What are the intangible resources of an Organisation?

2.1 IRs as the focal point of the RBV

The RBV scholars (Barney, 1991; Kor and Mesko, 2013) claim that IRs cannot be readily obtained in the factor markets and copied by competitors easily. Along with several researchers (Dierickx and Cool, 1989; Peteraf and Barney, 2003), Barney (1991) proposed that the sources of inimitability can be explained by three isolating mechanisms: historical uniqueness, causal ambiguity and social complexity. In addition to these mechanisms, time compression diseconomies and interconnectedness have been widely discussed in strategic management literature (Dierickx and Cool, 1989; Bharadwaj, 2000).

Historical uniqueness refers to “unique historical events such as a firm’s founding, being taken over by a firm sometime in the past by legendary managers or owners, emergence of the unique, valuable organisational culture in the early stages of a firm’s history, choice of facility location decisions which created distinctive location advantages in the following years and choice of market entrance decisions as a first mover, that determined the long-term performance of the firm” (Barney, 1991, p. 108). These unique historical conditions endowed firms with resources that cannot be controlled by rivals and that cannot be imitated.

Causal ambiguity refers to “the ambiguity surrounding the connection between a firm’s resource portfolio and its performance” (Bharadwaj, 2000, p. 171). Barney (1991) suggests that causal ambiguity exists when the link between its resources and sustained competitive advantage is not understood by competing firms. In this situation, it is very difficult for imitating firms to duplicate a successful firm’s strategies since they do not understand exactly what makes a firm successful. Social complexity can be found where resources are based on complex social phenomena (Barney, 1991, Eesley et al., 2014) and it significantly constraints the ability of other firms to imitate these resources. Socially complex resources such as interpersonal relations among managers, corporate reputation of a firm among customers and suppliers and organisational culture are imperfectly imitable because, although it may be possible for competitors to specify and replicate (or engineer) these resources, there is no guarantee that they can achieve similar valuable benefits since socially complex resources are not subject to direct and standard management (Barney, 1991). In a similar line, the elements of intellectual property assets such as copyrights, patents, registered designs and trademarks that provide legal protection to firms preserve the economic benefits of the firms from being eroded and cannot be duplicated by competitors (Chari and David, 2012; Grimpe and Hussinger, 2014). Unique organisational culture can be a great source of competitive advantage since it has strong roots with being different, more creative and innovative (Gupta et al., 2017). Through possession of complex and inimitable organisational culture which always supported its employees use their skills freely, Sony, Virgin and Apple became among the most innovative firms in global markets. Moreover, as an example of presenting how value creation ability has shifted from TR to IR, Apple has changed its business from selling hardware to selling design and emotions with its aesthetically pleasing products such as the candy-coloured iMac, the diminutive iPod Nano and the legendary iPhone and iPad.

Another mechanism time compression diseconomies which is related to “the observed tendency of the costs of resource accumulation to rise within a given time interval” (Lockett et al., 2009, p. 15) has also been widely mentioned in the literature. According to Dierickx and Cool (1989, p. 1507), time compression diseconomies refers to “the time needed to develop resources through learning, experience, firm-specific knowledge or, trained proficiency in a skill”. Dierickx and Cool (1989) argue that the inimitability of a resource is linked to the characteristics of the resource accumulation process. For example, organisational culture is such a unique IR that can be difficult for competitors to replicate since it possesses the conditions of asset specificity and time compression diseconomies (Dierickx and Cool, 1989; Lockett et al., 2009). Corporate reputation as an IR involving an external overall evaluation of firms’ actions and past performance in creating stakeholder value (Dowling, 2016) can be accrued in the minds of stakeholders over time. Research (i.e. Wei et al., 2017; Raithel and Schwaiger, 2015) found that because of its unique and complex nature, favourable corporate reputation was linked to firm performance and helped firms sustain competitive advantage in the markets. Similarly, sophisticated in-secret technology for the manufacturing firms (or service know-how for the services firms) may also become a socially complex and causally ambiguous resource over time. A similar and good example to the creation of competitive advantage through this kind of an in-secret technology ownership is “the cross-docking system of retail giant Wal-Mart” (Galbreath, 2004, p. 121). In the early years of Wal-Mart, whilst supply chain software of the firm contained commodity-type of information technologies that can be obtained easily in the factor markets, the system underwent such a complex customisation over years that none of the competitors could afford to imitate it. In a more recent study, Arend et al. (2014) who point knowledge as the most strategically important firm resource found that socially complex embedded internal knowledge were significantly correlated on firms’ survival, return on asset (ROA), and Tobin’s q of firms.

Interconnectedness which was discussed by Dierickx and Cool (1989) refers to “the value of a resource being inexplicably linked to the presence of another complementary or co-specialised resource” (Bharadwaj, 2000, p. 171). Lockett et al. (2009) explain resource interconnectedness as the link between the existing stock of resources and the cost of adding an increment of another resource to the firm’s stock. The closer and more complicated the link, the more difficult for rivals to understand the process and to imitate the competitive resource. A manufacturer which lowers its new product development costs via feedback benefits derived from the same firm’s customer service department can be a good example for value creating and imitation preventing resource interconnectedness (Dierickx and Cool, 1989).

Consequently, given their unique nature that stems from social complexity, causal ambiguity, path-dependency, historical uniqueness, and asset specificity, IRs that offer economic benefits to firms which cannot be easily acquired and replicated should have a higher impact on firm success than tangible assets. Therefore, this study offers the following hypothesis:

H1.

IRs will make a larger contribution to firm performance than that of TRs.

2.2 Capabilities as the dynamic enabling mechanisms

The dynamic capabilities (DCs) perspective posits that the organisations must integrate and reconfigure their resources and capabilities to renew or alter their resource mix to be able to cope with environmental changes (Teece, 2007; Helfat and Peteraf, 2015). Several empirical studies identified specific examples of DC such as customer relationship (Chari and David, 2012), supply chain management (SCM) (Barney, 2012), client-specific capabilities (Weigelt, 2013), managerial ability (Helfat and Peteraf, 2015) and geographical and network ties (Ozer and Zhang, 2015). Although different researchers identified different types of capabilities, the most common point that can be inferred from these identifications is that DCs are managerial and organisational processes and their basic role is “to assess the firm’s extant resource base and transform it to create a new configuration of resources that can sustain competitive advantage” (Ambrosini and Bowman, 2009, p. 32).

Compared to TR and IR, capabilities certainly remained the most amorphous and complicated to define among the constructs that constitute the RBV (Galbreath, 2004; Di Stefano et al., 2014). However, despite this complexity, the RBV scholars have had a common point that human capital (Coff and Kryscynski, 2011; Ployhart and Moliterno, 2011; Kor and Mesko, 2013; Chatterji and Patro, 2014), networking capabilities (Acquaah, 2012; Weigelt, 2013; Ozer and Zhang, 2015) and business processes (Ray et al., 2004, 2013; Hult et al., 2007; Barney, 2012; Weigelt, 2013) were the most influential as well as vital capabilities on the way of creating performance through building, coordinating, integrating and reconfiguring organisational resource bases and competencies of firms (Teece, 2007).

3.1 Sample and informant selection

The sample was selected from the database of Istanbul Chamber of Industry (ISO) that announced the largest 1,000 firms of Turkey (ISO-1000) from different sectors annually (ISO-1000 Database, 2016). The sample designed for multiple research purposes was the best available and relevant sample that could be found in the country. Therefore, the largest 1,000 firms of 2015 were chosen and the valid names and e-mails of senior-level executives of the companies were obtained for this study. The CEO or an equivalent top manager who deal with strategy issues and have adequate knowledge to assess the firm’s resource base and authority to answer the questions is chosen as the key informant (Hall, 1992; Galbreath and Galvin, 2006, 2008). Because the unit of analysis in this study was at the firm level, a single informant was used and the questionnaire was mailed to only one executive from each firm.

3.2 Administration of survey

A cross-sectional survey research design was used in the study. The measurement instrument was pre-tested by administrating a pilot study in order to assess the wording and construct reliability and validity (Saunders et al., 2007). The pilot study was conducted on a sample of 42 MBA students in a foundation university in Istanbul. The participants were middle- and lower-level managers who had sufficient knowledge about the objectives of the research. The questionnaire included some space at the end of the last section for the feedback of the respondents about how the measurement instrument could be improved. No difficulty to understand the questionnaire was observed. After the pilot study, the questionnaires were sent to the e-mail addresses of the top level executives as a web-link with a covering letter that assures the privacy and confidentiality of respondents. Three weeks after the initial mailing, a reminder follow-up e-mail was also sent to be able to increase the response rate of the study (Saunders et al., 2007). A total of 243 useable questionnaires were obtained, yielding a response rate of 24.3 per cent. The details about the composition of the sample are provided below.

3.3 Measurement instrument

The modified version of Galbreath and Galvin’s (2008) resource-performance questionnaire which was mainly developed based on the studies of Carmeli and Tishler (2004), Fahy (2002), Spanos and Lioukas (2001) and Hall (1992) was employed in this study. The questionnaire included a total number of 45 questions: 27 questions to measure the effects of resources including both tangibles and intangibles, and capabilities, 12 questions to control the effects of industry structure factors, three questions to measure market and financial performance, and two questions for the demographics (age and size). And the last question aimed to categorise the primary business activity of the firms. The items of the questionnaire were mentioned below and presented in Table IV.

3.4 Reliability and validity tests

Cronbach’s α coefficients were calculated to test the reliability of the constructs. The constructs that had α values equal to and above 0.70 were accepted as reliable constructs (Hair et al., 2009). In order to meet the minimum coefficient threshold and gain highest possible reliability, two items were dropped. Whilst “the legally-protected designs” item was eliminated from the IRs construct, “the fixed cost structure required to compete” was dropped from the control variable construct. Table V shows each construct and its Cronbach’s α value.

Factor analysis, as a common method, was used to examine construct validity. Factor analysis yielding five factors revealed that all items exceeded the cut-off point 0.50 (Hair et al., 2009). Whilst the whole scale indicated a Cronbach’s α reliability value of 0.839, Cronbach’s α values of the constructs’ scales were also fairly high: dependent variable – firm performance (0.862), TRs (0.813), capabilities (0.804), IRs (0.749), and control variable – industry structure factors (0.738). The result of the factor analysis is depicted in Table VI.

3.5 The methodology

The data were analysed by the computer software “Statistical Package for the Social Science” (IBM – SPSS®) version 22.0. Apart from the results of the correlation matrix, variance inflation factor (VIF) scores were also calculated for checking the multicollinearity problem. The VIF scores were below the score recommended as problematic, which is 5 (Hair et al., 2013). Furthermore, the results of Kolmogorov-Smirnov test proved that the data were normally distributed. In order to test the established hypotheses, hierarchical regression analysis was used. In hierarchical regression method, each set of independent variables is entered into separate blocks for analysis and the incremental changes of the R2 statistics are calculated. Hence, the explanatory power or in other words, the unique contribution of each independent variable in explaining dependent variable is explored (Hair et al., 2013).

4.1 H1

Model 1 shows the separate effects of control variables (age, size and industry factors) along with the TRs and their explanatory power in firm performance (see Table VIII). Namely, without other variables, age, size, industry factors and TR explained 12.6 per cent ((R2=126); (F=2.345, p<0.05)) of sales turnover, 8.9 per cent ((R2=0.089); (F=1.438, p<0.01)) of market share and 13.9 per cent ((R2=0.139); (F=2.998, p<0.001)) of profitability.

Having entered the IRs variable to model 2, the variations in sales turnover, market share and profitability increased to 15.7 per cent ((R2=0.157); (F=2.761, p<0.05)), 10.4 per cent ((R2=0.104); (F=1.663, p<0.05)) and 18.1 per cent ((R2=0.181); (F=3.586, p<0.01)), respectively. Thus, entrance of the IR variable provided an additional and significant explanation power 3.1 per cent (ΔR2=0.031) for sales turnover, 1.5 per cent (ΔR2=0.015) for market share and 4.2 per cent (ΔR2=0.042) for profitability in model 2.

IRs make a unique, individual contribution to firm performance after accounting for the effects of TRs and the control variables (see Table VIII). Across all three performance measures, the IR β coefficients are the largest and significant compared to the TR β coefficients.

Sales turnover; TR (β=0.194, t=2.745, p<0.001); IR (β=0.236, t=2.988, p<0.001).

Market share; TR (β=0.078, t=1.367, p<0.01); IR (β=0.122, t=2.174, p<0.01).

Profitability; TR (β=0.379, t=3.055, p<0.001); IR (β=0.475, t=3.269, p<0.001).

Given the analysis results, IRs are positively associated with all performance measures and make a larger contribution to firm performance than TR. Thus, H1 is supported.

4.2 H2

Having entered the capabilities variable (CAP) to model 2, significant changes in R2s were observed across all dependent variables (see Table VIII). The variations in sales turnover, market share and profitability increased to 14.9 per cent ((R2 =0.149); (F=2.598, p<0.05)), 11.8 per cent ((R2=0.118); (F=1.742, p<0.01)) and 21.4 per cent ((R2=0.214); (F=4.136, p<0.01)), respectively. Entrance of the CAP variable provided an additional and significant explanation power 2.3 per cent (ΔR2=0.023) for sales turnover, 2.9 per cent (ΔR2=0.029) for market share and 7.5 per cent (ΔR2=0.075) for profitability in model 2. Therefore, CAP account for significant additional exploratory power to the prediction of the dependent variables after simultaneously accounting for the effects of TR and the control variables.

CAP have the largest β coefficients of any of the independent variables in the regression model (see Table VIII). In H2, CAP have a larger β coefficient across all of the performance measures, than TR as shown below.

Sales turnover; TR (β=0.178, t=2.431, p<0.01); CAP (β=0.304, t=3.247, p<0.01).

Market share; TR (β=0.063, t=1.184, p<0.01); CAP (β=0.156, t=2.105, p<0.01).

Profitability; TR (β=0.204, t=2.446, p<0.01); CAP (β=0.498, t=3.507, p<0.01).

These results suggest that CAP are positively associated with all performance measures and more important to explaining firm performance than TR. Therefore, the findings of the analysis offer support for H2.

4.3 H3

The addition of CAP to model 2 that includes control variables along with IR results significant changes in R2s across all performance measures (see Table VIII). The variations in sales turnover, market share and profitability increased to 16.5 per cent ((R2=0.165); (F=2.087, p<0.01)), 12.4 per cent ((R2=0.124); (F=1.865, p<0.01)) and 20.3 per cent ((R2=0.203); (F=3.631, p<0.001)), respectively. Entrance of the CAP provided an additional and significant explanation power 1.4 per cent (ΔR2=0.014) for sales turnover, 2.1 per cent (ΔR2=0.021) for market share and 2.7 per cent (ΔR2=0.027) for profitability in the regression model. Thus, CAP account for significant additional exploratory power to the prediction of the dependent variables after simultaneously accounting for the effects of IR and the control variables.

With regard to the unique, individual contribution of CAP to explain performance relative to the other independent variables, the results were mixed (see Table VIII). For sales turnover, the β coefficient for CAP was β=0.239 (t=3.002, p<0.05) which was smaller than IR coefficient of β=0.276 (t=3.134, p<0.05). Similarly, for market share, the β coefficient for CAP was β=0.135 (t=1.184, p<0.01) which was also smaller than IR coefficient of β=0.147 (t=2.336, p<0.01). For profitability, the β coefficient for CAP was β=0.363 (t=3.198, p<0.01) compared to IR coefficient of β=0.287 (t=2.165, p<0.01). Given these results, CAP make larger contributions in only one of the three dependent variables that is profitability. Thus, the findings of the analysis offer only partial support for H3.

4.4 H4

The addition of CAP to the model including the control variables along with the combined contributions of TR and IR results significant R2 change only for profitability (see Table VIII). Whilst entrance of the CAP increased explanation power of the model significantly from R2=0.181 to R2=0.209 ((ΔR2=0.028); (F=02.884, p<0.01)) for profitability, R2 changes in sales turnover and market share were non-significant. Hence, in only profitability do CAP account for significant additional explanatory power to the prediction of firm performance after simultaneously accounting for the effects of both TR and IR along with the control variables.

With regard to the unique, individual contribution of CAP to explain performance relative to TR and IR, the results were weak (see Table VIII). For sales turnover, the β coefficient for CAP was β=0.129 (t=1.645, p<0.01) which was smaller than IR coefficient of β=0.143 (t=1.878, p<0.01) and slightly larger than TR coefficient of β=0.126 (t=1.532, p<0.05). For market share, the β coefficient for CAP was β=0.121 (t=1.629, p<0.01) which was again smaller than IR coefficient of β=0.152 (t=1.965, p<0.01) but larger than TR coefficient of β=0.056 (t=1.418, p<0.01). For only profitability, the β coefficient for CAP was β=0.311 (t=2.881, p<0.01) larger compared to β=0.109 (t=1.769, p<0.05) of TR and β=0.262 (t=2.477, p<0.01) of IR.

Given these results, CAP make larger contributions in only one of the three dependent variables that is profitability. Thus, the findings of the analysis do not offer support for H4.

Based on the results of the statistical analysis, only two hypotheses that posited the larger contributions of IRs (H1) and capabilities (H2) on firm performance compared to TRs were fully accepted. Whilst the data that were analysed offered only a partial support for H3 that posited a larger contribution of capabilities on firm performance compared to IRs, H4 suggesting a larger contribution of capabilities compared to the combined contribution of TR and IR was rejected. A summary of the findings was presented in Table IX.

5.1 Unexpected TR effects

The reason for this unexpected TR effect on performance may be linked to the previous competitive strategy choices of the Turkish firms in global markets. With the support of low labour cost, most of the Turkish firms preferred adopting a low-cost strategy and investing on TRs that enable the firms achieve high amount of production. A low-cost strategy relies “heavily on the ability to improve the manufacturing efficiencies in the firm’s value chain” (Spanos et al., 2001, p. 643). Although manufacturing efficiency can be increased through IRs such as just-in-time and LEAN manufacturing software, relative effects of the TRs such as low-cost raw material and labour, modern machinery and equipment, and physical buildings and manufacturing plants are greater (Grimpe and Hussinger, 2014). Another factor that can explain the finding of strong TR effect on firm performance is that until early 2000s, the Turkish trade and commercial laws did not have deterrent penalties against the firms violating intellectual property rights in the country. Hence, this situation might also direct Turkish firms to focus on just manufacturing at lower costs in order to sustain competitive advantage rather than offering differentiated services and products to the markets. Under these conditions, many Turkish firms developed a special expertise for manufacturing imitated products (e.g. Lacoste, Louis Vuitton and Tommy Hilfiger). Developed countries have a strong historical economic tradition based on free market structure, liberalisation and legal protection for intellectual property which enabled the firms of these countries make relatively more thorough strategic decisions in line with the requirements of new economy where service sector has a high share and IRs are in the focal concern. So, the discrepancies concerning the relative importance of TR vs IR and capabilities on firm performance between the results of similar types of studies conducted in Western countries (Spanos and Lioukas, 2001; Galbreath and Galvin, 2006; Weigelt, 2013) can be explained in this manner and this study may be attributed to the remnants of the past Turkish economic growth model and competitive strategy choices of the Turkish firms.

In H2, the capabilities did not only contribute firm performance significantly higher than TRs, but they also accounted for the largest β values in the context of all hypotheses and regression models. Moreover, apart from the profitability measure on which a considerable contribution was achieved, capabilities provided significant but relatively limited contribution to other performance measures. Therefore, evidence was found to suggest that capabilities are among the most important determinants of a firm’s market and particularly, financial performance.

A partial support was offered for H3 which examined the relative impact of capabilities compared to IRs. One explanation for this partial support might rest with capability and IR interconnectedness (Dierickx and Cool, 1989; Sirmon et al., 2011). For example, reputational resources (e.g. corporate reputation, customer/product service reputation or brand name) which are among the IR categories might be described as an outcome or the result of previous successful marketing or communication activities of a firm’s managerial and/or networking capabilities. In another example, IT systems or collaborative platforms which are among the capability constructs might be described as the outcomes of the in-house developed software that is an IR construct. Hence, when taken in the context of the broader resources necessary to build a capability such as an IT system, its impact on firm performance measures might not be as significant as found by past studies, many of which isolate on an IT system as a stand-alone capability (Ray et al., 2004, 2013). Lastly, the findings demonstrate that idiosyncratic stock of static resources and capabilities that are dynamic in nature become complementary while they create performance and they are likely to represent “the two sides of the same coin” (Wernerfelt, 1984).

The findings of the final H4 were inconclusive. Capabilities offered rather limited additional explanatory power to the prediction of firm performance only with respect to profitability against the combined effects of TR and IR. One possible explanation for the rejection of (H4) is that the hypotheses of this study were too broadly stated and firm performance was measured too narrowly. In reality, different resource categories and different types of capabilities may have varying influence on firm performance. As an example, the effects of human capital (which is a DC) may vary across different manifestations of firm performance but human capital which consists a number of human-related skills such as leadership and strategic decision-making abilities, employee know-how, creative skills of managers and/or employees, etc. was considered as a general capability construct. However, each skill that constitutes a whole capability construct can have different indirect effects within the context of different performance constructs such as number of new products and processes developed, new ideas generated, strategic partnerships established that may be the predictors of market and financial performance constructs used in this study. Although these skills, to some extent, may create performance repercussions on the final performance constructs, their real performance effects might largely remain on the mediating performance constructs.

5.2 Capabilities as determinants of performance

As an ultimate point, capabilities were found as the most important determinants of firm performance in the Turkish business context. Our capability construct included three sub-categories: human capital, networking capabilities and business processes. Although those sub-category capabilities have generated a total impact on firm performance as a general capability construct, their influence should be analysed separately.

Human capital can be seen as an important strategic initiative and enabler in the process of performance creation in the Turkish business context. One explanation for the important role of human capital might be related to the lack of high quality human resource and the existence of inefficiency in working life in the country (World Economic Forum, 2013). Given the conditions of incapability and inefficiency among workforce, more managerial supervision, initiation, control and interaction is required. Furthermore, integration of highly dynamic business environment with incapable workforce may complicate jobs of the managers and compel them to be even more interactive and intervening in every business function of the firms. Bearing in mind that, continuing immigration of skilled human capital from Turkey to Western countries (World Economic Forum, 2013) may have worsened the situation and due to the lack of necessary skilled human resource stock in the country, the qualified managers in firms may have taken additional burdens on their shoulders that force them to be more intervener and interactive in the process of firm performance creation. This position may increase the need of highly skilled employees even more and hence, the participants may have emphasised the vital importance of human capital for performance in the research. Thus, acquiring, attracting, retaining and motivating human capital through effective HRM policies such as developing a unique culture via shaping the spoken and unspoken norms and rules of the firm that creates a working atmosphere and environment for maximum worker productivity and performance should be management priorities.

With respect to networking capabilities, Turkey is a country where nepotism, friendship and trust-based relationship can be seen in every part of life as well as business life (Ozbilgin, 2011). Moreover, existence of poor institutional environment which leads to corruption, high levels of bureaucracy and red tape that can result to inefficiencies may compel firms to establish relations with politicians and bureaucrats. Therefore, given these characteristics of the country, the firms in Turkey may have developed special networking capabilities for relationship-based management. As a managerial implication, managers of the firms in Turkey should spend much of their time on day-to-day operations and establish relations with executives in governmental institutions. The development plans and programmes of political parties should be followed by managers cautiously. As such, the recent administrations which attempt to execute some economic activities with religious references (e.g. 0 per cent interest in the economy, extreme limitation for the sales of alcoholic beverages, utilisation of public services for some groups tendentiously) should be considered for the efficacy of managerial planning and control.

Relating to business processes, rapid and discontinuous changes are common in Turkish economy where political instability, financial volatility and discursive consumer shifts occur. In this situation, business processes such as IT skills, ERP, EDI and SCM systems enable firms to have sufficient intelligence pertaining to current and future customer needs, competitor strategies and actions, channel requirements, and the broader business environment and provide them agility to respond market demands quickly (Ray et al., 2004, 2013).

Since the firms in Turkey operated in a harsh business environment, most of them survived by finding idiosyncratic solutions to the unpredicted and unexpected problems, adopting new alternative strategies, or modifying the existing ones that increase the speed and scope of their strategic manoeuvring actions. Hence, Turkish firms may have given priority to invest in business processes to address their strategic flexibility requirements and after a while they may have acquired special skills to be able to operate in unreliable business environments. Given the hyper changing business conditions in the country, managers of the firms should pay attention to establish early warning systems along with rapid information and market intelligence providing mechanisms. In this sense, allocation of resources in favour of business process development such as strengthening IT infrastructure, SCM and logistics systems should be a concern for managers. However, resource allocation and the optimal deployment of strategic resources is a key managerial challenge and priority should be given to the most important ones.