Research Paper

The Effect of Business Improvement Methods on Innovation in Small and Medium-Sized Enterprises

in Peripheral Regions

RICHARD HARRIS†*, RODNEY MCADAM‡ and RENEE REID§ †Durham University Business School, Mill Hill Lane, Durham DH1 3LB, UK. Email: [email protected]

‡Business School, University of Ulster, Jordanstown, Belfast BT37 0QB, UK §Business School, Glasgow Caledonian University, Glasgow G4 0BA, UK

(Received March 2014; in revised form July 2015)

HARRIS R., MCADAM R. and REID R. The effect of business improvement methods on innovation in small and medium-sized enterprises in peripheral regions, Regional Studies. This paper tests whether commonly used business improvement methods (BIM) foster or inhibit innovation in small and medium-sized enterprises (SMEs) in peripheral regions. The findings show that adopting BIM diverts firms away from successful innovation (i.e., in terms of new products/services and new processes in the past three years), and instead is associated with undertaking innovation-related activities while remaining non-innovators. Indeed, reinforcing BIM (through greater ‘depth’ of use) may lead to further exclusion from successful innovation.

Innovation Business improvement methods

HARRIS R., MCADAM R. and REID R. 增进商业方法对边陲地区中小型企业创新的影响，区域研究。本文检测一般用 来增进商业的方法（BIM），是否促进或抑制边陲地区中小型企业（SMEs）的创新。研究结果显示，採用BIM使得 企业远离成功的创新（例如过去三年内的新产品／服务和新制程），反而是在维持非创新者的同时，与着手从事创 新相关活动有关。强化BIM（透过更为“深化”的运用），的确有可能导致进一步排除成功的创新。

创新 商业增进方法

HARRIS R., MCADAM R. et REID R. L’impact des méthodes d’amélioration opérationnelle sur l’innovation dans les petites et moyennes entreprises situées à la périphérie, Regional Studies. Ce présent article cherche à évaluer si, oui ou non, les méthodes d’amélioration opérationnelle fréquemment utilisées ouvrent la voie ou constituent une entrave à l’innovation dans les petites et moyennes entreprises (Pme) situées à la périphérie. Les résultats montrent que l’adoption des méthodes d’amélioration opérationnelle détourne les entreprises de l’innovation réussie (c’est à dire en termes de nouveaux produits et services, et de nouveaux procédés au cours des trois dernières années), et les associent plutôt à la réalisation des activités liées à l’innovation tout en restant non-innovatrices. En effet, il se peut que renforcer les méthodes d’amélioration opérationnelle (par moyen d’une utilisation plus ‘approfondie’) puisse provoquer une intensification de la marginalisation qui pourrait porter atteinte à une future innovation réussie.

Innovation Méthodes d’amélioration opérationnelle

HARRIS R., MCADAM R. und REID R. Die Auswirkung von Methoden zur Geschäftsverbesserung auf die Innovation in kleinen und mittelständischen Unternehmen in Randgebieten, Regional Studies. In diesem Beitrag wird überprüft, ob häufig eingesetzte Methoden zur Geschäftsverbesserung die Innovation in kleinen und mittelständischen Unternehmen (KMU) in Randgebieten fördern oder hemmen. Aus den Ergebnissen geht hervor, dass die Umsetzung von Methoden zur Geschäftsverbesserung Firmen von erfolgreichen Innovationen (hinsichtlich neuer Produkte bzw. Dienstleistungen und neuer Verfahren in den letzten drei Jahren) abhält und stattdessen mit der Durchführung von innovationsbezogenen Aktivitäten bei gleichzeitiger fortge- setzter Nichtinnovation einhergeht. Eine Verstärkung der Methoden zur Geschäftsverbesserung (durch intensivere Nutzung) kann sogar zu einem weiteren Ausschluss von erfolgreichen Innovationen führen.

Innovation Methoden zur Geschäftsverbesserung

HARRIS R., MCADAM R. y REID R. El efecto de los métodos de mejora empresarial en la innovación en las pequeñas y medianas empresas de regiones periféricas, Regional Studies. En este artículo comprobamos si los métodos que se utilizan habitualmente para la

*Corresponding author.

Regional Studies, 2016

Vol. 50, No. 12, 2040–2054, http://dx.doi.org/10.1080/00343404.2015.1083971

© 2015 Regional Studies Association http://www.regionalstudies.org

mejora empresarial fomentan o inhiben la innovación en las pequeñas y medianas empresas (pymes) de regiones periféricas. Los resul- tados indican que al introducir métodos de mejora empresarial, las empresas no solo se alejan de conseguir una innovación eficaz (en lo que afecta a nuevos productos o servicios y nuevos procesos en los últimos tres años), sino que más bien al emprender actividades relacionadas con la innovación permanecen a la vez como empresas no innovadoras. Al reforzar los métodos de mejora empresarial (mediante un uso más intensivo) las empresas pueden incluso quedar aún más alejadas de poder conseguir una innovación eficaz.

Innovación Métodos de mejora empresarial

JEL classifications: D24, L23, O12, O31

INTRODUCTION

Regional-, national- and European Union-level govern- ments face a significant policy and practice challenge in seeking to improve the competitiveness of (particularly indigenous) small- to medium-sized enterprises (SMEs) in peripheral regions1 (such as North West Europe, as in this study) and to limit the growing disparity in pro- ductivity between these regions and more central regions (COOKE and SCHWARTZ, 2008; ABREU et al., 2011, ARBUTHNOTT and VON FREIDRICHS, 2013). Because of their innate resource limitations, one area of policy has been a focus on improving both manage- ment and workforce skills through using business improvement methods (BIM)2 to improve efficiency in production (e.g., SCOTTISH ENTERPRISE, 2012; INVEST NORTHERN IRELAND, 2012; ENTERPRISE IRELAND, 2012; MANUFACTURING ADVISORY SERVICE, 2012). Such BIM have become relatively common, especially in manufacturing firms, in recent years, although precise estimates of their take-up are dif- ficult to ascertain.3 While increases in efficiency help overall competitiveness, the former is only one element in determining (total factor) productivity; indeed, increasing levels of competition, globalization and tech- nology development have challenged SMEs to increase their levels of innovativeness. Innovation (or technical change) and increases in efficiency are both seen as leading to greater competitiveness (DEPARTMENT OF TRADE AND INDUSTRY (DTI), 2003; HM TREASURY, 2004; DEPARTMENT FOR INNOVATION, UNIVER- SITIES AND SKILLS (DIUS), 2008; EUROPEAN COMMISSION, 2006a, 2006b). Hence, policy has increasingly focused on encouraging innovation devel- opment within SMEs using a range of approaches, and especially to assume that BIM (which is now commonly encouraged in SMEs) is also an enabler for innovation.

Although the emphasis is on measuring the impact of adopting BIM on innovation activities for SMEs, this study controls for other influences by including most of the standard determinants of innovation that have featured in the literature, such as the characteristics of the firm, including which markets in which it sells and ownership, as well as the importance of ‘leadership’, ‘culture’ and variables representing absorptive capacity. The inclusion of BIM is rare, except in the operations management literature that deals specifically with total

quality management (TQM) (and similar BIM). And yet it is well known that BIM and innovation manage- ment strategies are likely to share a common organiz- ational platform that facilitates the sharing of knowledge and skills, and thus lead to greater competi- tive advantage (NOWAK, 1997). Thus, there seem to be obvious, logical linkages between BIM and innovation, although previous (and rather limited) empirical analysis has generally found mixed results relating to this link. This is often ‘explained’ by assuming that firms have either not fully understood (and resourced) BIM or that only specific methods that involve a more narrowly defined emphasis on incremental improvement is implemented, and this may actually truncate product and process innovations.

The sample of firms used comprised SMEs (employ- ing between 10 and 250 people) that were the client companies of the development agencies (Invest North- ern Ireland, Enterprise Ireland and Scottish Enterprise) in the adjacent border regions of Ireland (north and south) and Scotland. In general the development agencies target firms to become clients that have charac- teristics that make them more likely to succeed in becoming innovative/productive/profitable;4 as such this population of client firms is more likely to adopt BIM and/or engage in innovation-enhancing activities. That is, this subgroup of the population of SMEs is a more appropriate sample given their growth potential and direct exposure to ‘policy’ designed to make them more competitive and profitable. If the much larger population of all SMEs operating in the border regions were sampled, it is very likely the overwhelming majority would not have adopted BIM or been involved in innovation-related activities. Thus, this article is effectively testing whether attempts by the development agencies to engage SMEs in adopting BIM also had an impact on innovation; if it did this leads to a better understanding of the efficacy of such policies designed to improve innovation outcomes in peripheral regions.

It is also likely that firms that use BIM have character- istics that make them on average more/less likely to achieve different innovation-related outcomes; that is, there is a potential issue of self-selection that, if present, would bias any attempt to measure the impact of BIM on innovation. Thus, this study adopts the typical solution to this problem of self-selection by

Effect of Business Improvement Methods on Innovation in SMEs in Peripheral Regions 2041

‘matching’ the ‘treated’ group (those that use BIM) with a ‘control’ group (‘untreated’ firms that do not use BIM but which have very similar characteristics to the ‘treated’ group of firms – with both sets of firms being clients of the agency tasked with implementing policy).

All the existing studies that test whether BIM and innovation are related treat the latter as a single con- struct, i.e. the firm produces product/process inno- vations or not. This study takes a different approach by distinguishing between firms that innovate success- fully, those that invest in innovation-related activities but are unsuccessful, and those that do not undertake innovation-related activities. BIM is thus allowed potentially to impact differently on whether the firm undertakes innovation-related activities or not, and if so whether BIM influences innovation outcomes.

Lastly, there have been a limited number of studies of the determinants of innovation in SMEs in the geo- graphies covered in this paper. These have typically been based on data collected directly by researchers5

and which have looked at a number of factors deter- mining innovation within the framework of the ‘inno- vation production function’; e.g. the earlier work of HARRIS and TRAINOR (1995) concentrated on the links between undertaking research and development (R&D) and innovation outputs in manufacturing plants operating in Northern Ireland, while HEWITT- DUNDAS and ROPER (2008) conducted similar analysis covering Ireland and Northern Ireland but with a more extensive set of variables representing knowledge sour- cing and barriers to innovation. More recent work using the Ireland and Northern Ireland data collected by Roper and associates cover what determines inno- vation persistence (ROPER and HEWITT-DUNDAS, 2008); the impact of ownership on innovation (LOVE et al., 2009); and how external knowledge sourcing (i.e., ‘open’ innovation) impacts on innovation (ROPER et al., 2013). However, none of these studies collected data on BIM and therefore do not consider links between BIM and innovation – and especially the possibility that rather than being complements, BIM might result in innovation in SMEs being less likely.

The paper is structured as follows. It begins with a review of the theoretical and empirical literature on the relationship between BIM and innovation. The third section discusses the data used and the modelling strategy. This is followed by a presentation and discus- sion of the results obtained in the fourth section. Finally, the fifth section has a summary and conclusion, including the policy relevance of this study.

LITERATURE REVIEW

BIM and innovation activities6

BIM are part of the operation of business management models that usually comprise some or all of the

following range of processes: the need to focus on the customer’s needs, management involvement (in stra- tegic planning and committed leadership to drive change), continuous improvement (in how work is organized and conducted, and thus how goods and ser- vices are produced), and employee involvement (and empowerment, for example, through cross-functional training and work). The most comprehensive example is TQM, often described as an integrative philosophy of management for continuously improving the quality of products and processes;7 other BIM have a narrower focus. For example, Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimiz- ing variability in manufacturing and business processes; continuous improvement lies somewhere in between as an ongoing effort to improve products, services or processes where these efforts can seek ‘incremental‘ improvement over time or ‘breakthrough’ improve- ment all at once (ASQ, 2012).

As to the link between BIM and innovation, there are a number of reasons why BIM should have a positive impact on the ability of the firm to produce new products and processes.8 Both rely on organizational learning to ‘create’ a stock of knowledge that can be utilized currently and in the future (DARROCH and MCNAUGHTON, 2002; YU-YUAN HUNG et al., 2010). More specifically, LIAO et al. (2010, table 4) sum- marize the arguments put forward by PRAJOGO and SOHAL (2001) and PERDOMO-ORTIZ et al. (2006) where each major element of TQM is mapped onto the set of positive and negative influences it can have on innovation (a comparable mapping between other BIM and innovation would concentrate on just those elements that are relevant to them). SADIKOGLU and ZEHIR (2010, tables 1 and 2) present very similar infor- mation. Thus, ‘customer focus’, where it involves meeting the changing needs of customers, should lead to the development of new products and services and thus offer greater value. However, such a focus can also lead to firms being reactive, more likely to respond through incremental changes and too tied-in to existing customer needs, with the longer-term result being product conformance rather than innovation. People (i.e., management and employee) involvement and teamwork have positive effects by encouraging taking responsibility (empowerment), participation and flexibility in decision-making; greater cooperation and communication; and the use of cross-functional team- work, all of which can lead to new idea generation and risk taking. This aspect of BIM might also stifle non-production activities and individual creativity, such that a lower common denominator-level of improvement becomes more the norm, especially as it involves what has been termed ‘management by fact’ which ‘necessitates a set of data, tools, and techniques with which to analyse the existing system, leading to solutions based on prior experience and inhibiting

2042 Richard Harris et al.

innovative solutions’ (SADIKOGLU and ZEHIR, 2010, p. 15). Continuous improvement encourages change and creative thinking not only in work patterns but also in product improvement. However, negative links to innovation can be workers adopting unambitious goals and standardized working, too much formalization (and thus rigidity), with stable and standard, repetitive systems promoted.

Overall BIM involves different elements, comprising a ‘hard’ focus on efficiency and a ‘soft’ concentration on learning, and this can lead to a mechanistic vis-à-vis an organic approach to how the business operates (MCADAM, 2000). Thus, perhaps it is not surprising that the empirical literature offers contradictory con- clusions. Work by FLYNN (1994), PRAJOGO and SOHAL (2003, 2004), FENG et al. (2006), MARTINEZ- COSTA and MARTINEZ-LORENTE (2008), YU-YUAN HUNG et al. (2010), and SADIKOGLU and ZEHIR (2010) suggests a positive relationship between (specifi- cally) TQM and technological innovation; whereas SINGH and SMITH (2003), PRAJOGO and SOHAL (2004), and TERZIOVSKI and SAMSON (1998) find a negative or non-significant relationship. PERDOMO- ORTIZ et al. (2009) found the relationship to be nega- tive when moderated by various aspects of innovation capabilities (linked to the firm’s absorptive capacity).

Based on the these different elements in (different) BIM, and the mixed results obtained in previous work, there are some who argue that there is a need to distinguish different BIM in terms of their ‘hard’/ ‘soft’ focus in measuring their impacts on innovation.9

In a similar vein, it has been argued (particularly by PERDOMO-ORTIZ et al., 2009) that there is a need to look at the BIM–innovation relationship based on different types of organization (mechanistic versus organic), with those having higher strategic fit (e.g., absorptive capacity) being more likely to see a positive relationship. Thus, the basic model is extended below to test whether different types of BIM (e.g., TQM versus continuous improvement) have different impacts, and whether the BIM–innovation relationship needs to include the mediating role of absorptive capacity or ‘culture’.

As stated in the Introduction, all the existing studies that test whether BIM and innovation are related treat the latter as a single construct, i.e. the firm produces product/process innovations or not. As explained below, a different approach is taken by distinguishing between firms that innovate successfully and those that invest in innovation-related activities but are unsuccess- ful. BIM is thus allowed potentially to impact differently on whether the firm undertakes innovation-related activities or not, and if so whether BIM influences inno- vation outcomes. A structural equation modelling (SEM) approach is also not used (like many other studies). Although the latter is a statistically valid method, the SEM models estimated are usually not fully explained or the results clearly interpreted; rather,

most studies simply established whether a statistically significant relationship existed between BIM and innovation.

Turning to what determines innovation outputs, these are normally, but not exclusively, the result of a decision by the firm to commit relevant resources, par- ticularly by investing in formal R&D;10 this relationship has been extensively examined in the empirical litera- ture (e.g. ACS and AUDRETSCH, 1988; FREEMAN and SOETE, 1997; MAIRESSE and MOHNEN, 2005). When a firm allocates resources (e.g., to R&D) there is no guarantee that the investment will lead to new products or processes, but there is evidence that by undertaking the process of innovation the firm may develop its absorptive capacity by enhancing its capabili- ties and competencies in the accumulation and appli- cation of externally acquired knowledge (COHEN and LEVINTHAL, 1990; TEECE and PISANO, 1998; PAVITT, 1984; SIMEON and MCCANN, 2008). The value of absorptive capacity has been well documented in the litera- ture and is concisely summarized by FABRIZIO (2009). Research by PARISI et al. (2006) provides evidence that the concept of absorptive capacity is important at the firm level – ‘internal R&D helps the firm in absorbing innovations generated outside the firm and embodied in new investment goods’ (p. 2055). ESCRIBANO et al. (2009) considered the impact of absorptive capacity on innovative performance and concluded that ‘it pays dividends, in terms of innovative performance, to invest in enhancing absorptive capacity’ (p. 104); while HARRIS and MOFFAT (2013 have shown that R&D and higher absorptive capacity (with the latter a determi- nant of the former11), inter alia, increase the probability of innovation as well as reducing barriers to exporting (all of which is likely to increase overall firm productivity).

BIM and small to medium-sized firms

Since there are differences between larger and smaller firms in what determines innovation-related activities, and since the importance of BIM is usually considered with reference to large firms,12 it is important to con- sider if the hypothesized links between BIM and innovation as set out above are only likely to be appli- cable to larger firms. It is well documented, for example, that SMEs commit fewer resources to formal R&D,13 and are less formally involved in ‘organizational learning’. For example, FREEL (2000) summarizes earlier work on the various constraints that have a par- ticular relevance for innovation activities in SMEs, noting that

small firms faced constraints associated with: lack of tech- nically qualified labour; poor use of external information and expertise; difficulty in attracting/securing finance and relating inability to spread risk; unsuitability of original management beyond initial prescription; and, high cost of regulatory compliance.

Effect of Business Improvement Methods on Innovation in SMEs in Peripheral Regions 2043

(p. 61)

This is in addition to those studies that show that indi- genous SMEs in peripheral regions are less competitive and innovative in comparison with more centrally located companies (e.g. SKURAS et al., 2008; COOKE, 1996; SODERQUIST et al., 1997); and these geographical limitations are compounded with innate SME skill limitations (PULLEN et al., 2009; PINHO, 2008; VOSSEN, 1999). These include training and develop- ment (JONES, 2005; BARCLAY and PORTER, 2005) and resources (CLARK, 2010; VESTER and BOSHOFF, 2006; NOOTEBOOM, 1994).

Others have pointed to an increasing trend in larger organizations, which are under pressure to make up for shortfalls in existing large-scale markets, targeting niche markets, once the unique preserve of SMEs, offering specialist products and services innovations (KUMAR, 2010). This effect creates the need for change in SMEs beyond that of incremental improvement in efficiency measures (BHASKARAN, 2006) and creates a demand for more radical change in terms of innovation as a sus- tainable source of competitive advantage. GHOBADIAN and GALLEAR (1999) state that SMEs ‘must re-examine and modify their competitive strategies by fully incorpor- ating innovation within their people, processes and pro- ducts’ (p. 121). Hence, as noted in the Introduction, to address these limitations one area of government policy over the past decade has been a focus on using BIM as an enabler of innovation and thus to improve competi- tiveness (CLARK, 2010; FREEL and RODSON, 2004).

PINHO (2008), in one of only a very small number of papers that have examined the relationship between TQM and performance in SMEs (finding no significant link between TQM and innovation14), noted that the latter have been slow in adopting quality initiatives, although noting that while

SMEs are usually associated with lack of competencies and resources, intense competition has forced them to increas- ingly adopt more formal quality system strategies as it is assumed that total quality orientated firms tend to evidence high levels of productivity and competitiveness.

(p. 257)

Indeed, HEWITT-DUNDAS (2006) has examined the resource and capability constraints to innovation in small and large plants in Ireland, finding that such ‘con- straints to innovation are remarkably similar for small and large plants. The only exception to this is the lack of finance, limited market opportunities and legislative or regulatory pressures, which were more significant for small plants’ (p. 273).

Given the discussion of the different elements in BIM, it might be hypothesized that SMEs are – e.g., because of their lack of resources – more likely to use BIM to make a hard focus on efficiency rather than a soft concentration on learning, leading to a mechanistic rather than an organic approach when implementing

such methods. PINHO (2008) goes as far to suggest that ‘the efficiency of continuous improvement may have ultimately minimised and even removed available resources for innovation’ (p. 269).

In conclusion, the above discussion suggests that looking at BIM and innovation for the SME sector is both justified and necessary; it is not an area that is only applicable to large firms, and indeed one of the main pur- poses ofthis study is toconsiderthe size andstrength ofthe impact of BIM on innovation-related activities (broadly defined) in more inherently disadvantaged SMEs.

DATA

In November–December 2009 a telephone survey was conducted of 606 SMEs (employing between 10 and 250 people), covering the border counties of the Republic of Ireland and Northern Ireland, and the West of Scotland (as designated in the EUROPEAN REGIONAL DEVELOPMENT FUND GUIDELINES, 2010).15 The companies were clients of the three gov- ernment development agencies (Enterprise Ireland, Invest Northern Ireland and Scottish Enterprise);16

and as such they were more likely to have developed BIM agendas as a result of assistance provided by the government agencies in these border regions.

The survey focused on whether the respondent firms were engaged in innovation-related activities (defined here as committing resources to developing new pro- ducts, processes or services and/or significantly improv- ing existing products, processes or services, or developing new niches for the firm). The firms’ responses were used to classify them as successful inno- vators (if they had introduced a major product or process innovation in the last three years), unsuccessful innova- tors (if they had engaged in innovation-related activities but had not introduced a major innovation), and non- innovators (they did not innovate or spend on inno- vation-related activities).

Fig. 1 indicates that nearly 45% of firms had intro- duced a major new innovation during 2007–09;17

nearly 23% had engaged in innovation-related activities but without any major new innovation(s); and nearly 33% overall did not engage in innovation-related activi- ties. It also shows the extent to which the sample of firms used BIM and which type. Overall, some 38% of firms were not involved in BIM; of those that used BIM, the most popular was continuous improvement and ISI 9001 (quality management). Some 72% of those firms using BIM were involved in more than one scheme; nearly half used three or more schemes.18

Given that the dependent variable here comprises three subgroups (successful and unsuccessful innovators, plus firms not engaged in innovation-related activities), a multinomial logit model was estimated. Based on the questions asked in the survey,19 a range of variables that potentially influenced innovation-related activities were

2044 Richard Harris et al.

included as determinants. These control for a wide range of influences on innovation and allow one to separate out the impact on innovation activities of BIM.20

These variables are listed in Table 1.21 As can be seen, there was a tendency for firms that engaged in inno- vation-related activities, but which did not innovate, to be more likely to use BIM.

Information was also obtained on factors associated with the life cycle of the firm, its strategic focus, leader- ship, culture, internal and external knowledge processes (the latter proxying absorptive capacity; see HARRIS and LI, 2009, and Table C7 in Appendix C in the sup- plemental data online), and linkages with outside organ- izations. For each area, a set of associated questions were asked with respondents required to rank whether they strongly agreed or strongly disagreed with each state- ment. Factor analysis was then used to extract the orthog- onal information available from each series of questions asked; the number of factors chosen was based on the Kaiser criterion (KAISER, 1960), such that principal com- ponents with eigenvalues greater than 1 were retained. The results of each factor analysis are reported in Tables C1–C8 in the supplemental data online.

RESULTS

The multinomial logit model was initially estimated by including all the variables in Table 1 (preferring BIM – in place 2+ years over BIM – current, although the results are very similar), including ‘depth of BIM’.22 A

test of the null hypothesis that certain variables were jointly insignificant in the model (including the employ- ment size dummy variables) was undertaken (the results are reported in Table 2) and these variables were dropped from the model to avoid over-fitting and the inclusion of ‘nuisance’ variables.23 Table 2 presents the results (marginal effects are reported that indicate the effect of each variable on the probably of belonging to a subgroup); the key result is that (ceteris paribus) firms that used BIM (for two years or more) were some 9.4% more likely to belong to the unsuccessful innovator group, and just over 11% less likely to belong to the non-innovator (‘not engaged in innovation activities’) subgroup.

Taking into account the ‘depth of BIM’ (i.e., it is entered as a composite variable for those firms that had BIM in place for two or more years) allows it to be checked whether there is an additional effect associated with not just having BIM, but also the extent to which it is embedded in the firms’ activities. It was found that firms with more ‘depth’ to BIM are more likely to belong to the unsuccessful innovator subgroup; a 1 SD (standard deviation) increase in the ‘depth’ variable for those with BIM boosts the prob- ability of being an unsuccessful innovator to nearly 15% (i.e., 0.094 + 0.055). There is also some (statisti- cally weaker) evidence that greater ‘depth’ also reduces the likelihood of being a successful innovator (significant at the 15% level).

Table 2 also shows that firms in Northern Ireland were (controlling for all other variables) more likely to

Fig. 1. Percentage of small and medium-sized enterprises (SMEs) engaged in innovation-related activities and use of business improvement methods (BIM)

Source: Data are from the authors’ own survey

Effect of Business Improvement Methods on Innovation in SMEs in Peripheral Regions 2045

be in the non-innovator group (16% higher probability) and less likely to be successful innovators (15% lower probability).24 Those using product design as their com- petitive edge were over 20% more likely to be successful

innovators (17% less likely to be non-innovators); the results for firms where cost-effectiveness dominates was to ‘push’ them into the non-innovator subgroup. Selling in local (export) markets increased (decreased)

Table 1. Definitions of variables

Variable Definition Successful innovator �X

Unsuccessful innovator �X

Non- innovator �X

BIM – in place 2+ years Coded 1 if any business improvement method has been used for two or more years; 0 otherwise

0.552 0.667 0.444

Scotland Coded 1 if the company is located in Scotland; 0 otherwise 0.333 0.384 0.318 N. Ireland Coded 1 if the company is located in Northern Ireland; 0

otherwise 0.300 0.297 0.394

Age Number of years operating in Northern Ireland/Scotland/ Republic of Ireland

25.637 32.399 27.798

Employs < 10 Coded 1 if the company currently employs fewer than 10 people in Northern Ireland/Scotland/Republic of Ireland

0.185 0.181 0.237

Employs 10–15 Coded 1 if the company currently employs 10–15 people in Northern Ireland/Scotland/Republic of Ireland

0.200 0.181 0.242

Employs 16–27 Coded 1 if the company currently employs 16–27 people in Northern Ireland/Scotland/Republic of Ireland

0.193 0.210 0.177

Employs 28–55 Coded 1 if the company currently employs 28–55 people in Northern Ireland/Scotland/Republic of Ireland

0.200 0.217 0.207

Employs 56+ Coded 1 if the company currently employs 56 or more people in Northern Ireland/Scotland/Republic of Ireland

0.222 0.210 0.136

Product design Coded 1 if product design is the single most important factor providing a competitive edge in the next three to five years; 0 otherwise

0.419 0.290 0.162

Cost effectiveness Coded 1 if cost-effectiveness the single most important factor providing a competitive edge in the next three to five years; 0 otherwise

0.181 0.239 0.404

% local sales Percentage of sales to its own region (Northern Ireland/ Scotland/Republic of Ireland)

43.848 56.361 70.004

% exports Percentage of sales to a non-British Isles destination 22.011 11.995 5.374 Family-owned firm Coded 1 if the company is 50% or more family owned; 0

otherwise 0.526 0.543 0.646

Foreign-owned firm Coded 1 if the headquarters of the company is outside its own region of Northern Ireland/Scotland/Republic of Ireland; 0 otherwise

0.096 0.101 0.045

Lifecycle – expansion dominates

PCF based on life cycle questions (see Table C1)a −0.059 −0.041 −0.108

Lifecycle – survival dominates

PCF based on life cycle questions (see Table C1) −0.064 0.024 0.070

Strategy – narrow products and seldom adjusts

PCF based on strategic focus questions (see Table C2) 0.260 0.015 0.345

Strategy – continual search for better

PCF based on strategic focus questions (see Table C2) 0.104 −0.030 −0.121

Leadership – proactive for change

PCF based on leadership questions (see Table C3) 0.159 0.058 −0.257

Culture – strong team and communication

PCF based on culture questions (see Table C4) 0.127 0.057 0.212

Culture – good HRM PCF based on culture questions (see Table C4) 0.031 −0.073 0.009 Depth of BIM PCF based on BIM questions (see Table C5) 0.050 0.138 −0.165 Knowledge-strong internal

structures/processes PCF based on internal knowledge questions (see Table C6) 0.052 −0.095 −0.004

Strong internalization of external knowledge

PCF based on knowledge acquisition questions (see Table C7)

0.269 0.133 0.274

Knowledge acquired from outside bodies

PCF based on knowledge acquisition questions (see Table C7)

0.078 −0.159 −0.005

Strong networking capabilities

PCF based on linkage questions (see Table C8) 0.093 0.046 0.095

Notes: aPrincipal component factor. All appendices are available in the supplemental data online. HRM, human resource management.

Source: Data are from the authors’ own survey (for details, see the supplemental data online).

2046 Richard Harris et al.

the probability of belonging to the non-innovator group and decreased (increased) the probability of being a successful innovator. Family-owned firms were some 7% more likely to be non-innovators (although the impact is statistically weak), while foreign-owned firms tended away from non-innova- tiveness and towards being unsuccessful innovators (pre- sumably as successful innovation occurs ‘at home’). Interestingly, firms faced with issues over whether to expand or not are some 4% less likely to be successful innovators, implying that post-survival growth dampens down product innovation. However, firms with a narrow product range that are opposed to change are considerably more likely to be non-innova- tors and less likely to be successful innovators. A strong team and change culture, and higher absorptive capacity (associated with acquiring and internalizing external knowledge) has the opposite effect by facilitating suc- cessful innovation and moving firms away from being not engaged in innovation-related activities; while being more likely to acquire knowledge from outside bodies increases the likelihood of successful innovation but decreases the probability of being an unsuccessful

innovator. Lastly, the industries listed in Table 2 are more (less) likely to be associated with successful (unsuc- cessful) innovation.

For the reasons set out in the literature review, the basic model is extended to test whether different types of BIM (e.g., TQM versus continuous improvement) have different impacts, and whether the BIM–inno- vation relationship needs to include the mediating role of absorptive capacity or culture. Table 3 first presents results when only the variable ‘BIM – in place 2+ years’ is included, with ‘depth of BIM’ excluded (to make comparisons with other models easier). The results for the other determinants of innovation are omitted, but these generally do not change much from model to model.

The third model in Table 3 shows that allowing BIM to be moderated via an indicator of absorptive capacity (the principal component factor measuring ‘strong internalization of external knowledge’) has little impact on the results obtained. Even though the com- posite variable has a significant, negative relationship with belonging to the ‘not engaged in innovation activi- ties’ subgroup, this is at the expense of the (not shown)

Table 2. Marginal effects from multinomial logit model of innovativeness

Variables

Successful innovator Unsuccessful innovator

Not engaged in innovation activities

�X∂p/∂x z-value ∂p/∂x z-value ∂p/∂x z-value

BIM – in place 2+ years 0.017 0.32 0.094 2.20 −0.111 −2.30 0.543 BIM – in place 2+ years × Depth of BIM −0.066 −1.46 0.055 1.64 0.010 0.26 0.303 Scotland −0.061 −0.97 0.044 0.86 0.017 0.30 0.340 N. Ireland −0.154 −2.58 −0.004 −0.08 0.158 2.69 0.330 Agea −0.032 −1.06 0.028 1.58 0.004 0.19 27.883 Product design 0.203 3.77 −0.033 −0.76 −0.170 −3.74 0.305 Cost effectiveness −0.051 −0.82 −0.066 −1.46 0.116 2.11 0.267 % local salesa −0.084 −2.69 0.002 0.07 0.082 2.91 55.244 % exportsa 0.073 2.27 −0.006 −0.24 −0.067 −1.91 14.295 Family-owned firm −0.021 −0.42 −0.047 −1.14 0.068 1.56 0.569 Foreign-owned firm 0.055 0.57 0.134 1.45 −0.190 −3.40 0.081 Lifecycle – expansion dominatesb −0.039 −1.54 0.016 0.81 0.023 1.03 0.000 Strategy – narrow products and seldom adjustsb −0.108 −4.20 0.016 0.81 0.092 4.20 0.000 Culture – strong team and communicationb 0.055 2.05 0.024 1.15 −0.079 −3.47 0.000 Strong internalization of external knowledgeb 0.143 5.26 −0.064 −3.06 −0.079 −3.40 0.000 Knowledge acquired from outside bodiesb 0.049 1.92 −0.053 −2.65 0.004 0.16 0.000 Manufacture of food, beverages and tobacco 0.192 2.49 −0.125 −2.58 −0.067 −1.05 0.104 Manufacture of rubber and plastic products 0.311 2.70 −0.233 −6.95 −0.078 −0.70 0.030 Man. of other non-metallic mineral products 0.282 1.97 −0.187 −2.85 −0.095 −0.74 0.017 Manufacture of machinery and equipment n.e.c. 0.160 1.87 −0.079 −1.41 −0.081 −1.11 0.089 Manufacture of transport equipment 0.103 0.59 −0.185 −2.74 0.083 0.49 0.020 Manufacturing not elsewhere classified 0.129 1.71 −0.157 −3.71 0.028 0.39 0.127

p̂ 0.463 0.244 0.293 N 606 Pseudo-R2 0.193 Log-likelihood −519.447 H0: omitted variables = 0 (x228d.f .) 16.52 Notes: aAll continuous variables are measured with respect to a standard deviation (SD) increase in X.

bAll principal component factors (PCFs) were measured with respect to the mean of the variable (results are very similar to measuring with respect to an SD increase in X since the mean and SD of PCFs is 0 and 1, respectively).

n.e.c., Not elsewhere classified.

Effect of Business Improvement Methods on Innovation in SMEs in Peripheral Regions 2047

absorptive capacity variable becoming insignificant in the rest of the model. Similarly, including ‘culture’ to moderate the relationship between BIM and innova- tiveness is not significant.

Any differences across the three regions covered was also checked: for Northern Ireland (note, not the Republic of Ireland) just engaging in BIM for the last two years strengthens the likelihood that firms become unsuccessful innovators. But when this is coupled with greater depth of BIM, then Table 3 (the last set of results) shows that there is some evidence that SMEs in the Republic of Ireland with greater ‘depth’ are more likely to be successful rather than unsuccessful innovators.

Lastly, BIM was limited only to cover the two most popular models – TQM and continuous improvement – to allow for any ‘hard’ and ‘soft’ impacts of BIM. The results from including only TQM are much weaker, which might suggest that a ‘soft’ concentration on learn- ing (which is more likely to be associated with TQM) does lower the likelihood of becoming an unsuccessful innovator, but it also lowers the probability of moving

away from a firm not engaging in innovation-related activities (i.e., usually TQM is multifunctional and con- tinuous improvement is typically focused on a unitary area which causes differences in the learning potential). Limiting BIM to a ‘harder’ focus on efficiency also has only a small impact on the results obtained, although there is some evidence that it results in a slightly stronger push into becoming an ‘unsuccessful’ innovator, which is consistent with a priori expectations.25

CONCLUSIONS

This study seeks to contribute to the relative paucity of studies on the effects of business improvement methods (BIM) on innovation in client SMEs located in periph- eral regions that are directly helped by regional develop- ment agencies, while at the same time controlling for a wide range of other (standard) determinants of inno- vation outcomes. The increased pressure on SMEs in underperforming regions to implement innovation to remain competitive, particularly in times of economic

Table 3. Marginal effects from various multinomial logit models of innovativeness (based on a full sample of 606 observations)

Variables

Successful innovator

Unsuccessful innovator

Not engaged in innovation activities

�X∂p/∂x z-

value ∂p/∂x z-

value ∂p/∂x z-

value

Baseline model BIM – in place 2+ years −0.021 −0.42 0.124 3.26 −0.103 −2.40 0.543

Preferred model (see Table 2) BIM – in place 2+ years 0.017 0.32 0.094 2.20 −0.111 −2.30 0.543 BIM – in place 2+ years × Depth of BIM −0.066 −1.46 0.055 1.64 0.010 0.26 0.303

Moderated by absorptive capacity BIM – in place 2+ years −0.021 −0.43 0.138 3.55 −0.116 −2.68 0.543 BIM – in place 2+ years × Strong internalization of external knowledge 0.049 0.93 0.043 1.02 −0.092 −2.08 0.025

Moderated by culture BIM – in place 2+ years −0.021 −0.42 0.123 3.24 −0.103 −2.39 0.543 BIM – in place 2+ years × Culture – strong team and communication −0.009 −0.18 −0.000 −0.01 0.009 0.22 0.017

Limiting BIM to TQM TQM – in place 2+ years −0.041 −0.75 0.077 1.63 −0.036 −0.75 0.243

Limiting BIM to continuous improvement Continuous improvement – in place 2+ years −0.051 −1.00 0.140 3.21 −0.089 −2.04 0.338

Moderated by location BIM – in place 2+ years 0.049 0.59 0.107 1.73 −0.157 −2.04 0.543 BIM – in place 2+ years × located in Northern Ireland −0.134 −1.17 0.073 1.67 0.061 0.54 0.173 BIM – in place 2+ years × located in Republic of Ireland −0.080 −0.67 −0.017 −0.18 0.097 0.81 0.198

Moderated by location BIM – in place 2+ years −0.003 −0.04 0.113 2.63 −0.111 −2.24 0.543 BIM – in place 2+ years × Depth of BIM −0.126 −1.89 0.148 3.03 −0.022 −0.37 0.303 BIM – in place 2+ years × Depth of BIM × located in Northern Ireland 0.046 0.09 −0.153 −2.21 0.107 1.29 0.106 BIM – in place 2+ years × Depth of BIM × located in Republic of Ireland 0.206 2.02 −0.196 −2.61 −0.010 −0.11 0.142

Note: TQM, total quality management.

2048 Richard Harris et al.

downturn, has led to a need to probe the role of BIM in stimulating increased innovation implementation at more radical levels (i.e., by increasing technological improvements and not just improvements in efficiency).

Given the current extensive ‘push’ by regional devel- opment agencies to use BIM, as well as government policy more generally to extend their take-up, in the belief that this will improve efficiency and innovative- ness (i.e., productivity), it is important to test whether BIM fosters or inhibits innovation. The findings show that on average adopting BIM diverts assisted SMEs away from successful innovation (i.e., especially in terms of new products/services in the past three years), and instead is associated with undertaking innovation- related activities while remaining non-innovators. Indeed, reinforcing BIM (through greater ‘depth’ of use) may lead to further exclusion from successful inno- vation, especially in Northern Ireland.

The findings are therefore relevant for existing policy, and whether the latter is in fact in a majority of existing cases truncating product innovation in those SMEs government agencies that are trying to help become more innovative. Thus, the implications for business development agencies are significant, and it could be argued they need a clearer understanding of BIM and to monitor carefully the impact of BIM when they provide assistance to firms. They need to be clearer on how BIM is ‘sold’ to clients (e.g., what is the intended outcome – is the emphasis on learning or efficiency? – and is this achieved?). This raises the question of whether agencies need to adjust the way they promote BIM. Thus, the results from this study will be useful in developing a wider understanding of how government agencies, SME managers and the con- sultants employed by both can effectively use scarce resources to improve innovation implementation and hence competitiveness without necessarily having to trade-off efficiency and technology gains.26

The review of BIM suggests there is no inherent reason to expect a trade-off between efficiency and innovation, as long as such practices are used, for example, as an integrative philosophy of management for continuously improving the quality of products and processes, and as long as they concentrate on increased organizational learning to ‘create’ a stock of knowledge that can be utilized by the firm now and in future (rather than just the exploitation of existing knowledge). The alternative is standardization of the production process (cf. WRIGHT et al., 2012), which while it creates order and offers the potential for improved performance via routinization, simplification and cost economies, the outcome is usually the antithesis of innovation. Thus, being aware of the potential posi- tive and negative aspects of the BIM–innovation nexus is a necessary ingredient when devising and, more importantly, implementing innovation policy.

There are a number of limitations to this study that could be addressed in future work. Clearly, it would

be useful to extend the analysis not just to peripheral regions of Scotland and Ireland (north and south), but also to include SMEs that were not the clients of public agencies27 who are attempting to improve com- petitiveness in the firms being studied. The role of design in determining innovation-related activities was not explicitly covered, which given its importance (NATIONAL ENDOWMENT FOR SCIENCE, TECHNOL- OGY AND THE ARTS (NESTA), 2009) is an area to include in future work.

Disclosure statement – No potential conflict of interest was reported by the authors.

Supplemental data – Supplemental data for this article can be accessed at http://dx.doi.org/10.1080/ 00343404.2015.1083971

NOTES

1. A number of studies (e.g. MELANÇON and DOLOREUX, 2013; SKURAS et al., 2008; COOKE et al., 1997) have shown that SMEs from peripheral regions are likely to be less competitive and innovative in comparison with more centrally located companies.

2. For example, total quality management (TQM), ISO: 9001:2008, continuous improvement, lean, Investors in People and Six Sigma (see BESSANT and TIDD, 2011, for a discussion).

3. EEF (2008) estimate that just under three-fifths of UK manufacturing was using lean in 2008 (with 41% take- up in those employing fewer than 50 rising to over 70% in those employing 500 or more). The Workplace Employee Relations Survey for 2004 (for Great Britain) shows that some 36% of plants benchmark against other organizations, 17% use quality circles (which can include continuous improvement, and other forms of problem-solving groups), and 37% have an Investors in People award.

4. For example, Scottish Enterprise provides an especially intensive form of support to account and client managed firms (commonly referred to as ‘direct relation- ship management’ companies) that are considered to be capable of benefiting from a high level of attention. They are companies with a proven or likely higher growth potential. Each company is regularly reviewed by a ‘client-manager’ with the company offered the most appropriate (in-house) training, courses or pro- grammes. Invest Northern Ireland and Enterprise Ireland follow a similar approach.

5. For example, HARRIS and TRAINOR (1995) collected information on 140 manufacturing firms operating in Northern Ireland in 1991; Roper and associates have used the Irish Innovation Survey (IIS), which has several waves comprising between 750 and 1055 manu- facturing plants (including non-SMEs) operating in Ireland and Northern Ireland; HARRIS and TRAINOR (2011) used 250 matched manufacturing plants in

Effect of Business Improvement Methods on Innovation in SMEs in Peripheral Regions 2049

Northern Ireland. None of the datasets is claimed to be representative of the population of SMEs operating in (Northern) Ireland. For example, the IIS reports levels of product innovation that are around twice the levels reported in the results from the Community Innovation Surveys conducted in each area.

6. Appendix A in the supplemental data online also discusses ‘Other determinants of innovation activities’.

7. For example, GRANT et al. (1994) state ‘TQM comprises a group of ideas and techniques for enhancing competi- tive performance by improving the quality of products and processes’ (p. 20).

8. The BIM–innovation relationship can be simultaneous and complementary, but it is often argued that ‘in general business practice first incorporates the concept of quality management and then gradually integrates innovation’ (PERDOMO-ORTIZ et al., 2009, p. 5088). The theoretical underpinning for this is the resource- based and dynamic capabilities (RDBC) view, which incorporates an evolutionary view of management priori- ties being path dependent with the ‘quest for innovation performance (requiring) greater organizational complex- ity than that for quality’ (p. 5088). The literature cited to back up such claims includes FOSS (1993), TEECE et al. (1997) and HODGSON (1998). Note that below this paper also tests the links between BIM and innovation using a ‘matching’ approach that mitigates against any bias from that part of a simultaneous relationship due to self-selection issues.

9. Although note that this distinction is not universally accepted as some influential studies – such as UTTERBACK (1971) and FREEMAN (1982) – suggest that so-called hard BIM practices support innovation performance.

10. This paper does not limit innovation inputs to R&D, as many SMEs do not engage in such (formal) activities. Therefore, the present empirical work simply asked firms to state if they were engaged in innovation- related activities, which were defined for them as com- mitting resources to developing new products, processes or services and/or significantly improving existing pro- ducts, processes or services, or developing new niches for the firm.

11. At a practical level, studies point to the critical role of R&D investment and training that firms undertake in order to absorb, assimilate and manage foreign technol- ogies (MOWERY and ROSENBERG, 1989; COHEN and LEVINTHAL, 1989, 1990; GLOBERMAN, 2000). Thus, R&D is often used as a proxy measure of absorptive capacity, but clearly when using this concept to explain why firms undertake innovation-related activities (including R&D) it is necessary to measure absorptive capacity in a more specific way, which is done below when more direct proxies for absorptive capacity are introduced.

12. Although it was found that over 60% of the sample of SMEs used at least one form of BIM (see Fig. 1). In addition, AHIRE and GOLHAR (1996) surprisingly found that the size of the firm was not a critical factor in the implementation of TQM.

13. See note 7 above. 14. Pinho studied manufacturing plants in Portugal; in a

different study, SÁ and ABRUNHOSA (2007) looked at the Portuguese footwear industry (again finding a low

linkage between TQM and innovation). CLARK (2010) considered the case of 95 SMEs in New Zealand, again finding little evidence supporting a link.

15. There is often an issue in collecting survey data about the impact of self-reported information (studies have suggested this can lead to bias; e.g., CASSAR, 2010; STOREY, 2011; FRASER et al., 2007). The study was part of a larger European Union-funded study involving SMEs and so early on in the project, when devising the questionnaire, the authors engaged in face-to-face inter- views with a small number of the firms in each region to satisfy themselves that the information being supplied was accurate.

16. The development agencies provided access to their SME client companies operating in the relevant areas (1334 for Northern Ireland, 346 for the Republic of Ireland and 495 for Scotland). A random sample of these SMEs was used for the telephone surveys and the responses were tested based on industry and size characteristics to ensure the samples were representative of the population of client firms operating in each region.

17. There were a small number of innovating firms (12%) that had introduced only a process innovation and not a product innovation as well; the majority of innovators (88%) had introduced a product innovation, and over 68% of innovators had introduced both a product and a process innovation. The authors experimented with clas- sifying innovators as successful/non-successful product innovators separately from successful/non-successful process innovators, and while there are small differences in the parameter estimates obtained, the overall con- clusions remain unchanged.

18. Although not shown in Fig. 1, firms in the Republic of Ireland tended to have a higher use of some of the differ- ent types of BIM (e.g., 29% used TQM versus 26% across firms in all three areas; 42% used continuous improve- ment vis-à-vis 37% for all firms). However, the use of different forms of BIM is comparable (continuous improvement was the most popular in all areas, followed by ISO 9001 and TQM). The authors therefore believe these BIM schemes were of similar (international) com- position in all three areas covered, although further work needs to be done in order to confirm this.

19. See Appendix D in the supplemental data online for the questions asked.

20. As the authors only had access to cross-sectional data (as is usually the case in studies of this kind that rely on the col- lection of new information on variables of interest that are generally not available elsewhere), one cannot con- sider time-varying issues such as the pre- and post- impact of the introduction of BIM on innovation, or test (using instrumental variables, or similar, approaches) whether there is any systematic bias to the relationships estimated between BIM and innovation because of endo- geneity issues (due to causality going in both directions) (although see note 8 above). Therefore, it could be argued that the results are possibly only indicative of rel- evant associations between the variables concerned, and potentially biased in magnitude. However, a ‘matching’ approach that should limit any bias due to possible simul- taneity was also used.

21. Thirty-three industry dummy variables are omitted from Table 1.

2050 Richard Harris et al.

22. Such ‘depth’ was measured using factor analysis based on agreement with statements such as whether there were clear goals for total quality/continuous improvement programmes, it was spread throughout the organization, adequately resourced, involved the majority of workers, etc. (see Table C5 in the supplemental data online).

23. The authors agree with a referee who stated that one might expect size effects to be significant; however, this paper only deals with SMEs and not larger firms where the relationship between size and adoption of BIM is stronger.

24. Employment size dummies were not significant in the model and therefore dropped.

25. It could be argued that there is an internal contradiction with different BIM. For as long as learning – absorptive capacity and other proxies – is a feature of BIM, then the likelihood of SMEs being innovators is enhanced, though not guaranteed. The problem seems to be with the efficiency element and its relative emphasis in the BIM used by firms. Thus, perhaps it is not surprising

that certain BIM lead to unsuccessful innovation. For example, some are innovation (continuous improve- ment) whilst others are explicit tools/frameworks for innovation (balanced scorecard), or not. Others are mix- tures (TQM). Lastly, the authors experimented with other specifications of the key BIM variables, but the results were always weaker. Some robustness checks are included allowing for selection effects in Appendix B in the supplemental data online.

26. In 2012 the authors fed-back the results through presen- tations to Scottish Enterprise, Invest Northern Ireland and Enterprise Ireland.

27. That is, it is possible that SMEs that are not clients of regional development agencies and adopt BIM may experience a different outcome to that found herein, and it is also possible that SMEs in other peripheral regions could also have different BIM–innovation relationships. A priori this is thought unlikely, but it would be useful to test whether the results presented here can be generalized.

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