Product resource–capability complementarity, integration mechanisms, and first product advantage

Journal of Business Research 67 (2014) 704–709

Contents lists available at ScienceDirect

Journal of Business Research

Product resource–capability complementarity, integration mechanisms, and first product advantage☆ Hormoz Ahmadi ⁎, Aron O'Cass, Morgan P. Miles Faculty of Business, University of Tasmania, Private Bag 16, Hobart, Tasmania 7001, Australia

a r t i c l e

i n f o

Article history: Received 1 April 2013 Received in revised form 1 October 2013 Accepted 1 November 2013 Available online 12 December 2013 Keywords: First product commercialization Resource–capability complementarity New technology ventures Supplier integration

a b s t r a c t The current study extends work on resource-based theory (RBT) by exploring resource—capability complementarity in a new context—that of new technology ventures' (NTVs) first product (FP) commercialization in India. This study examines the influence of marketing and technology resource–capability complementarity on FP positional advantages (differentiation and cost-efficiency) and their influence on first product performance (FPP). Furthermore, this study incorporates the influence of supplier integration (SI) mechanisms (in terms of knowledge sharing and cocommercialization) in the process of FP commercialization. The findings suggest that asset complementarities have a positive relation with FP positional advantages, in that both differentiation and cost-efficiency enhance an NTV's FPP, and that SI moderates the relationships between both marketing and technology R–C complementarity and FP positional advantages. © 2013 Elsevier Inc. All rights reserved.

1. Introduction

2. Theory development

NTVs are young SMEs that develop R&D-oriented products in technology-based markets (Li & Zhang, 2007). The success of their FP is a harbinger of the ultimate success of an NTV (Song, Song, & Benedetto, 2011). NTVs have many product related asset limitations (Fernhaber & Li, 2012) which make commercialization of the FP a challenge (Song et al., 2011). Research on product asset deployment leading to new product superiority is substantial; however, much research targets established firms (e.g., Kim & Atuahene-Gima, 2010; Kim, Im, & Slater, 2013). Current research does not emphasize how NTVs can more effectively configure their assets to enhance FPP (Song, Di Benedetto, & Song, 2010). Stakeholder integration in the new product commercialization process is critical. However, the mechanisms that NTVs use to cooperate with suppliers are still unclear (Cavazos, Patel, & Wales, 2011), particularly in relation to FP commercialization processes. This study suggests that when technology and marketing resources and capabilities are complementary they enhance an NTV's FP market performance via the generation of FP positional advantages. Building on social capital theory this study suggests that the influence of technology and marketing resource–capability (R–C) complementarity on FP cost efficiency and differentiation is contingent on the effective integration of suppliers during the commercialization process.

This study extends Day and Wensley's (1988) positional advantage framework for an NTV's FP. In this sense, achieving first product differentiation and cost-efficiency comes from the ability of the NTV to achieve complementarity between the R–C deployed in first product commercialization. Fit is a critical factor in the success of any organization (Zott & Amit, 2008) because efficiency and effectiveness are the result of fit between internal and external contingency factors. Two elements fit well if complementarities exist between them. The sources of positional advantage are complements if increasing one of them increases the returns to the other. Fig. 1 summarizes the conceptual model identifying marketing capability and resources. Marketing capabilities are experiential knowledge, skills, and related processes to undertake marketing activities (Vorhies & Morgan, 2005). Marketing resources include market knowledge and the marketing budget—both critical for new product marketing (Morgan, 2012). Market knowledge denotes the breadth, depth, tacitness, and specificity of knowledge about customers and competitors for the purposes of commercialization (De Luca & Atuahene-Gima, 2007). The marketing budget reflects the allocation of funds to marketing during product commercialization (Song et al., 2011). On the basis of the notion of complementarity, marketing resources and capabilities should undergo fine-tuning to enhance each other's contribution to the FP commercialization process (Huang, Sinha, & Dong, 2004). Marketing capabilities require exploiting complementary marketing resources to achieve differentiation and cost-efficiency (Slotegraaf, Moorman, & Inman, 2003). Marketing resources are static factors of the firm (Makadok, 2001) and need pairing with complementary capabilities to create synergy to enhance the venture's ability to identify customer needs and offer a superior value proposition to customers (Ngo &

☆ We thank Arch G. Woodside and Domingo Ribeiro for their generous and insightful guidance regarding this paper. ⁎ Corresponding author. E-mail addresses: [email protected] (H. Ahmadi), [email protected] (A. O'Cass), [email protected] (M.P. Miles). 0148-2963/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jbusres.2013.11.031

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705

Supplier integration

Positional advantages

Source of Advantage

Marketing resources x Marketing capabilities

First product differentiation

Technology resources x Technology capabilities

First product cost - efficiency

Performance

First product performance

Fig. 1. Conceptual model.

O'Cass, 2012) in the form of the first product. For example, through deploying marketing capabilities in complementary with financial resources in promotion, NTVs try to inform customers about how the first product is different or costs less. Therefore, H1a. Marketing R–C complementarity has a positive relationship with FP differentiation. H1b. Marketing R–C complementarity has a positive relationship with FP cost-efficiency. Technology capabilities denote experiential knowledge, skills, and related processes in designing, developing and manufacturing the product (Song, Droge, Hanvanich, & Calantone, 2005). Technology resources include physical resources and the R&D budget—both vital to new product success (Song, Podoynitsyna, Van Der Bij, & Halman, 2008; Zahra & Bogner, 2000). The R&D budget reflects the financial resources available to invest in product development activities (Song et al., 2011). Physical resources include plant, machinery, and test equipment for product development activities (Sirmon & Hitt, 2009). Complementary deployment of technology resources and capabilities should also enhance each other's contribution to FP commercialization (Fig. 1). Innovation related to product newness, features, and breakthrough technology resides in the capacity of the firm's technology capabilities. For example, the usefulness of technology capabilities only occurs through funding capacity development during the FP design and prototype stages. This enables an NTV to create a low-cost and differentiated product that meets the needs of the current market or potentially creates a new market. Therefore, H2a. Technology R–C complementarity has a positive relationship with FP differentiation. H2b. Technology R–C complementarity has a positive relationship with FP cost-efficiency. NTVs possess limited assets and face challenges to make trade-offs in pursuing either effectiveness or efficiency (Morgan, Clark, & Gooner, 2002). The relative advantage of a novel FP is positively related to its rate of adoption (Rogers, 1995). Likewise, product advantage appears as a significant feature in describing the adoption of new products (Langerak, Hultink, & Robben, 2004). Particularly in emerging economies, the customers' ability to afford the FP is vital in markets in emerging economies, and affordability is critical to converting non-adopters to customers (Sheth, 2011) as outlined in Fig. 1 both FP differentiation and cost efficiency are related to FPP. Therefore, H3a. FP differentiation has a positive relationship with FPP. H3b. FP cost efficiency has a positive relationship with FPP.

Social capital theory underpins a firm social networking with its suppliers (Lin, 2008). Social networking can lead to more effective integration of suppliers (Zhang & Wu, 2012) in the process of FP commercialization in NTVs. This study examines SI in terms of informationknowledge sharing and product co-commercialization (Lau, Yam, & Tang, 2010). Information sharing occurs in terms of shared knowledge about the market and technology, inventory, and production (Lau et al., 2010). Informal information exchanges among suppliers and firms' product teams provide synergy to co-commercialize innovative products and lower the costs of commercialization operations by increasing efficiency (McDermott & Handfield, 2000). Suppliers are key sources of innovative ideas for developing novel products (Baldwin & Hanel, 2003). Real time information about market and technology changes provided by suppliers aids NTVs in obtaining a more comprehensive understandings of their customers and more effectively deploying their assets in the new product development project (Lau et al., 2010). Effective information sharing minimizes information asymmetries and, consequently, leads to higher performance because commercialization processes run more efficiently (Rosenzweig, Roth, & Dean, 2003). Market information provided by suppliers at early stages help NTVs to devise effective pricing and sales strategies while also arranging effective launch and promotion tactics for introducing the FP to the market. Integrating suppliers into operations reduces the risks associated with changing technology and market needs (Johnston, McCutcheon, Stuart, & Kerwood, 2004). Joint production is often a foundation for collaborative product commercialization with suppliers, increasing the chance of commercializing products that create new markets (Song & Di Benedetto, 2008) (Fig. 1). Early SI enhances market linking capabilities to accumulate knowledge about the market. Integration is transactional as NTVs work closely with suppliers to create products that meet cost, quality, and delivery goals. SI processes also lead to better design, lower operation costs, and a shorter time to market (Primo & Amundson, 2002). Therefore, H4 (a, b). SI positively moderates the relationship between marketing resource–capability complementarity and a) FP differentiation; and b) FP cost-efficiency. H4 (c, d). SI positively moderates the relationship between technology resource–capability complementarity and c) FP cost-efficiency; and d) FP differentiation. 3. Method This study takes India as the context because this country is a key emerging economy (Javalgi, Todd, Johnston, & Granot, 2012). The records of the Indian Chamber of Commerce yield a list of 650 NTVs. One selection

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H. Ahmadi et al. / Journal of Business Research 67 (2014) 704–709 Table 1 (continued) Dimensions and manifest variables

Table 1 Measurement model results. Dimensions and manifest variables Marketing capabilities 7-point scale much worse–much better Comparing your firm to your major competitors, rate your firm in the following areas in relation to your first product project. In… Planning (AVE = .66, CR = .88) … segmenting and targeting the market, we are … formulating marketing strategies, we are … marketing planning, we are Pricing (AVE = .71, CR = .89 ) … pricing strategies, we are … pricing accurately, we are … setting prices according to how customer perceives value of the product (or service, if applicable), we are … pricing that is maximum beneficial to customers, we are Communication (AVE = .55, CR = .90 ) …advertising and promotion, we are … developing advertising and promotion programs, we are … public relations, we are … managing corporate image and reputation, we are Sales (AVE = .64, CR = .89 ) … giving salespeople the training they need, we are …sales management skills, we are … providing sales support to the sales force, we are Launching (AVE = .68, CR = .89 ) … launching new products (or services, if applicable), we are … ensuring that product development efforts are responsive to customer needs, we are Market linking (AVE = .59, CR = .90) … focusing on meeting customers' long term needs, we are … maintaining loyalty among attractive customers, we are … enhancing the quality of relationships with customers, we are … adding value to our channel members (e.g., distributors, retailers and wholesalers) businesses ,we are … attracting and retaining the channel members in the market, we are … satisfying the needs of channel members, we are … closeness in working with channel members, we are … establishing and maintaining close supplier relationships, we are Technology capabilities (AVE = .65, CR = .88) 7-point scale much worse–much better In relation to your firm's first product launch project and comparing your firm to your major competitors, rate your firm in the following areas. In… …new product (or service, if applicable) development capabilities, we are … new technology development capabilities, we are … manufacturing processes, we are … predicting technological changes and trends, we are … quality control skills, we are … adopting new technologies to current processes, we are FP differentiation (AVE = .50, CR = .87) 7-point scale strongly disagree–strongly agree Our first product … … compared to competitive products, has offered some unique features and attributes to the customer … has been clearly superior to competing products in terms of meeting customers' needs … has had higher quality than competing products—tighter specification , stronger, lasted longer , or more reliable … has provided a superior benefit to cost ratio than competing products … has had superior technical performance than competing products FP cost-efficiency (AVE = .62, CR = .90) 7-point scale strongly disagree–strongly agree Compared with other competing products in our industry, the first product we introduced was developed to incorporate: … … operation efficiencies (e.g., manufacturing modernization, adopting new technologies). … benefits from economies of scale … minimum manufacturing and delivery costs … cost advantages in raw material procurement SI 7-point scale not at all–extensively Rate your firm in the following areas representing the extent your firm integrated and coordinated activities with the SUPPLIERS during your first product launch project. Our firm engaged in…

Loading t-Value

0.77 0.81 0.83

18.34 22.35 25.03

0.82 0.85 0.84

24.49 32.67 25.88

0.77

20.22

0.52 0.55 0.67 0.65

4.23 6.32 9.41 10.02

0.73 0.71 0.68

16.52 13.92 9.85

0.53 0.54

4.88 5.70

0.58 0.56 0.63 0.67

6.75 5.95 7.33 8.90

0.66

7.48

0.69 0.71 0.72

10.85 12.55 13.42

0.81

18.51

0.77 0.76 0.71 0.69 0.80

17.57 15.42 14 10.75 18.91

0.54

6.34

0.63

11.26

0.58

9.71

0.57

7.32

0.62

6.98

0.69

12.37

0.75 0.77 0.78

16.93 18.21 18.52

Loading t-Value

Information sharing (AVE = .66, CR = .88) Sharing inventory mix/level information 0.75 Sharing production plans 0.81 Sharing marketing information 0.83 Sharing technological information 0.85 Co-commercialization (AVE = .73, CR = .91) Joint product (or service, if applicable) design 0.72 Joint process engineering 0.79 Joint production operations 0.76 Joint marketing operations 0.80 FPP (AVE = .73, CR = .90) 7-point scale strongly disagree–strongly agree Since its launch, our first product, has … … achieved its sales goals 0.89 … achieved its profit goals 0.88 …. has had great profitability 0.85 … has achieved its goals in customer satisfaction 0.79 Technology resources 7-point scale strongly disagree–strongly agree In relation to our first product launch… Budget (AVE = .55, CR = .88) … our R & D department acquired / possessed substantial financial 0.63 resources in comparison to our major competitors, … our R & D department had substantial financial resources 0.66 available in our firm Physical (AVE = .66, CR = .91) … we accessed/acquired State-of-art production and 0.78 manufacturing machinery … we accessed/acquired high standard production plant in terms 0.80 of facilities … we accessed/acquired well equipped R & D labs for testing op- 0.79 erations … we accessed/acquired advanced technological software(s) 0.78 Marketing resources 7-point scale In relation to our first product launch… Budget (AVE = .58, CR = .87) strongly disagree–strongly agree … considerable financial resources were allocated to the 0.83 marketing area in comparison to our major competitors … considerable amount of financial resources were invested in 0.85 the marketing department in our firm Market knowledge Since the launch of our FP/service, our firm's knowledge about our… Breadth (AVE = .53,CR = .87) narrow(1)–broad(7) limited(1)– wide ranging(7) specialized(1)–general(7) … competitors' strategies has been 0.59 … competitors' strategies has been 0.61 … customers has been 0.55 … customers has been 0.59 … competitors' strategies has been 0.57 … customers has been 0.63 Depth (AVE = .55,CR = .88) shallow(1)–deep(7) basic(1)–advanced(7) … competitors' strategies has been 0.61 … competitors' strategies has been 0.55 … firm's customers has been 0.56 … firm's customers has been 0.63 Specificity (AVE = .63, CR = .89) strongly disagree–strongly agree Since the launch of our FP/service, our firm's knowledge about our customers and competitors… … has been quite specific to our kind of business 0.73 … has been very difficult for an employee to transfer it throughout 0.71 firm and other environment … has been tailored to meet the specific conditions of our business 0.76 …. largely depends on the human and physical assets we have 0.74 dedicated to acquiring information about market conditions Tacitness (AVE = .66, CR = .82) strongly disagree–strongly agree … comprehensively document in manuals or reports 0.78 … comprehensively understand from written documents 0.80 … identify without personal experience in using them 0.81 …. precisely communicate through written documents 0.79

15.96 17.11 18.37 20 12.25 14.48 13.55 17.22

39.21 37.55 35.90 29.98

8.85 9.32

21.25 25.59 16.48 14.77

29.91 33.5

11.22 15.43 9.95 10.41 13.87 19.92 16.52 10.21 13.39 18.87

14.78 11.92 18.43 12.55

18.88 24.65 26.01 22.11

criterion is for the NTVs to have launched their first products at least one year prior to participation in the study. A preliminarily telephone screening produced 300 NTVs operating in business-to-business markets

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Table 2 Correlations. Variables

Mean

SD

Composite reliability

1

2

3

4

5

6

7

8

1- Marketing capabilities 2- Technology capabilities 3- Marketing resources 4- Technology resources 5- FP differentiation 6- FP cost efficiency 7- FPP 8- Supplier integration

5.45 5.95 6.03 5.98 6.33 5.22 4.98 5.23

0.77 0.75 0.71 0.70 0.82 0.77 0.74 0.73

0.92 0.88 0.87 0.86 0.89 0.90 0.90 0.89

1.000 0.33 0.41 0.25 0.45 0.28 0.51 0.12

1.000 0.61 0.53 0.56 0.49 0.39 0.22

1.000 0.46 0.33 0.29 0.59 0.14

1.000 0.27 0.28 0.s41 0.32

1.000 0.33 0.48 0.31

1.000 0.42 0.35

1.000 0.14

1.000

agreeing to participate. Adopting the procedure from De Luca and Atuahene-Gima (2007), this study uses a multi-informant (the CEO and a mid-level manager per NTV) design, thereafter adopting a drop-andcollect technique (Soltani & Wilkinson, 2011). A total of 142 NTVs returned valid surveys. These NTVs operate in the biotechnology (10%), pharmaceutical (12%), telecommunication (18%), electronics (18%), information technology (31%), and industrial machine (11%) industries. 4. Measures This study uses the marketing capabilities scale from the work of Vorhies, Orr, and Bush (2011). Items capture pricing, selling, planning, promotion, product launch, channel management, and supplier relationship management functions. Measurement of marketing resources relies on items from De Luca and Atuahene-Gima's (2007), which focus on the market knowledge, including breath, depth, specificity, and tacitness. Measurement of marketing resources uses items from Gruber, Heinemann, Brettel, and Hungeling (2010). The study measures technology capabilities by adopting items from DeSarbo, Di Benedetto, Jedidi, and Song (2006). Measurement of technology resources requires the adaptation of items from Borch, Huse, and Senneseth (1999) and Gruber et al. (2010) to assess the level of the R&D budget compared to competitors. Items measuring the technological physical resources for FP commercialization derive from the works of McKelvie and Davidsson (2009) and Zahra and Bogner (2000). Measurement of supplier integration requires the adaptation of items from Lau et al. (2010) and Song and Di Benedetto (2008).

with both FP cost-efficiency and FP-differentiation, with a path coefficient (β) of 0.21 (t-value = 2.84) and β = 0.29 (t-value = 3.89). Likewise, support for H2a and H2b emerges from the results. The relationship between technology R–C complementarity and differentiation shows a β = 0.25 (t-value = 3.35). Also, technology R–C complementarity has a positive relationship with cost-efficiency with a β = 0.22 (t-value = 2.95). The results provide support for H3a and H3b as both relationships set out in the hypotheses are significant, and both FP differentiation (β = 0.57, t-value = 7.66) and FP costefficiency (β = 0.33, t-value = 4.41) have positive relationships with FPP. For moderating effects, this study considers explanatory power, which involves evaluating R2 and exploring the effect size of the model constructs (Andreev, Heart, Maoz, & Pliskin, 2009). Adapting Limayem and Cheung (2008), this study uses a hierarchal approach to compare the R2 value of the direct effect with that of the interaction effect which excludes the R2 of interaction effect (Chin, 1998). Where the R2 interaction model is the explained variance of the dependent construct, including both independent and moderator constructs, and the R2 direct model is the explained variance of the same dependent construct when moderator construct is removed from the model. Chin (1998) reports that the effect size f2 is either small (f2 = 0.02), medium (f2 = 0. 15), or large (f2 = 0.35). Hence, calculation of the strength of the substantive impact of the moderator construct is as follows: h i h i 2 2 2 f2 ¼ R interaction model − R direct model = 1 − R direct model :

This study utilizes Partial Least Square (PLS)/Structural Equation Modeling (SEM) to analyze the data. Table 1 depicts the outer model results including the first-order and second-order constructs. As shown in Table 1, the first-order factor AVEs are in the range of 0.55–0.73. The AVEs and CRs for other constructs are as follows: technology capabilities (AVE = 0.65, CR = 0.88), FP differentiation (AVE = 0.50, CR = 0.87), FP cost-efficiency (AVE = 0.62, CR = 0.90), FPP (AVE = 0.73, CR = 0.90). The results in Table 1 indicate that all the reliability coefficients are greater than the threshold of 0.7 (Nunnally, 1978). All the factor loadings are significant and acceptable, and are all greater than 0.5, indicating convergent validity of the measures (Hulland, 1999). Ngo and O'Cass (2009) argue that discriminant validity among constructs occurs when no correlations of individual constructs are higher than their corresponding reliabilities, thereby suggesting discriminant validity of all the constructs (Table 2).

The results support H4a as the interaction effect (R2 = 0.32) reflects more explanatory power than the direct effect (R2 = 0.16), and the relationship is significant with a β = 0.15 (t-value = 2.01), and the effect size is 0.19. Thus SI positively moderates the relationship between marketing R–C complementarity and FP differentiation. H4b states that SI positively moderates the relationship between marketing R–C complementarity and FP cost-efficiency. The results do not support H4b with an insignificant β = 0.065 (t-value = 0.87). H4c states that SI positively moderates the relationship between technology R–C complementarity and FP cost-efficiency. The results support H4c as the interaction effect (R2 = 0.25) reflects more explanatory power than the direct effect (R2 = 0.18) and relationship is significant with a β = 0.14 (t-value = 1.99), and the effect size is 0.09. Further, H4d states that SI positively moderates the relationship between technology R–C complementarity and FP differentiation. The result supports H4d as the interaction effect (R2 = 0.26) reflects more explanatory power than the direct effect (R2 = 0.19), and the relationship is significant with a β = 0.16 (t-value = 2.15), and the effect size is 0.09.

6. Hypotheses testing

7. Discussion

Computing the interaction between the constructs, by generating the product term of the standardized scores, allows for an operationalization of the complementarity between resources and capabilities (O'Cass & Sok, 2012). The results support both H1a and H1b, indicating that marketing R–C complementarity has a positive relationship

The findings support the theory set out in the above theoretical discussion to do with the impact of technology and marketing resources, and capabilities' complementary enhances the efficiency and effectiveness of FP commercialization in NTVs. The results suggest that deploying FP commercialization resources and capabilities in marketing

5. Analysis

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H. Ahmadi et al. / Journal of Business Research 67 (2014) 704–709

and product development in a complementary manner is significant in obtaining FP positional advantages. This study conceptualizes FP assets in a way that accounts for the importance of both resources and capabilities' functionality and their interdependence (Day & Wensley, 1988). Given the characteristics of NTVs, the findings support the importance of examining the simultaneous influence of both technology and marketing resources and capabilities (based upon their distinct functionality), while involving their contribution to each other's performance in the FP commercialization process. Particularity, the findings reveal the critical need of knowledgebased assets such as marketing capabilities and technology capabilities to exploit and utilize resources to efficiently and effectively undertake FP development and launch activities at the operational level. The findings also confirm that R–C complementarity of marketing and technology can simultaneously enhance effectiveness and efficiency in commercializing the FP with unique features and lower operational costs. As a result, the findings shed light on the important issue of examining both innovation and marketing functions when studying technology-oriented firms and in particular NTVs' FP commercialization. Hence, this study concludes that NTVs cannot rely solely on their abilities as technology developers as the source of FP advantage, but must also accumulate and deploy R–C complementarity in marketing as well. Extending the work by Kim and Atuahene-Gima (2010) the findings confirm the necessity of examining both product-related positional advantages in the domain of the FP commercialization process in NTVs, and support the simultaneous contribution of differentiation and costefficiency to FPP in emerging economies. This contribution is significant given the lack of scholarly attention towards the cost efficiency aspects of the FP in conjunction with its differentiated features while studying the FP positional advantages. The findings show the effect of SI mechanisms in enhancing the contribution of technology and marketing complementarity in both product-related functional areas. The findings support the positive impact of the interaction between internal and external assets to help NTVs realize efficiency and effectiveness during their FP commercialization. In addition, the findings reveal that the SI in terms of knowledgesharing and co-commercialization contribute to commercialization of the FP that meets cost-efficiency and differentiation objectives. Likewise, this study finds support for the influence of SI in supporting the marketing complementary assets in achieving FP differentiation; however, the results show that integrating the supplier's marketing processes into NTVs FP marketing operations, does not help NTVs to achieve FP cost-efficiency. By incorporating the interaction effect of external integration mechanisms, this study enhances the usefulness of the analysis by simultaneously examining the role of internal complementary R–Cs along with the effect of external integration mechanisms. Hence, the results provide insights on how commercialization of a successful FP occurs, by illustrating the concurrent impact of internal and external assets throughout the FP commercialization. The findings suggest that NTVs need to simultaneously pay attention to the accumulation of resources and capabilities (that complement each other) throughout development and launch phases. Moreover, the findings support Sheth's (2011) contention suggest that NTVs in emerging markets need to jointly purse cost-efficiency and differentiation because of the low purchasing power of the customers who seek both innovative features but low prices. Future research may incorporate the role of other environmental and firm level contingency factors that can affect the relationship between the complementary FP assets and positional advantages. For example, in emerging economies the perception is that the government is the main policymaker of the business environment, so the role of NTV founders' political networking capabilities may be crucial in acquiring regulatory and market knowledge and R&D funding. Furthermore, the present study's cross-sectional research design may not fully capture the dynamic relationship between the complementary assets and

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