized hybrid car — Prius, which received numerous awards and orders However, “Toyota's reputation for quality was tarnished by massive global recalls that started five years ago and ultimately encompassed almost every model in its lineup and totaled more than 10 million vehicles” (The Associated Press, 2013) Why does a firm with a strong quality focus have so many quality issues in such a short amount of time? Is it just because Toyota did not strongly focus on quality issues while pursuing innovation? Or, is any attempt to achieve both quality and innovation doomed to fail? The recent Toyota crisis leads us to rethink about quality management (QM)'s value and role in securing other competitive http://dx.doi.org/10.1016/j.ijpe.2014.07.006 0925-5273/& 2014 Elsevier B.V All rights reserved Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ advantages, particularly innovation, in future competitive environment A practical management issue emerged: Does QM foster or hinder innovation? However, literature on this issue fails to provide a clear answer to this question since there are conflicting arguments pertaining to the relationship between QM and innovation (Prajogo and Sohal, 2001) Furthermore, there are only a few empirical attempts to test this relationship Some studies use an integrated approach to consider QM as one single factor influencing innovation and empirically found the relationship between them to be positive (Sadikoglu and Zehir, 2010; SantosVijande and Álvarez-González, 2007; Prajogo and Sohal, 2003) Some studies analyze this issue in more depth by considering multidimensional aspects of QM (Prajogo and Sohal, 2004; Feng et al., 2006), but their scope is usually restricted to a specific region (e.g Australia, Singapore) Martínez-Costa and Martínez-Lorente (2008) suggest that more studies are needed to analyze which QM dimensions have more effect on innovation and whether some of them could be a barrier to it Following the suggestion, this study adopts a multidimensional view of QM to examine the impact of QM implementation on innovation performance in a more extensive context across eight countries Previous literature on QM has proposed different dimensions embodied by QM As noted by Wilkinson (1992), the “hard” aspect of QM involves a range of production techniques, such as statistical process control and quality function deployment, reflecting the production orientation of the QM gurus The “soft” aspect of QM is more concerned with the establishment of customer awareness and the management of human resources Following this classification, we view QM from two dimensions, hard QM and soft QM, and use this view to solve the dispute over the relationship between QM and innovation Nevertheless, the literature on quality has dispute over the relationships between these two dimensions of QM and their contribution to performance It presents mixed results regarding whether soft QM has a direct or indirect impact on performance, and which dimension is more important to yield superior performance Since our paper is grounded on the dichotomy view of QM, clarifying the relationship between hard QM and soft QM in linking them to quality performance is the prerequisite for further investigation on the QM–innovation relationship These opposing arguments also extend to the relationship between quality performance and innovation performance A fundamental question remains about whether organizations can excel in both types of performance or have to achieve one at the expense of the other Empirical studies have rarely investigated the mediating effect of quality performance on the relationship between QM practices and innovation performance To further explore the direct and indirect relationship between quality and innovation, we examine the relationship between quality performance and innovation performance In this paper, we particularly focus on product innovation, whose relationship with QM is more controversial and ambiguous, compared to process innovation, which is closely linked to QM's concept of streamlining a process Above all, the purpose of this study is to empirically examine the relationships between two dimensions of QM (hard QM and soft QM) and quality/innovation performance on a global basis It aims to answer the following questions: How does hard QM relate to soft QM? How does hard/soft QM relate to quality performance? How does hard/soft QM relate to innovation performance? How does quality performance relate to innovation performance? A conceptual framework is developed in this study to postulate causal linkages across hard/soft QM, quality performance, and innovation performance This framework is examined at the operational level, as Flynn et al (1994) have noted that QM is not always implemented at the firm level, but the plant level is the level at which QM is often implemented Data for this study were collected from 283 plants in eight countries across three industries and the framework is tested using structural equation modeling (SEM) The findings indicate that, in general, QM can provide a fertile environment to foster innovation The results also suggest the different ways of different dimensions of QM to affect innovation Our study contributes to a multidimensional view of QM in exploring different paths to innovation from different dimensions of QM Also, by using a sample of eight industrialized countries, this study contributes to the generalization of the positive relationship between QM and innovation Furthermore, the results regarding the different ways of different dimensions of QM to affect innovation can provide guidance for the organizations to adjust hard and soft QM to meet the quality and innovation needs The remainder of this paper is organized as follows In the next section, we provide a literature review on the relationship between QM and innovation, which helps develop the research hypotheses We then describe the research methodology, followed by presenting the results of hypotheses testing Section five discusses the main findings and implications stemming from this research Section six includes limitations of this study and future research Finally, the conclusions are summarized in the last section Literature review and hypothesis development This section includes a brief review of the literature that has examined relationships between QM and innovation as well as the two dimensions of QM Following the literature review, we formulate our hypotheses 2.1 QM–innovation relationship There are conflicting arguments about the relationship between QM and innovation (Prajogo and Sohal, 2001) One group of arguments claims that philosophy and principles of QM are not compatible with innovation QM advocates the philosophy of continuous improvement which aims at simplifying or streamlining a process Continuous improvement focuses on incremental change and requires standardization or formalization in order to establish control and stability (Imai, 1986; Jha et al., 1996) This would yield rigidity and inhibit innovation by trapping people into focusing on the details of the current quality process rather than a new idea to change the current work system (Morgan, 1993; Glynn, 1996) Process management practices basically aiming at eliminating waste and improving efficiency could be detrimental to innovation, since it reduces slack resources that are necessary for fertilizing innovation (Sadikoglu and Zehir, 2010) Bennett and Cooper (1981) and Slater and Narver (1998) have criticized the customer focus itself as a source of innovation These authors contend that customer focus could lead organization “narrowminded” to current product and services rather than making breakthrough improvements to explore customers' latent needs However, positive viewpoint contends that companies embracing QM in their system and culture can provide a fertile environment for innovation McAdam et al (1998) argue that “in many ways QM can be seen as laying the foundation of a culture environment that encourages innovation” (p 141) Pfeifer et al (1998) propose three subject areas of importance for innovation: customer orientation and service; flexible organizational structures; and creative staff, which are in agreement with the QM Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ principles QM advocates customer focus which also highlights the importance of delighting customers Thus focusing on customers can stimulate companies to search for new customer needs and be creative beyond simply conforming to standards (Prajogo and Sohal, 2001; 2003) The implementation of QM would result in changes in the organizational structure, making it flexible (Forza, 1996), which would yield a beneficial effect on innovation QM promotes employee empowerment, involvement and teamwork, which is highly linked to workers' autonomy and knowledge transfer The literature has highlighted the important role of teamwork (Humble and Jones, 1989), workers' autonomy (Spreitzer, 1995), and knowledge transfer (Molina et al., 2007) in nurturing innovation Imai (1986) maintains that continuous improvement is needed to sustain the benefits resulting from innovation The concepts of QM such as formalization and empowerment can create the necessary balance between autonomy, discipline and underlying control, which provides a solid basis for the development of gradual innovations and eventually radical innovations (Santos-Vijande and Álvarez-González, 2007) These opposing arguments also extend to the relationship between quality performance and innovation performance, making the QM–innovation relationship more ambiguous The conventional wisdom has been that fast product innovation and quality represent a trade-off (Flynn, 1994) This model suggests that an improvement in one measure of performance necessitates a decrease in another and thus firms cannot achieve high levels of performance for multiple competitive priorities simultaneously However, the cumulative or “sandcone” model (Ferdows and de Meyer, 1990) argues that firms are able to improve multiple dimensions of performance concurrently because the improvements reinforce each other in a cumulative fashion Some researchers such as Leong et al (1990), Corbett and Van Wassenhove (1993), and Noble (1995) have positioned innovation performance as the ultimate apex of the pyramid in the sandcone model, arguing that the achievement of innovativeness is built upon the cumulative effect of improvement on other types of manufacturing performance including quality performance This confusion needs to be clarified, since improving quality performance is the fundamental driver for firms to implement QM practices Also, understanding the relationship between quality performance and innovation performance would help us explore the possible mediating effect of quality performance on the relationship between QM practices and innovation performance, which is rarely considered by previous empirical studies Sadikoglu and Zehir (2010) point out that few empirical studies have investigated the mediating effect of one type of performance on the relationship between QM practices and another type of performance In this paper, we include the examination on the relationship between quality performance and innovation performance to fill such a gap and provide further insight on the ambiguous QM–innovation relationship Despite the ongoing arguments above, the empirical studies which investigate the relationship between QM and innovation are rather limited, and researchers have reported mixed results The seminal work by Flynn (1994) reports on the relationship between QM and the speed of product innovation The findings demonstrate that quality foundation and organizational infrastructure can support fast product innovation McAdam et al (1998) compare QM (presented by continuous improvement) to innovation in 15 companies in Ireland, finding a significant and strong correlation between continuous improvement and innovation They argue that such a strong correlation in fact indicates a causal relationship where the introduction of continuous improvement over a period of time would lead to innovation Prajogo and Sohal (2003), based on a sample of Australian firms, found a positive relationship between QM and innovation performance However, Singh and Smith (2004), with a wider sample of Australian manufacturing organizations, could not find a strong link between QM and innovation Perdomo-Ortiz et al (2006) identify three QM practices (process management, product design, and human resource management) standing out for the establishment of business innovation capability However, the empirical findings by Kim et al (2012) highlight the critical role of process management through which a set of interlocked QM practices positively relates to each type of innovation (e.g radical product innovation, incremental product innovation) Empirical studies such as Martínez-Costa and Martínez-Lorente (2008), Santos-Vijande and Álvarez-González (2007), and Sadikoglu and Zehir (2010) all analyze the overall impact of QM and innovation and found a positive result Abrunhosa and Sá (2008) argue that the overall impact of QM and innovation is difficult to generalize, since QM is a complex management philosophy encompassing both “hard” and “soft” elements, which may lead to contrasting results in association with innovation We consider that a study which analyzes the different dimensions of QM (hard versus soft) in linking to innovation would provide more insight in explaining the ambiguous relationship between QM and innovation Another drawback of the previous empirical studies on the QM–innovation relationship reviewed above is the restricted scope to a specific geographical region, such as US, Spain, Turkey, Australia, and Canada Empirical evidence based on a wider sample beyond a specific region would add more knowledge about the QM–innovation relationship In this paper, we will look into the hard and soft dimensions of QM and investigate their impact on innovation respectively with a global sample From a managerial perspective, firms can perceive quality improvement, especially in product, more as a way to achieve strategic needs of gaining knowledge than as a way to satisfy the needs of obtaining efficiency and effectiveness Mazzola and Perrone (2013) provide empirical evidence that “improving product quality” is closely related to the strategic needs aiming at gaining knowledge This is because improvement in quality requires firms to increase their technological knowledge and their ability to understand and solve customers' problems This knowledge and learning capability can be then used to build superior new product development capability, leading to improved innovation output 2.2 Hard QM and soft QM Martínez-Costa and Martínez-Lorente (2008) argue that a possible explanation of the contrary effect of QM on innovation would be the different ways of QM implementation in a firm by focusing more on hard aspects or more on soft aspects of QM The multidimensional view of QM has emerged in recent literature as a promising approach to resolve the debate regarding the relationship between QM and innovation Prajogo and Sohal (2004) divide QM into two dimensions: mechanistic (customer focus and process management) and organic (leadership and people management) dimensions Their results based on an Australian sample indicate that the hard aspect of QM which is more mechanistic favors quality performance, whilst the soft aspect of QM which is more organic positively relates to innovation performance A replicated study conducted by Feng et al (2006) in Singapore confirms the conclusion However, including customer focus into the mechanistic dimension of QM has been questioned by Martínez-Costa and Martínez-Lorente (2008) who argue that customer focus has traditionally been considered to be one of the “intangible” elements of QM which is more soft (Anderson and Sohal, 1999; Dow et al., 1999; Samson and Terziovski, 1999) Martínez-Costa and Martínez-Lorente (2008) suggest that more Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ studies are needed to analyze the relationship between QM and innovation in more depth using a multidimensional view of QM QM literature has revealed the existence of different dimensions of QM Wilkinson (1992) maintains that QM has both “hard” and “soft” sides Hard QM pertains to the technical aspects of QM, whereas soft QM relates to the social/behavioral attributes of QM Flynn et al (1995) advocate that QM practices can be divided into two interdependent groups: core quality management practices such as process flow management, product design process, and statistical control and feedback, and quality management infrastructure practices which are broadly defined in terms of customer relationship, supplier relationship, work attitudes, workforce management and top management support Ho et al (2001) follow this concept and conclude that core QM practices completely mediate the effect of supportive QM practices on quality performance Kochan et al (1995) argue there are two ways of implementing QM – one approach conceptualizes QM as a relatively limited set of technical engineering changes while the second implements these technical changes as part of broader changes to human resource practices Forza (1995) examines the QM system from a dichotomy view: QM practices (e.g quality continuous improvement, process control) and the supporting information system including quality information flows and information technologies for quality, and demonstrates the interdependence between them Sitkin et al (1994) argue the existence of two different orientations of QM: TQC (Total Quality Control) and TQL (Total Quality Learning), with TQC focusing on cybernetic control system and TQL facilitating sharing of knowledge and skills Rahman and Bullock (2005) distinguish hard QM, which is tool/ technique oriented, from soft QM, which is essentially dimension of human resource management Their results show a partial mediating effect of hard QM on the relationship between soft QM and performance Though the labels and the coverage of the two dimensions of QM emerging from these studies would vary somewhat, the essential concept they advocate tends to be congruent We adopt the conceptualization of Wilkinson (1992) where QM is classified into two dimensions: hard QM and soft QM We provide the definition below, and identify the main constructs for them from major QM studies at an operational level Hard QM is generally defined as the QM practices which focus on controlling processes and products through techniques and tools in order to conform to and satisfy established requirements One of the most representative tool/technique-oriented QM practices (hard QM) is process management which has been covered by most major studies on QM such as Saraph et al (1989), Anderson et al (1995), and Flynn et al (1995) Process management refers to monitoring of manufacturing process through the techniques and tools applied to a process to reduce process variation, so that it operates as expected, without breakdowns, missing materials, fixtures, tools, etc and despite workforce variability (Flynn et al., 1994) The process management category can further be broken down into sub-categories According to Flynn et al (1994), process management includes three major practices: process control, preventative maintenance, and housekeeping Process control is used to track process performance for in-production quality assurance (Deming, 1986; Ahire and Dreyfus, 2000) Preventative maintenance aims to conduct safety activities and avoid equipment breakdowns through scheduled maintenance (Flynn et al., 1995; Arauz et al., 2009) Housekeeping focuses on keeping the cleanliness and organization of the workplace to avoid clutter that hides defects and their causes (Flynn et al., 1994; Schonberger, 2007) Another typical tool/technique-oriented QM practice is the usage of quality information whose importance in QM has been underlined by so many researchers (Ho et al., 2001; Forza, 1995; Saraph et al., 1989) that it can be identified as one of the fundamental dimensions in hard QM Quality information provides workers with timely and accurate information about both quality performance and the operation of the manufacturing process to assist in operational controls (Flynn et al., 1994; Forza, 1995) Soft QM can be generally defined as the QM practices which are directed toward involvement and commitment of management and employees, training, learning, and internal cooperation or teamwork – in other words, promoting the human aspects of the system As noted by Bowen and Lawler (1992), ultimately it is “people that make quality happen” Previous studies have captured soft QM broadly at organizational or strategic level by including open organization (Powell, 1995), visionary leadership (Anderson et al., 1995), shared vision (Dow et al., 1999), strategic planning (Samson and Terziovski, 1999), etc., at interorganizational level by considering relationship with customer and suppliers (Flynn et al., 1995), and at employee level by embodying employee relations (Saraph et al., 1989) As our study is conducted at an operational level, soft QM can be better captured by employee-related factors Ahire et al (1996a) consider three employee-related factors: employee involvement, employee empowerment, and employee training This content and range are similar to the suggestion of Martinez-Lorente et al (2000) for measuring employee relations: the use of improvement teams, suggestion schemes and training Following the same line, in our study, we used small group problem solving, employee suggestion, and task-related training for employees to capture the concept of soft QM Small group problem solving uses teamwork activities to solve quality problems (Flynn et al., 1994) for improvement The importance of teaming for joint problem solving and quality improvement has been included in several research works (Linderman et al., 2004; Dow et al., 1999; Abraham et al., 1999) Employee suggestion encourages personnel to make suggestions on how the process can be improved, by referring to their direct experience (Forza and Salvador, 2001) Implementation and feedback on these suggestions can help make improvement and unleash the knowledge previously retained by individuals Task-related training for employees aims to update employees' skill and knowledge in order to maintain a workforce with cutting-edge skills and abilities (Flynn et al., 1994) This can not only facilitate workers to better perform their tasks, but also transform workers into flexible problem solvers and encourage them to be involved with their jobs (Kaynak, 2003) There are no consistent findings on the relationship between hard QM and soft QM and their role in determining performance Scholars not agree on which dimension of QM is more important to quality performance Studies such as Powell (1995) and Dow et al (1999) conclude that only tacit, intangible and social practices (soft QM) combine to contribute to superior quality outcomes, rather than QM tools and techniques (hard QM) However, studies such as Forza and Filippini (1998) suggest hard QM to be more important than human resources factor (soft QM) in the achievement of quality performance Also, there is no agreement on the direct/indirect effect of hard/soft QM on quality performance Many insightful studies in the QM literature, such as Ahire and Ravichandran (2001), Anderson et al (1995), Flynn et al (1995), Kaynak (2003), all tend to model QM practices–performance relationships in the sequence from soft QM practices, hard QM practices, up to quality performance This approach assumes complete mediation of hard QM between soft QM and quality performance since the direct impact of soft QM on quality performance is not considered This assumption lacks rigorous validation and the partial mediation of hard QM between soft QM and quality performance needs to be examined, as argued by Ho et al (2001) and Rahman and Bullock (2005) However, Ho et al (2001) and Rahman and Bullock (2005) arrive at different results Ho et al (2001) empirically support soft QM only has an indirect impact on performance through hard QM (complete mediation), Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ while Rahman and Bullock (2005) support the direct impact of soft QM on performance as well (partial mediation) We build on the classification of hard and soft QM discussed above to introduce a set of hypotheses that link hard QM, soft QM, quality performance and innovation performance 2.3 Hypotheses development According to this literature, QM practices that are more technique and tool oriented such as process management, and quality information fall under the category of hard QM However, upgrading technology and promoting hard QM may not be sufficient to increase competitive advantage Kochan et al (1995) argue that quality needs to be viewed not as a limited set of technical engineering changes, but as part of a broader strategy of an organizational change The adoption and utilization of these technique and tool for quality improvement highly rely on wellmotivated employees with good problem-solving ability and systematic encouragement promoted by managers empowering employees to apply their ability These can be supported by soft QM Previous studies such as Ahire and Ravichandran (2001), Anderson et al (1995), Flynn et al (1995), Kaynak (2003) all tend to model QM practices–performance relationships in the sequence from soft QM practices, hard QM practices, up to quality performance and empirically found that soft QM facilitates the implementation of hard QM As such, we contend that a sound soft QM system can nurture a corporate culture of autonomy, cooperation and teamwork, which provides a firm support for the successful implementation of QM techniques and tools The following hypothesis can therefore be suggested: H1 Soft QM has a positive impact on hard QM The relationship between QM practices and quality performance has been well documented in the extensive QM literature, such as Flynn et al (1995), Powell (1995), Dow et al (1999), Samson and Terziovski (1999), Forza and Filippini (1998), and Kaynak (2003) TOM literature suggests that hard QM such as striving for the reduction of process variance, making full use of quality information, etc., in fact have a profound impact on organizational performance By identifying problem areas in production and taking corrective actions to eliminate the quality problems through process management, the amount of scrap and rework generated will decrease, which directly leads to better conformance quality (Ahire and Dreyfus, 2000; Flynn et al., 1995; Kaynak, 2003) The use of quality information should also have a direct effect on quality performance by informing the operators and engineers about defective parts immediately so that corrective actions can be taken timely to remedy problems before the process drifts out of control, producing defects (Flynn et al., 1995; Kaynak, 2003) Direct impact of soft QM on organizational performance has been demonstrated by empirical studies such as Powell (1995), Ahire et al (1996b), and Dow et al (1999) Through a study of 39 QM companies in the US, Powell (1995) examines the relationship of each of 12 QM factors The results indicate that QM success is dependent on more intangible factors (soft QM), rather than on the more tangible factors (hard QM) such as zero defects mentality, and process improvement Ahire et al (1996a) draw a similar conclusion in their study of automobile manufacturing and component companies in the US They conclude that product quality is highly correlated with elements of soft QM, such as employee empowerment, employee training and employee involvement Empirical findings from the study of Australian manufacturing companies conducted by Dow et al (1999) also suggest that out of a total of nine QM factors, only three soft aspects of QM practices have a significant positive association with quality performance Taking a resource-base perspective, the intangible and behaviorally oriented elements that are embodied in soft QM might not be readily imitable by QM adopters since they may require a substantial change in corporate culture, and thus can directly yield a superior performance for the companies having these intangible factors embedded into their corporate culture The following hypotheses can be proposed: H2 Hard QM has a positive impact on quality performance H3 Soft QM has a positive impact on quality performance Several empirical studies have shown that hard QM can have a positive impact on innovation (Flynn, 1994; Kim et al., 2012; Perdomo-Ortiz et al., 2006) Kim et al (2012) argue that by implementing QM tools, a firm can identify potential innovation areas, develop innovation plans, and produce innovative products and processes Effective management of processes encourages firms to develop routines that are formed by a set of best practices, which can be used to establish a learning base and support innovative activities (Perdomo-Ortiz et al., 2006; Peng et al., 2008) Effective use of quality information offers the opportunities for identifying non-value-added process, and helps employees when modifying and improving processes (Kaynak, 2003) Flynn (1994) demonstrates that receiving immediate and useful feedback from the manufacturing process is instrumental in speeding new product to the market Along the same line, Miller (1995) found that managing quality information is the most important QM practice that can be applicable to innovation activities Sitkin et al (1994) argue hard QM focusing on cybernetic control system is tightly related to the achievement of conformance, and soft QM which facilitates sharing of knowledge and skills can be expected to associate with innovation Soft QM which promotes employee empowerment, involvement and teamwork is highly related to TQL, and can be expected to contribute to innovation Soft QM enables open communication and supports creative idea suggestion, which is essential to innovate It can be argued that soft QM can create a favorable and fertile atmosphere or platform for developing innovation As noted by Zairi (1994), QM has “given organizations the impetus and commitment required for establishing climates of never-ending innovation or innovativeness” (p 28) Empirical evidence provided by Prajogo and Sohal (2004) confirms this favorable effect They conclude that leadership and people management are related to the greater novelty of the product innovation Flynn (1994) also highlights the importance of soft QM which can help establish teamwork, encourage creative ideas from employees, and promote communication environment in achieving fast product innovation This leads to the following hypotheses: H4 Hard QM has a positive impact on innovation performance H5 Soft QM has a positive impact on innovation performance According to the perspective of cumulative capabilities, capabilities are layered upon each other, and are mutually reinforcing (Boyer and Lewis, 2002) There are a number of researchers who have made an effort to develop a sequential model for cumulative capabilities (Ferdows and De Meyer, 1990; Swink and Way, 1995; Schmenner and Swink, 1998) One of the commonalties between these sequential models is that quality is viewed as the foundation for the development of cumulative capabilities Quality performance is a precondition for the development of other strategic thrusts Flynn (1994) notes that firms which use product innovation as a competitive weapon would fall short of achieving potential market success with a poor quality Besides, quality performance reflects the cumulative efforts firms have strived to Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ improve quality in the past While firms may enjoy improved innovation performance through implementing QM practices as an expedient measure, enhancing innovation performance would also need to keep on doing QM practices until remarkable results (superior quality performance) are achieved Prajogo and Sohal (2003) empirically demonstrate a strong relationship between quality performance and innovation performance in terms of both product innovation and process innovation Thus, we hypothesize: H6 Quality performance has a positive impact on innovation performance The structural model presented in Fig shows the relationships proposed above the structural relationship between management practices and performance to have remained stable in the last decade and that the findings from the study will be relevant to current business and management practice All plants in the sample represented different parent corporations Three hundred and sixty-six plants were solicited for participation by calling or personal visit Two hundred and thirty-eight plants agreed to participate and each plant received a batch of questionnaires The question items were assigned to multiple questionnaires and distributed to the appropriate respondents For comprehensive details on HPM survey, please refer to Schroeder and Flynn (2001), Peng et al (2008), etc Table summarizes the profile of the sample by industry and country 3.2 Measures Research methodology This study uses a survey research method to examine the hypothesized relationships between QM practices and innovation performance Description about the survey sample, measures and data testing is provided below 3.1 Sample Data used in this study were collected through an international joint research named High Performance Manufacturing (HPM), round This project aims to study management practices and their impact on plant performance within global competition The sample consists of 238 manufacturing plants which are both traditional and world-class plants, and was stratified by industry and nation There are eight countries included in the sample: the United States, Japan, Italy, Sweden, Austria, Korea, Germany and Finland The three industries chosen are electrical & electronics, machinery, and automobile, since they were industries in transition, where a great deal of variability in performance and practices was expected to be present (Schroeder and Flynn, 2001) Even though the data was collected during 2003–2005, we can expect Fig Conceptual model To operationalize hard QM and soft QM, we identify suitable measurement scales from the HPM database that would be consistent with the meaning of the constructs Following the literature review conducted in Section 2.2, hard QM is proposed as a multidimensional construct consisting of Process management and Quality information Three individual measurement scales, Process control, Preventive maintenance, and Housekeeping, are used to measure Process management which is constructed as a super-scale Three measurement scales are developed to examine soft QM – Small group problem solving, Employee suggestion, and Task-related training for employees Thus, in total four measurement scales are identified to measure hard QM, along with three measurement scales for soft QM These seven measurement scales are measured through perceptual questions over seven points on the Likert scale (1¼Strongly disagree, 4¼Neither agree nor disagree, 7¼ Strongly agree) Each of these measurement scales has multiple respondents from the same plant These respondents are from six positions: direct workers, human resource manager, quality manager, supervisors, process engineer, and plant superintendent Quality performance has been reflected and measured in various ways in past empirical studies on QM One well known work was carried out by Garvin (1987), which proposes eight dimensions of product quality Among the eight dimensions, conformance is the primary dimension measuring quality, having impact on performance, durability and reliability In this study, we measure quality performance by conformance which is the most basic among quality criteria Conformance is defined as the level of conformity to specifications which indicates how well the actual product conforms to the design once it has been manufactured This measurement is linked to the production point of view and to some extent is determined by defect rates, new product yield, scrap and rework, etc Previous studies on organizational innovation also show variations in measuring innovation performance in organizations Researchers have tried to distinguish different types of innovation, and a number of typologies of organizational innovation have been proposed (e.g Daft, 1978; Dewar and Dutton, 1986; Ettlie et al., 1984) Three typologies have emerged from past research and gained the most attention, with each centering on a pair of types of innovation: administrative and technical, product and process, Table Profile of sample plants Country Electrical & electronic Machinery Automobile Total Total Austria Finland Germany Italy Japan Korea Sweden USA 10 21 14 10 30 13 19 41 10 10 27 10 12 13 35 10 10 11 31 10 24 11 29 79 79 80 238 Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ and radical and incremental In this study, we refer to the typology of product and process innovation, which is the most traditional one, and we particularly focus on product innovation instead of lumping all kinds of innovation into one single indicator According to Ettlie (1990), product innovations are new products or services introduced to meet an external user or market need We measure product innovation by two criteria: speed of new product introduction, and product innovativeness Both quality and innovation performance measures are evaluated based on a five-point scale, where a high score indicates that plant manager perceives that the plant has been relatively successful pursuing these performance indicators compared to its competitors 3.3 Testing measurement scales Three steps are executed in the validation process for the measurement scales: reliability, content validity and construct validity The reliability and validity tests for the four measurement scales for hard QM from Process control to Quality information, three measurement scales for soft QM from Small group problem solving to Task-related training for employees, as well as Innovation performance in Table are conducted on a dataset at an individual level consisting of response from each respondent Reliability is broadly defined as the degree to which scales are free from error and therefore consistent (Nunnally and Bernstein, 1994) Reliability is operationalized through the internal consistency method Cronbach's alpha is used as the reliability indicator and a value of 0.6 or above is considered acceptable We eliminate the items that not strongly contribute to Cronbach's alpha and whose content is not critical Table shows the Cronbach's alpha value for all scales As can be seen, most of the scales exceed the lower limit by a substantial margin, indicating a good reliability of the measurement scales Content validity is ensured through an extensive review of literature and empirical studies Construct validity measures the extent to which the items in a scale all measure the same multivariate construct Factor analysis is used to establish construct validity, and the results demonstrate that all scales are onedimensional The eigenvalues for each measurement scale are presented in Table and the factor loadings by item are shown in the Appendix The eigenvalue of the first factor for each scale is above the minimum eigenvalue of 1.00, and all factor loadings meet the criterion of larger than 0.4 Thus, all items contribute to their respective scales, indicating a good construct validity After establishing satisfactory measurement performance, a dataset at the plant level is aggregated by averaging the item scores for each measurement scale All scale responses are averaged into a single plant response per scale Aggregating respondents across respondent category and collecting the same data from different respondents can help address the issue of common method bias Based on this plant-level data, the super-scale Process Management consisting of Process control, Preventive maintenance, Table Summary of measurement analysis Measure name Process control Preventive maintenance Housekeeping Quality information Small group problem solving Employee suggestion Task-related training for employees Innovation performance Process management Mean S.D 4.811 4.858 5.516 4.878 5.046 5.171 5.187 3.448 4.987 0.827 0.666 0.687 0.843 0.640 0.624 0.625 0.877 0.577 Cronbach alpha Eigenvalue (% variance) 0.824 0.675 0.817 0.791 0.824 0.834 0.792 0.681 0.696 2.964(59) 2.202(44) 2.847(57) 2.759(55) 3.211(54) 3.025(60) 2.477(62) 1.517(75) 1.878(63) and Housekeeping is subject to the same process of testing reliability and validity as above This super-scale is found to be reliable and valid as shown at the bottom of Table 2, and then it is computed by averaging the scores of its three measurement scales Hypothesis testing Hypotheses are tested using AMOS program A number of indices are used to determine the fit of the data to the model (e.g χ2/df, CFI, RMSEA and PNFI) The overall fit statistics for the hypothesized model are χ2 ¼18.102, df ¼10, χ2/df ¼1.810, p ¼0.053, CFI¼0.988, PNFI¼ 0.417, and RMSEA¼ 0.047 The index χ2/df ratio which is below the threshold level of with a p value more than 0.05 indicates a good model fit Our CFI, which has the value of 0.988, is optimal, since it has to be greater than 0.9 for the model to be considered very good (Bentler, 1990) PNFI should be higher than 0.5 for the model to be considered very good; our results (PNFI¼0.417) are close to this criterion RMSEA is another fit statistics which adjust the sample discrepancy function by degree of freedom The RMSEA has been recognized as one of the most informative criteria in SEM (Byrne, 2001) and values of 0.05 or less indicate good fit; on this criterion, our model (RMSEA ¼0.047) fits well From these fit statistics, it is concluded that the overall model demonstrates a good model fit In addition to a good fit of the structural model, a good structural equation model needs to have a good measurement model Table presents the estimated values of the standardized path coefficients of all measurement constructs to their related latent constructs, and the relative p-value Some constructs not present p-values in that the relative path coefficient is fixed at as suggested in the SEM theory The three constructs of hard QM, and those of soft QM all have significant estimates of the standardized coefficients between 0.691 and 0.888, demonstrating good measurement models of hard QM and of soft QM Table presents the analysis results of the structural model Two paths, from soft QM to Quality Performance (standardized Table Results for the measurement model Construct name Measure variable Standardized coefficient p-Value Hard QM Process management Quality information 0.888 0.783 – 0.000 Soft QM Small group problem solving Employee suggestion Task-related training for employees 0.861 0.772 0.691 – 0.000 0.000 Table Results for the structural model Causing construct Caused construct Hypothesis Standardized coefficient p-Value Soft QM Hard QM Hard QM Quality performance Quality performance Innovation performance Innovation performance Innovation performance H1 H2 0.900 0.294 0.000 0.000 H3 Not supported H4 0.141 H5 Not supported H6 0.308 Soft QM Hard QM Soft QM Quality performance 0.047 0.000 Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ coefficient¼0.064; p-value¼ 0.799) and from soft QM to Innovation Performance (standardized coefficient¼ 0.025; p-value¼0.918), are insignificant Among six hypotheses, four are supported and two are rejected The results show that soft QM has a positive impact on hard QM, suggesting support for H1 The results also indicate that hard QM has a significant impact on both quality performance and innovation performance, supporting H2 and H4 However, soft QM has no direct impact on either quality performance or innovation performance, suggesting rejecting H3 and H5, which is surprising This result might be due to our study scope particularly focusing on plant operations, as further discussed in the next section Quality Performance is also found to directly influence innovation performance, which provides support for H6 Fig presents the summary of the findings above Discussion and implications In this section, we discuss the main findings and implications for management First, the results of this study reveal that hard QM completely mediates the relationship between soft QM and quality performance (support for H1 and H2, and rejection against H3) Although some researchers found that soft QM had a direct effect on performance (Rahman and Bullock, 2005), our findings are consistent with the results suggested by Ho et al (2001) Indeed, many insightful empirical studies on the impact of QM practices on performance have modeled the relationship between QM practices and performance in the sequence from soft QM to hard QM then to quality performance, such as Anderson et al (1995), Flynn et al (1995), Forza and Filippini (1998), and Kaynak (2003) Our findings provide a strong support for the assumption of complete mediation underlying these studies, though Ho et al (2001) argue the possibility that hard QM practices partially mediate the relationship between soft QM practices and performance Firm-level studies, such as Rahman and Bullock (2005), tend to suggest the direct impact of soft QM on performance However, at the plant level, hard QM could exhibit a dominant influence on quality performance in terms of conformance Therefore, hard QM becomes a complete mediator between soft QM and quality performance Successful implementation of hard QM, in turn, is achieved through well-established soft QM Another interesting insight gained from this study considers the different ways of each dimension of QM in influencing innovation performance This has been suggested by a few of previous studies, but there exists disagreement regarding which dimension is more effective in determining innovation performance While some studies (e.g Prajogo and Sohal, 2003; Feng et al., 2006) contend that only soft dimension (leadership and people management) can foster innovation, Perdomo-Ortiz et al (2006) assert that both hard and soft dimensions (e.g process Fig SEM result management and human resource management) play a significant role in building innovation capability However, Kim et al (2012) demonstrate a dominant role of process management (hard QM) when supported by other interrelated quality practices in determining innovation Our study is significantly different from these studies in that it distinguishes hard QM from soft QM It also verifies the QM– innovation relationship on a global basis rather than a single region Our findings align with Kim et al.'s (2012), highlighting the importance of hard QM to innovation and the supporting role of soft QM Results reveal that hard QM plays an essential role in determining innovation performance Supported by soft QM, hard QM can affect innovation performance not only directly but also indirectly through the accumulative effect of improved quality This finding can be supported by several arguments in the literature Since hard QM emphasizes the use of quality techniques and tools, it helps organization to reestablish order – getting the system in control through the reduction of variance Spencer (1994) notes that once the system is stable and in control, it is possible to learn how to improve, leading to fostering a learning base A set of routines established through the implementation of hard QM can support innovation activities because routine-based organizations pay more attention to vital processes and avoid activities that not add value (Hoang et al., 2006) However, the direct effect of soft QM on innovation performance lacks support by our empirical evidence This might be due to our operationfocused scope, under which soft QM is particularly measured at the operational level rather than at the firm level Firm-level soft QM practices, such as top management leadership for quality initiatives and organizational-wide training and learning, can instantly disseminate knowledge across functions and inspire creative ideas, which could be expected to directly yield improved innovation performance However, at the operational level, the strengthened human power through implementation of soft QM is first converted into productivity in terms of improved quality performance, and then would gradually become a solid foundation fostering innovation The choice of operational level allows us to have higher scrutiny of QM practices, since QM is often implemented on the plant level (Flynn et al., 1994) However, this also results in a limitation of scope Future research with a wider scope could complement our results Third, this study also provides support for the notion that quality must be attained first as a sequential precedent to other strategic capabilities (Ferdows and De Meyer, 1990) Quality performance has a mediating effect on the relationship between hard QM and innovation performance The mediating effect is partial because hard QM has a direct impact on innovation performance The continuously improved quality performance would lead to the achievement of other strategic competitive priorities in a cumulative fashion Although QM practices are originally intended to enhance quality performance, the achieved quality performance can result in the improvement of innovation performance This result can be considered as a secondary but indispensible effect of the implementation of QM practices Therefore, quality and innovation are not a matter of trade-off, but they can coexist in a cumulative improvement model with quality as a foundation Managers can find useful reference from this study Our findings respond to the concerns that managers have on whether QM should be continued as a future management paradigm in the increasingly competitive and fast changing environment The empirical results suggest that QM implementation can affect innovation which allows firms to adapt to the market changes This is an encouraging finding for practicing mangers as it demonstrates the simultaneous pursuit of multiple competitive advantages in both quality and innovation QM implementation is able to transform firms to be ambidextrous in both efficiently Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ managing current market demands and adaptively responding to market changes coming in the future Firms should not abandon QM practices, even though some quality aspects such as conformance to specifications are no longer considered as a winning criterion in some industries To obtain innovation performance through QM, managers are encouraged to leverage the different roles played by different dimensions of QM in determining innovation performance Firms would foster innovation through QM by emphasizing on the establishment of a routine base through QM tools and techniques, which can be facilitated by the concurrent use of teamwork, training, employee empowerment and problem-solving approaches Additionally, the role of quality performance as a partial mediator between QM practices and innovation performance has a valuable managerial implication Quality performance reflects the cumulative efforts firms have strived for quality improvement in the past The cumulative effect of quality performance on innovation performance would suggest that managers devote continuous efforts involving employees into quality improvement initiatives in order to foster innovation eventually Firms should not just rush to implement QM practices for short periods expecting instant benefits on innovation performance, but need to stay grounded to keep implementing QM until remarkable quality performance is achieved All together, achievement of innovation through QM requires a sound quality system in place integrating a set of QM practices and corresponding performance measures At the end, innovation is not a fancy achievement occasionally coming from a whim of some talent, but it stems from a solid foundation where employees have thorough understanding of process, go deep into the root cause of quality problems, and persistently look for solutions to improve As a sound quality system is the very mechanism of laying such a foundation, firms that have their feet on the ground with much attention to their process could more easily enjoy the benefit of innovation in addition to quality foundation Limitations and future research Several limitations to this study should be taken into consideration First, the data we used to conduct analysis was collected from 2003–2005 The implementation level of QM has become more widespread and pervasive across business organizations since these data were collected However, we argue that the structural relationships between management practices and performance are likely to have remained fairly constant We note below the desirability of further longitudinal studies to understand these issues further Another limitation is that this study utilizes survey-based subjective and qualitative data Although we address the issue of common method bias through the use of multiple respondents, this study relies on the perceptions of the respondents to operationalize the survey instrument This may have introduced bias in to the data, which could cause potential concerns regarding generalizability, reliability, and validity Third, many parts of the discussion in this research tend to be biased towards manufacturing operations A large portion of the literature addressing the theoretical and empirical aspects of the research topic has been derived from the manufacturing point of view, and the data used in this study is coming from only manufacturing plants The findings and conclusion could not be generalized to the firm level or the service industry at the current stage Future research can expand to a service setting While this study has contributed to the body of knowledge about the relationship between QM and innovation, we suggest that the following areas could further enhance the understanding about this relationship First, an examination of the potential effects of contingency factors on the proposed framework could provide a fruitful field of research endeavor Contingency factors such as environmental uncertainty, organizational culture, and organization's strategy can be investigated Second, it would be valuable to conduct a longitudinal study within organizations to observe the achievement of innovation performance through the cumulative effect of QM implementation Third, future studies can also examine the QM–innovation relationship with an expanded scope such as strategic level, firm level, or even inter-firm level, which would generate more interesting results complementing with ours Conclusions Based on a multi-dimensional view of QM, this study has provided empirical evidence to resolve some of the controversies that appear in the literature concerning the relationship between QM and innovation The findings support the notion that QM provides a foundation to achieve a competitive position in innovation, and suggest the importance of continued efforts with QM practices Innovation can be achieved through quality in a cumulative fashion, which is consistent with the proposition by the well-known sand cone model By looking at QM from two dimensions, hard and soft QM, this study further contributes to the understanding of the different roles played by different QM dimensions in determining innovation It highlights the significance of the routine-based approach through emphasis on the implementation of hard QM to foster a learning base leading to innovation, with soft QM playing a supporting role behind to enable this effect to work Acknowledgments The authors appreciate the financial support for this research from the Japan Society for the Promotion of Science by Grant-inAids for Scientific Research, Nos 22330112 and 25245050 Appendix Question items of measurement scales Factor loadings are given in parentheses following each item Process control Processes in our plant are designed to be “foolproof” (0.581) A large percent of the processes on the shop floor are currently under statistical quality control (0.815) We make extensive use of statistical techniques to reduce variance in processes (0.825) We use charts to determine whether our manufacturing processes are in control (0.734) We monitor our processes using statistical process control (0.862) Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 10 Preventive maintenance We upgrade inferior equipment, in order to prevent equipment problems (0.689) In order to improve equipment performance, we sometimes redesign equipment (0.542) We estimate the lifespan of our equipment, so that repair or replacement can be planned (0.748) We use equipment diagnostic techniques to predict equipment lifespan (0.734) We not conduct technical analysis of major breakdowns (0.578) Housekeeping Our plant emphasizes putting all tools and fixtures in their place (0.698) We take pride in keeping our plant neat and clean (0.811) Our plant is kept clean at all times (0.856) Employees often have trouble finding the tools they need (0.586) Our plant is disorganized and dirty (0.791) Quality information Charts showing defect rates are posted on the shop floor (0.758) Charts showing schedule compliance are posted on the shop floor (0.754) Charts plotting the frequency of machine breakdowns are posted on the shop floor (0.692) Information on quality performance is readily available to employees (0.781) Information on productivity is readily available to employees (0.726) Small Group Problem Solving During problem solving sessions, we make an effort to get all team members' opinions and ideas before making a decision (0.643) Our plant forms teams to solve problems (0.805) In the past three years, many problems have been solved through small group sessions (0.786) Problem solving teams have helped improve manufacturing processes at this plant (0.775) Employee teams are encouraged to try to solve their own problems, as much as possible (0.652) We don't use problem solving teams much, in this plant (0.710) Employee suggestion Management takes all product and process improvement suggestions seriously (0.809) We are encouraged to make suggestions for improving performance at this plant (0.780) Management tells us why our suggestions are implemented or not used (0.764) Many useful suggestions are implemented at this plant (0.819) My suggestions are never taken seriously around here (0.711) Task-related training for employees Our plant employees receive training and development in workplace skills, on a regular basis (0.854) Management at this plant believes that continual training and upgrading of employee skills is important (0.779) Employees at this plant have skills that are above average, in this industry (removed) Our employees regularly receive training to improve their skills (0.879) Our employees are highly skilled, in this plant (0.608) Innovation performance Please circle the number which indicates your opinion about how your plant compares to its competition in your industry, on a global basis (5 ¼Superior, ¼Better than average, ¼Average or equal to the competition, ¼Below average, ¼Poor, low end of industry) Speed of new product introduction (0.871) Product innovativeness (0.871) References Abrunhosa, A., Sá, P., 2008 Are TQM principles supporting innovation in the Portuguese footwear industry? Technovation 28 (4), 208–221 Abraham, M., Crawford, J., Fisher, T., 1999 Key factors predicting effectiveness of cultural change and improved productivity in implementing total quality management Int J Qual Reliab Manag 16 (2), 112–132 Ahire, S.L., Dreyfus, P., 2000 The impact of design management and process management on quality: an empirical examination J Oper Manag 18 (5), 549–575 Ahire, S.L., Ravichandran, T., 2001 An innovation diffusion model of TQM implementation IEEE Trans Eng Manag 48 (4), 445–464 Ahire, S.L., Waller, M.A., Golhar, D.Y., 1996a Quality management in TQM versus non-TQM firms: an empirical investigation Int J Qual Reliab Manag 13 (8), 8–27 Ahire, S.L., Golhar, D.Y., Waller, M.A., 1996b Development and validation of TQM implementation constructs Decis Sci 27 (1), 23–56 Anderson, J.C., Rungtusanatham, M., Schroeder, R.G., Devaraj, S., 1995 A path analytic model of a theory of quality management underlying the Deming management method: preliminary empirical findings Decis Sci 26 (5), 637–658 Anderson, M., Sohal, A., 1999 A study of the relationship between quality management practices and performance in small businesses Int J Qual Reliab Manag 16 (9), 859–877 Arauz, R., Matsuo, H., Suzuki, H., 2009 Measuring changes in quality management: an empirical analysis of Japanese manufacturing companies Total Qual Manag Bus Excell 20 (12), 1337–1374 Bennett, R.C., Cooper, R.C., 1981 The misuse of marketing: an American tragedy Bus Horizons 24 (6), 51–61 Bentler, P.M., 1990 Comparative fit indexes in structural models Psychol Bull 107 (2), 238–246 Bowen, D., Lawler, L., 1992 Total quality-oriented human resource management Organ Dyn 24 (4), 39–41 Boyer, K.K., Lewis, M.W., 2002 Competitive priorities: investigating the need for trade-offs in operations strategy J Oper Manag 11 (1), 9–20 Byrne, B.M., 2001 Structural Equation Modelling with AMOS—Basic Concepts, Applications and Programming Lawrence Erlbaum Associates, Mahwah, NJ Corbett, C., Van Wassenhove, L., 1993 Trade-offs? What trade-offs? Competence and competitiveness in manufacturing strategy Calif Manag Rev 35 (4), 107–122 Daft, R.L., 1978 A dual core model of organizational innovation Acad Manag J 21 (2), 193–210 Deming, W.E., 1986 Out of the Crisis MIT Press, Cambridge, MA Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i J Zeng et al / Int J Production Economics ∎ (∎∎∎∎) ∎∎∎–∎∎∎ Dewar, R.D., Dutton, J.E., 1986 The adoption of radical and incremental innovations: an empirical analysis Manag Sci 32 (11), 1422–1433 Dow, D., Samson, D., Ford, S., 1999 Exploding the myth: all quality management practices contribute to superior quality performance Prod Oper Manag (1), 1–27 Ettlie, J.E., Bridges, W.P., O'Keefe, R.D., 1984 Organizations strategy and structural differences for radical versus incremental innovation Manag Sci 30 (6), 682–695 Ettlie, J.E., 1990 What make a manufacturing firm innovative? Acad Manag Exec (4), 7–20 Feng, J., Prajogo, D.I., Tan, K.C., Sohal, A.S., 2006 The impact of QM practices on performance a comparative study between Australian and Singaporean organizations Eur J Innov Manag (3), 269–278 Ferdows, K., De Meyer, A., 1990 Lasting improvements in manufacturing performance: in search of a new theory J Oper Manag (2), 168–184 Flynn, B.B., 1994 The relationship between quality management practices, infrastructure and fast product innovation Benchmarking Qual Manag Technol (1), 48–64 Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1994 A framework for quality management research and an associated measurement instrument J Oper Manag 11 (4), 339–366 Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1995 The impact of quality management practices on performance and competitive advantage Decis Sci 26 (5), 659–691 Forza, C., 1995 The impact of information systems on quality performance: an empirical study Int J Oper Prod Manag 15 (6), 69–83 Forza, C., 1996 Work organization in lean production and traditional plants: what are the differences? Int J Oper Prod Manag 16 (2), 42–62 Forza, C., Filippini, R., 1998 TQM impact on quality performance and customer satisfaction: a causal model Int J Prod Econ 55 (1), 1–20 Forza, C., Salvador, F., 2001 Information flows for high-performance manufacturing Int J Prod Econ 70 (1), 21–36 Garvin, D.A., 1987 Competing on the eight dimensions of quality Harv Bus Rev 65 (6), 202–209 Gibson, B.C., Birkinshaw, J., 2004 The antecedents, consequences, and mediating role of organizational ambidexterity Acad Manag J 47 (2), 209–226 Glynn, M.A., 1996 Innovative genius: a framework for relating individual and organizational intelligences to innovation Acad Manag Rev 21 (4), 1081–1111 Hoang, D.T., Igel, B., Laosirihongthong, T., 2006 The impact of total quality management on innovation: Findings from a developing country Int J Qual Reliab Manag 23 (8–9), 1092–1117 Ho, D.C.K., Duffy, V.G., Shih, H.M., 2001 Total quality management: an empirical test for mediation effect Int J Prod Res 39 (3), 529–548 Humble, J., Jones, G., 1989 Creating a climate for innovation Long Range Plan 22 (4), 46–51 Imai, M., 1986 Kaizen: The Key to Japan's Competitive Success Random House, New York Jha, S., Noori, H., Michela, J.L., 1996 The dynamics of continuous improvement— aligning organizational attributes and activities for quality and productivity Int J Qual Sci (1), 19–47 Kaynak, H., 2003 The relationship between total quality management practices and their effects on firm performance J Oper Manag 21 (4), 405–435 Kim, D.Y., Kumar, V., Kumar, U., 2012 Relationship between quality management practices and innovation J Oper Manag 30 (4), 295–315 Kochan, T.A., Gittel, J.H., Lautsch, B.A., 1995 Total quality management and human resource systems: an international comparison Int J Hum Resour Manag (2), 201–222 Leong, G.K., Snyder, D.L., Ward, P.T., 1990 Research in the process and content of manufacturing strategy OMEGA: Int J Manag Sci 18 (2), 109–122 Linderman, K., Schroeder, R.G., Zaheer, S., Liedtke, C., Choo, A.S., 2004 Integrating quality management practices with knowledge creation processes J Oper Manag 22 (6), 589–607 Martinez-Lorente, A.R., Dewhurst, F.W., Gallego-Rodriguez, A., 2000 Relating TQM, marketing and business performance: an exploratory study Int J Prod Res 38 (14), 3227–3246 Martínez-Costa, M., Martínez-Lorente, A.R., 2008 Does quality management foster or hinder innovation? An empirical study of Spanish companies Total Qual Manag 19 (3), 209–221 Mazzola, E., Perrone, G., 2013 A strategic needs perspective on operations outsourcing and other inter-firm relationships Int J Prod Econ 144 (1), 256–267 Miller, R., 1995 Applying quality practices to R&D Res Technol Manag 38 (2), 47–54 11 McAdam, R., Armstrong, G., Kelly, B., 1998 Investigation of the relationship between total quality and innovation: a research study involving small organisations Eur J Innov Manag (3), 139–147 Molina, L.M., Lloréns-Montes, J., Ruiz-Moreno, A., 2007 Relationship between quality management practices and knowledge transfer J Oper Manag 25 (3), 682–701 Morgan, M., 1993 Creating Workforce Innovation—Turning Individual Creativity into Organizational Innovation Business and Professional Publishing, Chatswood, NSW Noble, M.A., 1995 Manufacturing strategy: testing the cumulative model in a multiple country context Decision Science 26 (5), 693–721 Nonaka, I., Peltokorpi, V., 2009 Knowledge-based view of radical innovation: toyota prius case In: Hage, J., Meeus, M (Eds.), Innovation, Science, and Institutional Change: A Research Handbook Oxford University Press, New York, pp 88–104 Nunnally, J.C., Bernstein, I.H., 1994 Psychometric Theory, third ed McGraw-Hill, New York Perdomo-Ortiz, J., González-Benito, J., Galende, J., 2006 Total quality management as a forerunner of business innovation capability Technovation 26 (10), 1170–1185 Peng, D.X., Schroeder, R.G., Shah, R., 2008 Linking routines to operations capabilities: a new prospective J Oper Manag 26 (6), 730–748 Pfeifer, T., Siegler, S., Varnhagen, V., 1998 Business excellence through a robust development process for innovative products Total Qual Manag Bus Excell (4&5), 191–194 Powell, T.C., 1995 Total quality management as competitive advantage: a review and empirical study Strateg Manag J 16 (1), 15–37 Prajogo, D.I., Sohal, A.S., 2001 QM and innovation: a literature review and research framework Technovation 21 (9), 539–558 Prajogo, D.I., Sohal, A.S., 2003 The relationship between QM practices, quality performance, and innovation performance: an empirical examination Int J Qual Reliab Manag 20 (8), 901–918 Prajogo, D.I., Sohal, A.S., 2004 The multidimensionality of QM practices in determining quality and innovation performance – an empirical examination Technovation 24 (6), 443–453 Rahman, S.-U., Bullock, P., 2005 Soft QM, hard QM, and organisational performance relationships: an empirical investigation Omega 33 (1), 73–83 Saraph, J., Benson, P., Schroeder, R., 1989 An instrument for measuring the critical factors of quality management Decis Sci 20 (4), 810–829 Samson, D., Terziovski, M., 1999 The relationship between total quality management practices and operational performance J Oper Manag 17 (4), 393–409 Sadikoglu, E., Zehir, C., 2010 Investigating the effects of innovation and employee performance on the relationship between total quality management practices and firm performance: an empirical study of Turkish firms Int J Prod Econ 127 (1), 13–26 Santos-Vijande, M.L., Álvarez-González, L.I., 2007 Innovativeness and organizational innovation in total quality oriented firms: the moderating role of market turbulence Technovation 27 (9), 514–532 Schmenner, R.W., Swink, M.L., 1998 On theory in operations management J Oper Manag 17 (1), 97–113 Schonberger, R.J., 2007 Japanese production management: an evolution – with mixed success J Oper Manag 25 (2), 403–419 Schroeder, R.G., Flynn, B.B., 2001 High Performance Manufacturing: Global Perspectives John Wiley & Sons, New York Singh, P.J., Smith, A.J.R., 2004 Relationship between QM and innovation: an empirical study J Manuf Technol Manag 15 (4), 394–401 Sitkin, S.B., Sutcliffe, K.M., Schroeder, R.G., 1994 Distinguishing control from learning in total quality management: a contingency perspective Acad Manag Rev 19 (3), 537–564 Slater, S.F., Narver, J.C., 1998 Customer-led and market-led: let's not confuse the two Strateg Manag J 19 (10), 1001–1006 Spencer, B.A., 1994 Models of organization and total quality management: a comparison and critical evaluation Acad Manag Rev 19 (3), 446–471 Spreitzer, G.M., 1995 Psychological empowerment in the workplace: dimensions, measurement, and validation Acad Manag J 38 (5), 1442–1465 Swink, M., Way, M.H., 1995 Manufacturing strategy: propositions, current research, renewed directions Int J Oper Prod Manag 15 (7), 4–26 Tidd, J., Bessant, J., Pavitt, K., 1997 Managing Innovation: Integrating Technological, Market, and Organizational Change Wiley, Chichester The Associated Press, 2013 Toyota Recalls 247,000 U.S Vehicles to Fix Engine Problems, September 4th Wilkinson, A., 1992 The other side of quality: ‘soft’ issues and the human resource dimension Total Qual Manag (3), 323–329 Zairi, M., 1994 Innovation or innovativeness? Results of a benchmarking study Total Qual Manag (3), 27–44 Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i ... article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i... article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An empirical study International Journal of Production Economics (2014), http://dx.doi.org/10.1016/j.ijpe.2014.07.006i... 0.308 Soft QM Hard QM Soft QM Quality performance 0.047 0.000 Please cite this article as: Zeng, J., et al., The impact of hard and soft quality management on quality and innovation performance: An