Supplier Learning and Knowledge Acquisition Within Buyer-Supplier Relationships: The Moderate Effect of Knowledge Protection

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Supplier Learning and Knowledge Acquisition

Within Buyer-Supplier Relationships: The

Moderate Effect of Knowledge Protection

Master thesis

MSc Supply Chain Management University of Groningen Faculty of Economics and Business

Yingran Li S3162583 y.li.72@student.rug.nl

Supervisor: C. Xiao

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Abstract

Knowledge acquisition is critical for continuous improvement and innovation of suppliers. Prior research investigating inter-organizational knowledge acquisition either focus too less on buyer-supplier relationships, or is confined to the buyer perspective. This paper focuses on buyer-supplier relationships in inter-organizational knowledge acquisition field and studies the main effect of supplier learning on knowledge acquisition with knowledge protection of the key buyer as a moderator. The study is conducted under a survey method and the focal perspective is of suppliers in knowledge-intense industries like automobile, consumer electronics, healthcare, etc. Questionnaires are distributed in the Netherlands, Greece, and China. After analysis of the data from 126 valid responses we received in total three countries, a positive relationship between supplier learning and knowledge acquisition are found and the knowledge protection doesn’t show a significant negative effect on the relationship. Suppliers are encouraged to invest more in learning without concerning the impact of knowledge protection of the key buyer as a weighty problem.

Keywords: Knowledge acquisition; supplier learning; knowledge protection; buyer-supplier

relationship.

Acknowledgement

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Figures and tables

Figure 1 Conceptual model ... 7

Figure 2 Results ... 15

Table 1 Profile of respondents ... 9

Table 2 Factor analysis ... 11

Table 3 Descriptive statistics and correlations ... 13

Table 4 Regression analysis (Hypothesis 1) ... 14

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1.Introduction

Recent years, the globalization of markets and the dramatic technological progress make the competition among organizations more and more intense. Organizations are motivated to acquire knowledge to continuously improve and innovate themselves for the purpose of developing sustainable competitive advantage acquisition (Lane, Salk, & Lyles, 2001; Norman, 2004; Zhou, Zhang, Sheng, Xie, & Bao, 2014). Knowledge acquisition occurs when organizations interact with each other, through which organizations approach to external knowledge and then associate it with existing knowledge (Yli-Renko, Autio, & Sapienza, 2001). Prior research exploring inter-organization knowledge sharing and knowledge acquisition has focused almost solely on horizontal forms of governance, such as joint ventures and strategic alliances (Juan et al., 2010; Squire, Cousins, & Brown, 2009). Nonetheless, knowledge sharing is quite common on vertical forms of governance such as buyer-supplier relationship, within which buyers often serve as the knowledge sources and suppliers often act as the knowledge receivers (Squire et al., 2009). However, the knowledge acquisition does not take place automatically or involuntarily, and the supplier learning is one of the critical factor affecting the extent of knowledge acquisition (Lema, 2012).

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It raises the interest of this research that whether the knowledge protection is able to impair the positive effect of supplier learning on knowledge acquisition. Empirical research is required to test how seriously knowledge protection spoils this positive effect.

Research question: How does knowledge protection affect the relationship between supplier learning and knowledge acquisition?

The main contribution of this paper is to enrich the scarce empirical research with regard to inter-organizational knowledge protection and supplier learning. Most of the existing research with respect to inter-organizational knowledge management concern about knowledge transfer and acquisition (Dyer & Hatch, 2006; Dyer & Nobeoka, 2000; Van Wijk, R., Jansen, J. J., & Lyles, 2008; Zhou et al., 2014). The study related to inter-organizational knowledge protection has not been paid enough attention to, and most of the relevant research was either limited to buyer perspective (Wu et al., 2013) or learning alliances (Hurmelinna-Laukkanen, 2011; Norman, 2002). Besides, supplier learning is a relatively new concept which is getting increasing attention from researchers in last decade. Correspondingly, it has received little direct empirical research so far. Furthermore, the overwhelming majority of existing literature as respects to inter-organizational knowledge management, including knowledge sharing, knowledge acquisition, knowledge protection, etc., has taken the perspective of the buyers (Y. Li, Wei, & Liu, 2010). Hence, as one of the major focus of this paper, researching from supplier perspective could also be counted as a contribution of fulfilling this deficiency.

The structure of the paper is as follows. In the next section, the theoretical background and conceptual model of the research are presented. After that, the research method is depicted. Subsequently, the results of the study are presented. The discussion and conclusion are provided in the final section.

2.Theoretical background

The relative literature is reviewed in this section. The concepts are discussed first and then the hypotheses are posited.

2.1 Knowledge acquisition of suppliers

Companies engaging in inter-organizational relationships approach to knowledge that they do not presently have (Holcomb & Hitt, 2007). Researchers and business professionals support that inter-organizational relationships is a critical source of knowledge acquisition (Dushnitsky & Shaver, 2009).

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Wijk, R., Jansen, J. J., & Lyles, 2008). This categorization concerns the difficulty of transferring of different knowledge. Another typology is addressed by other researchers studying supplier learning. They suggest that firms acquire two types of knowledge, namely market and technical knowledge, from their inter-organizational partners (Alcacer & Oxley, 2014; Y. Li, Wei, et al., 2010; Yli-Renko et al., 2001).

When it comes to supplier firms, knowledge acquisition is critical because these firms are apt to fall behind in knowledge and experience compared to their buyers, especially to international buyers (Alcacer & Oxley, 2014; Hitt, Dacin, Levitas, Arregle, & Borza, 2000). Knowledge acquisition offers suppliers opportunities that can be exploited to enhances its competence. The accumulated knowledge acquired from buyers is proved as a contribution to the development and growth of suppliers (Yli-Renko et al., 2001).

Supplier-buyer relationships contain intensive cooperation between suppliers and their buyers. For example, buyers often provide technical support to their suppliers who are not able to complete the production processes or who operate low efficient and behindhand processes (Dyer & Hatch, 2006; Dyer & Nobeoka, 2000; Ernst, 2000). This cooperation contains a knowledge flow from buyers to suppliers. In other words, when knowledge sharing happens in buyer-supplier relationships, buyers often serve as the knowledge sources and suppliers often act as the knowledge receivers (Squire et al., 2009). The received knowledge may then be utilized for enhancing competitive advantage through new product development, technology innovation and reduced costs of production and sales (Yli-Renko et al., 2001). As a companion to technical knowledge acquisition, a substantial amount of market knowledge is also obtained by suppliers. For instance, global sourcing partnerships possibly enable suppliers to participate in supply chain networks with foreign buyers who provide the necessary market knowledge to help suppliers design, manufacture, and refine products that satisfy the demand of the market (Dyer & Hatch, 2006; Ernst, 2000). Through engaging in supply chain networks provided by buyers, suppliers are able to approach up-to-date knowledge about the market and information about the tendency of customer demand changing (Ma & Huang, 2016).

2.2 Supplier learning

To cope with intensified global competition, suppliers are motivated to continually update their technology and capabilities to effectively respond to the rapid changes in customer requirements (Huang & Chu, 2010; Y. Li, Li, et al., 2010). Suppliers involving in OEM relationships commonly intent to develop their innovation capability through the special access to the valuable knowledge embedded in OEM cooperation (Chen, 2005; Horng & Chen, 2008; Levy, 2005). Alcacer & Oxley (2014) also state that suppliers tend to learn to become independent innovators and producers of their own branded products.

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This spillover is noted as ‘opportunities space’ by Lema (2012). The opportunities space contains a ‘market space’ and a potential ‘learning’ space that can enable firms to obtain knowledge and improve their innovation capability (Lema, 2012). A significant degree of pre-existing capability is critical for effective exploitation of the market space. Through such opportunities space that suppliers can release their learning efforts pursuing new knowledge and innovation capability.

Regarding to Figueiredo (2003), inter-organizational learning refers to the various processes that enable firms to pile up new genres and levels of capability. Concerning supplier learning, which is one of inter-organizational learning specific to supplier perspective, Lema (2012) established a way to classify the prime inputs: Idea, investment, and knowledge.

2.3 The effect of supplier learning on knowledge acquisition

According to Alcacer & Oxley (2014), a fact is revealed that suppliers are capable of accumulating technical and market knowledge through learning from their experience as an OEM supplier. Knowledge acquisition is a process accompanied by knowledge sharing and cooperation between buyers and suppliers (Wang, Singh, Koh, & Tong, 2001). Many researchers have verified that knowledge acquisition can be facilitated by inter-firm trust (Mohr & Sengupta, 2002; Squire et al., 2009), social capital (Inkpen & Tsang, 2005; Yli-Renko et al., 2001), absorptive capacity (Owen, Thielman, Guimaraes, & Cornick, n.d.; Tavani, Sharifi, Soleimanof, & Najmi, 2013), etc. Little literature concerning the facilitating role of supplier learning limited its focus on supplier learning intent (Huang & Chu, 2010; Y. Li, Li, et al., 2010). It is argued that suppliers with higher learning intent tend to double their effort to learn from advanced foreign buyers in inter-organizational cooperation (Child, J. and Rodrigues, S. B., 2005; Duanmu & Fai, 2007; Horng & Chen, 2008). That sounds rational but also suspectable since it cannot be sure that the following learning efforts taken by suppliers are perfectly consistent with the learning intent they claimed. The reason why most previous scholars didn’t directly measure the input of supplier learning is that there was no established approach to classify different types of inputs into learning and innovation processes until Lema (2012) established one.

As inter-organizational learning requires considerable resources at a high cost (Bresman et al., 1999), not all suppliers intend to learn from OEM relationships (Huang & Chu, 2010). Some firms purely maintain the transactional relationships without any learning efforts (Hamel, 1991; Hamel et al., 1989). Based on the classification of Lema (2012), ideas, investment and knowledge are considered as three major inputs of supplier learning.

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culture. Innovative organizational culture allows employees to recognize more opportunities space by facilitating the acquisition of knowledge and the utilization of their learned knowledge (Ma & Huang, 2016).

Investment: Through investment, the gap between existing competence and the capabilities needed to achieve the goal can be overcome (Lema, 2012). Suppliers may invest into external relationships, such as set up internal R&D projects or communities of practice. The more closed collaboration let them get access to the knowledge of buyers more frequently and deeply. In addition, suppliers may acquire entire firms or business units (Altenburg, Schmitz, & Stamm, 2008; Figueiredo, 2003). These acquisitions warrant suppliers to come directly into possession of external knowledge.

Knowledge: In the two inputs discussed above, knowledge acquisition seems more like a by-product. Sometimes suppliers make efforts to straightly acquire knowledge, e.g., making investment decision aiming at the acquisition of specific knowledge. But there is another way for a supplier to obtain knowledge without investment, which is asking suppliers to redouble their efforts to capture and exploit opportunities spaces.

Grounded on the analysis of three major input of supplier learning and their correlation with knowledge acquisition, the following hypothesis is proposed:

H1: Supplier learning has a positive effect on knowledge acquisition.

2.4 Knowledge protection of buyers

Although organizational learning is a key factor for firms to attain competitive advantage (Dyer & Nobeoka, 2000), several risks may be generated when companies collaborate and share knowledge. The most critical risk is to lose core competence (Yang et al., 2014). Therefore, knowledge protection is essential to maintaining a company’s competitive advantage (Bogers, 2011; Hurmelinna-Laukkanen, 2011; Norman, 2002).

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limiting the acquisition of crucial knowledge and imitation of core competence by suppliers. Previous pieces of research with regard to knowledge protection focusing on buyer perspective, e.g., Wu et al. (2013), developed a portfolio approach for buyers who want to protect their crucial knowledge to select suppliers.) and elaborate on the knowledge protection mechanism (Gallié & Legros, 2012; Neuhäusler, 2012). Based on the statement of Gallié & Legros (2012) and Neuhäusler (2012), knowledge protection mechanisms can be classified into two main categories: (1) formal mechanisms, including patents and other intellectual property rights (IPRs) and contracts; (2) informal mechanisms, including human resource management (HRM) practices and tacitness. The IPRs mechanism is costly and hard to apply (Olander, Hurmelinna-Laukkanen, & Mähönen, 2009). Most buyers tend to restrictive outsourcing agreements or contracts to protect knowledge from suppliers (Alcacer & Oxley, 2014; Olander et al., 2014; Wu et al., 2013). Because of the complicated industry environment today and the relatively insufficient legislation protection, writing a restrictive agreement of a contract is the most effective approach deployed by many companies (D. Li, Eden, Hitt, & Ireland, 2008). With informal mechanisms, organizations protecting knowledge through the human resource approach often keep the key employees and their knowledge the company (Hurmelinna-Laukkanen, 2011). Keeping the tacitness of knowledge is also an efficient mechanism to impede the knowledge transferring to other firms (Olander et al., 2014).

2.5 The moderating effect of knowledge protection

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Inkpen & Tsang, 2005). Remaining the tacitness of knowledge is a protecting approach with little effort to compress opportunities spaces.

Since the opportunity spaces are the main source through which suppliers learning from buyers, the positive effect of supplier learning on knowledge acquisition possibly deteriorate whilst a buyer takes knowledge protection measures. Thus, the following hypothesis is posited:

H2: Knowledge protection from the buyer negatively moderates the relationship between

supplier learning and knowledge acquisition.

Overall, these two hypotheses lead to the development of the conceptual model depicted in Figure 1.

Figure1 Conceptual model

3.Methodology

To test our hypotheses, the methodology of this paper is demonstrated in this section. It is organized as follows: questionnaire development, sampling, and data collection, and data reduction and analysis.

3.1 Questionnaire development

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items used in this paper were derived from established scales of extant literature in the field and had shown crediable levels of validity. All items are designed as 7 Likert-scale items, with scores ranging from ‘1’ representing ‘strongly disagree’ to ‘7’ representing ‘strongly agree’.

Knowledge acquisition. We used items from a scale developed by Yli-Renko et al. ( 2001) to measure this construct. This scale includes 4 items focusing on both market and technical knowledge acquisition of firms. It’s common to regard the sum of market and technical knowledge acquisition as total knowledge acquisition in literature related to organizational learning. Considering one of the focus of this paper is supplier learning. It’s suitable and rational to use the items of Yli-Renko et al. ( 2001).

Supplier learning. As we mentioned before, the extant research measured supplier learning as supplier learning intent (Huang & Chu, 2010; Y. Li, Li, et al., 2010), which is considered as an unreal reflection of supplier learning in fact. We refer to the classification of inputs of supplier learning of Lema (2012) to develop our measurement. There are three inputs of supplier learning identified by Lema (2012): idea, investment, and knowledge. Four questions are formulated on the base of these inputs. These items collectively represent total inputs of supplier learning.

Knowledge protection. The items of knowledge protection are from the scale developed by Olander et al., (2014). This scale reflects the primary mechanism of inter-firm knowledge protection, which is suitable for this paper. However, since supplier perspective is the focus of this study and all questionnaire are sent to suppliers, this variable is measured as the knowledge protection of buyers perceived by suppliers. The questions are adjusted with respect to the supplier perspective.

Control variable. Firm age, firm size, and the length of buyer-supplier relationship are control variables widely used in the field of knowledge acquisition (Lin, Lin, & McDonough, 2016; Yli-Renko et al., 2001; Zhou et al., 2014). This paper also select them as control variables. Besides, since we distribute our questionnaire to three different countries: the Netherland, Greece and China, firm ownership and firm location are also selected as control variables to compare the difference of results across countries.

In reality, each supplier has many buyers, so it’s impossible for suppliers to answer questions about all their buyers. Practically, in the questionnaire, we ask the supplier to keep its largest buyer in mind when it answers all questions. We refer this largest buyer as the ‘Key buyer’ to the supplier in the following sections.

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3.2 Sample and data collection

Questionnaires are distributed among three different countries: the Netherland, Greece, and China. There is no denying that the Netherland is a developed country and China is a developing country. But whether Greece is a developed country or a developing country has been widely argued around the world especially after the Greek government-debt crisis. It is assumed that suppliers in these three countries vary in different development phases. To analyze the data comparatively can view different results respecting to different types of countries and summarized data analysis leads to more general insights.

Knowledge acquisition is happening in almost every inter-organizational partnership but it is difficult to measure if the knowledge flow between firms is too low. Therefore, companies in knowledge-scarce industries, e.g., agricultural industry, food industry, are not the target respondents in this paper. We focus on knowledge-intense industries such as healthcare, consumer electronics, automobile etc. Bogers (2011) points out that companies in knowledge-intense put great emphasis on innovation, which requires learning efforts and knowledge acquisition. Doig, Ritter, Speckhals, & Woolson (2001) also advocate that outsourcing is popular in knowledge-intense industries and the cooperation with buyers creates opportunities for supplier learning (Alcacer & Oxley, 2014; Kale et al., 2000). Hence, data is only collected from suppliers in knowledge-intense industries.

The survey service provider we selected is Qualtrics both in the Netherland and Greece. In China, due to some internet issue, we test how Qualtrics works before distributing questionnaire. The result shows that people feel tardiness and unsmooth when they completing the questionnaire. Thus, we change to a local survey provider named sojump.com to conduct the distribution. The questionnaire distribution in the Netherland and Greece are in charge with our Dutch and Greek team members who are also master students of supply chain management of the University of Groningen. We sent our invitation of the survey to target companies at first. However, the response rate is quite low because of the number of questions are too much to motivate respondents to finish it. Then we call the target companies who hadn’t completed the survey to invite them to participate sincerely. A considerable number of firms participated after our invitations by phone and the response rate increase.

For the reason of ensuring data reliability in advance, we particularly addressed in the questionnaire that it needs to be completed by at least two senior managers of the company. Totally we sent out 461 questionnaires, of which 135 in China, 56 in Greece, and 270 in the Netherlands. After three weeks data collection, we have received 126 valid out of 153 responses in total three countries. The response rate is 33.2% and the profile of respondents is summarized in Table 1.

Table 1 Profile of respondents

Control variables Number Percentage

Location of the organization

The Netherlands 27 21.42%

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Greece 43 34.12%

Age of the organization in years

0~20 71 56.35%

21~50 32 25.40%

51~100 16 12.70%

≥101 7 5.55%

Length of relationship with major buyer in years

0~5 26 20.63%

6~25 81 64.29%

26~50 15 11.91%

≥51 4 3.17%

Number of employees in this organization

0~50 38 30.16% 51~250 30 23.81% 251~500 22 17.46% ≥501 36 28.57% Type of ownership State-owned 9 7.14% Domestic private 84 66.67% Joint-venture 17 13.49% 100% foreign invested 16 12.70%

3.3 Validity and Reliability

To determine the validity and reliability of our measures, we performed an exploratory factor analysis (EFA) on SPSS as well confirmatory factor analysis (CFA) on AMOS. Table 2 summarizes the results of factor analysis, which only represent the results after reduction.

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Table 2 Factor analysis

Thereafter, a reliability test is conducted and the Cronbach’s alpha of each factor is also shown in Table 2. The a-value for knowledge acquisition is 0.777 (>0.7), which is considered acceptable with high reliability (Nunnally & Bernstein, 1979). For the fact of knowledge protection, the Cronbach’s alpha is 0.667, close to 0.7 and larger than the minimum recommended level, 0.6. It’s also considered acceptable and reliable. After the factor analysis, the items of supplier learning remain only two. Using two-items scale is not common in survey research because more items lead to better construct representation (Schmitt, 2011). However, note that the reliability of this scale before factor reduction is pretty weak (Cronbach’s alpha < 0.6), which is unacceptable. It is recognized that the reliability of this two scale is also weak (Cronbach’s alpha = 0.624), but it does fall within acceptable limits for newly established measures (Nunnally & Bernstein, 1979). In addition, Eisinga, Grotenhuis, & Pelzer (2013) found that the real reliability of a two-item scale is larger than the Cronbach’s alpha value states. Therefore, this two-item scale is considered acceptable in this study.

Constructs and associated indicators

Factor loading

1 2 3

F1: Knowledge acquisition: a = .777

To what extent do you agree with the following statement*:

Our company obtains a substantial amount of market knowledge

from this buyer 0.57

Our company obtains substantial amounts of technical know-how from this buyer

0.81 Our company obtains most of its valuable technical knowledge

related to supplying our product/service

0.85

F2: Knowledge protection a =.667

Our major buyer protects its knowledge through Intellectual property rights

0.79 Our major buyer protects its knowledge through restrictive contract 0.81 Our major buyer intentionally limits the staffs exchange with your

company.

0.86 Our major buyer is reluctant to share tacit knowledge 0.77

F3: Suppler learning a =.624

Our firm invests a lot in external relationships. 0.55

Our firm puts strong efforts to acquire knowledge from buyers. 0.84

Eigenvalues 3.097 2.173 1.273

Percentage of variance explained (%) 28.754 19.756 11.571

*Scale: completely disagree – completely agree (1-7) Extraction Method: Principal Component Analysis.

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3.4 Common method variance

When collecting data for independent and dependent variables at the same time from the same participants using self-reporting questionnaires, common method variance (CMV) might be a concern. (Chang, van Witteloostuijn, & Eden, 2010). The cause of CMV is the that respondents often have a propensity to answer the survey questions positively aligned with the potential relationships. For the purpose of resolving the problem of CMV, we strongly ask two senior managers of the participated supplier to answer the questionnaire together. It is assumed that two respondents of senior managers can provide more factual data than only one respondent. In addition, we have a joint questionnaire mixing with near twenty scales of eight master theses, which brings difficult to respondents for identifying potential relationships of scales.

In case that the common method variance still occurs even with all preventive measures we have taken, i.e., a manager ignores the announce of two respondents and complete the questionnaire himself, Herman’s single factor test on SPSS and a common latent factor test on AMOS have been run. The factor emerged from Herman’s single factor test explains 31.113% variance, showing there might be no problem with CMV since it is far smaller than 50%. When testing the CMV with the common latent factor (CLF) method, a common latent factor was added to the CFA model and the standardized regression weights from the models with and without CLF are compared. The outcome reveals that there is no difference of each item larger than 0.2. The results of these two tests suggest that common method variance might not be a problem for the measurements of this paper.

4. Results

4.1 Descriptive and correlation analysis

Before data analysis, the mean values of item are computed to represent three variables, knowledge acquisition, supplier learning and knowledge protection. In the following analysis, supplier learning is treated as the independent variable, knowledge acquisition is treated as the dependent variable and knowledge acquisition is handled as the moderator.

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these variables are calculated to represent them. The transformation let values of each control variable distribute normally and lead to more rational results than original values. All values of these control variable included in the later analysis are represented by their logarithm of ten. The outcomes of correlation analysis display that firm size is significant correlating to firm age, relationship age, firm location and knowledge protection. Firm age has a significant correlation with relationship age and knowledge acquisition, respectively. Firm location significantly correlates to knowledge protection and knowledge acquisition. Regarding our main model, a significant correlation is showed by Table 3 between supplier learning and knowledge acquisition (r= .425, p< .01).

Table 3 Descriptive statistics and correlations

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

4.2 Regression analysis: Supplier learning and knowledge acquisition

The hypothesized relationships were tested in this section, using hierarchical multiple regression analysis. Hierarchical regression analysis is a method to show if some specific variables explain a statistically significant amount of variance in the dependent variable after accounting for all other variables (Huberty, 2003).

To begin with regression analysis, two categorical control variables of firm location and ownership type are recoded to dummy variables. The Netherland and domestic private are chosen as reference category respectively. Table 4 depicts the results of first regression analysis. Two models are conducted to test hypotheses. The first model includes all control variables and supplier learning as independent variables and knowledge acquisition as dependent variables. Step 1 depicts the results of control variables that demonstrates that China has a significant positive effect on knowledge acquisition compared to the Netherland, and the model is significant refers to F value (2.555*). In step 2, supplier learning is added to independent variables and the result reveals that supplier learning has a significant positive effect on knowledge acquisition (b.= 0.403, p<0.001). This result supports hypothesis 1, which suggests that suppliers with higher extent of learning can acquire more knowledge from their key buyers. The 𝑅"_{of the second model is 0.290, means all the independent}

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variables could explain 37.8% changes of knowledge acquisition. Furthermore, the F-values are at p<0.05 and at p<0.001 levels of model 1 and 2 respectively, which indicates the both two models are significant.

Table 4 Regression analysis (Hypothesis 1)

Knowledge acquisition Step Variables 1 2 1 control Firm size 0.012 0.039 Firm age -0.164 -0.161 Relationship age 0.010 -0.045 Greece 0.103 -0.036 China 0.328* 0.158 Stated own 0.076 0.111 Joint venture 0.013 0.032 Foreign invested -0.031 0.020 2 Main effect Supplier learning 0.403*** R square 0.149 0.290 Adjust R square 0.091 0.235 F 2.555* 5.272***

***. Significant at the 0.001 level (2-tailed). **. Significant at the 0.01 level (2-tailed). *. Significant at the 0.05 level (2-tailed).

4.3 Regression analysis: the moderate effect of knowledge protection.

In this section, the second regression model is performed with the intention of examining the moderate effect of knowledge protection and results are summarized in Table 5. Step 1 presents the regression result of the control variables, of which only China has a significant correlation with the dependent variable. In step 2, we include supplier learning and knowledge protection as additional variables. It can be viewed from the result that supplier learning significantly correlated to knowledge acquisition (b.= 0.410, p<0.001). However, the correlation between knowledge protection and knowledge acquisition is not significant. The 𝑅"_{showing in this step is 0.298 with an F-value of a significant level (p<0.001).}

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Table 5 Regression analysis: the moderator (Hypothesis 2) Knowledge acquisition Step Variables 1 2 3 1 control Firm size 0.012 0.041 0.021 Firm age -0.164 -0.160 -0.129 Relationship age 0.010 -0.038 -0.044 Greece 0.103 -0.031 -0.052 China 0.328* 0.189 0.183 Stated own 0.076 0.107 0.104 Joint venture 0.013 0.037 0.029 Foreign invested -0.031 0.024 0.023 2 Main effect Supplier learning 0.410*** 0.404*** Knowledge protection -0.093 -0.079 3 Interaction effect Supplier learning X knowledge protection -0.088 R square 0.149 0.298 0.305 Adjust R square 0.091 0.237 0.237 F 2.555* 4.879*** 4.538***

***. Significant at the 0.001 level (2-tailed). **. Significant at the 0.01 level (2-tailed). *. Significant at the 0.05 level (2-tailed).

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5. Discussion and conclusion

5.1 Discussion

The results of this study support the initial thought that supplier learning positively influences knowledge acquisition, but the negative moderate effect of knowledge protection on the relationship is rejected. Knowledge acquisition has been verified as an important process related to a firm’s innovation and improvement (Giannakis, 2008). The process isn’t operated automatically. Typically, in buyer-supplier relationships, it does not only depend on efforts taken by suppliers to capture the knowledge, but also depend on the willingness and actual amount of knowledge shared by buyers. From the supplier perspective, a supplier commonly has less power in negotiations with it key buyer. Likewise, it is probably that a supplier cannot affect the willingness and efforts of knowledge sharing from its key buyer. Thus, a supplier has to depend on itself when it wants acquire more knowledge from its key buyer. The results of this paper suggest that facilitating learning of a supplier can lead to knowledge acquisition increase. Suppliers invest more on the external relationship, e.g., facilitating the personnel exchange between two companies, resulting in more knowledge acquisition.

As a contrary of hypothesis 2, the negative moderate effect of knowledge protection on the relationship isn’t supported by the results of this study. It’s kind of a surprising finding since lots of extant research addressed that buyers usually intentionally protecting some of their knowledge from acquiring by suppliers in order to avoid losing competitive advantage (Bray et al., 2007; Lee et al., 2007). It infers that suppliers still obtain a remarkable amount of knowledge through learning even suffering from the knowledge protection from buyers. In other words, the direct effect of knowledge protection is the compressed opportunities spaces, from which the intentional learning efforts let suppliers capture sufficient knowledge for their capacity enhancements and technical innovations. Grounded on practical activities, when the buyer limits personnel exchange to keep the tacitness of some knowledge, a supplier could invest in its employees’ knowledge absorptive capacity as well as in the ability of research and development to overcome the protection measures.

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5.2 Limitations and suggestions for future research

This study opens a few potential doors for future studies. The paper advocates that knowledge protection cannot impede the positive effect of supplier learning on knowledge acquisition, which is adversarial to common sense and challenging the existing literature. Future studies are suggested to further elaborate this model by taking different types of knowledge into account. The main two types of typologies of organizational knowledge classify it either into market and technical or tacit and explicit. Contemplating each of these typologies respectively, different types of knowledge link to different efforts of supplier learning as well as of knowledge protection (Lema, 2012; Olander et al., 2014). By elaborating the model proposed in the paper may generate more detail insights about how suppliers overcome the impact of knowledge protection from buyers.

We also note the low reliability of the supplier learning variable. It is acceptable for a newly developed construct but it is below the recommended level. Further research is supposed to refine this scale by choosing a different group of items together with a further pilot test with researchers and practitioners.

Even though the number of total valid responses in three countries is 126, in whcih of each country is too less (27 of the Netherland, 56 of China and 43 of Greece, respectively) to generate various results of different countries. Likewise, the ownership of firm doesn’t show any significant correlation with any variables might also account for the few samples of each type of ownership. Further studies should find a way to collect more data to verify the variance of results with respect to diverse countries and ownerships.

Finally, the knowledge protection variable is measured as perceived knowledge protection from the supplier perspective. Future research may look for collecting data directly from the key buyer of a supplier. After that, more reliable and veritable results might be found.

5.3 Conclusion

Since suppliers have the motivation to climb up the value chain by improvement and innovation, acquiring knowledge from their major buyer is a valuable choice. The acquisition of knowledge, however, is not an easy job. It does not only depend on the willingness to share knowledge of the key buyer but sometimes even suffer from the knowledge protection from the key buyer. The paper offers advice for suppliers to intensify their extent of learning since it leads to knowledge acquisition increase. Furthermore, this study also states that knowledge protection is not able to impair the positive influence of supplier learning on knowledge acquisition. It realizes the suppliers that they do not have to address the knowledge protection of the major buyer as a serious problem when they are enhancing their learning.

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Appendix – Questionnaire

Firm size

1.Please indicate the number of employees in your organization. Firm age

2.Please indicate the age of your organization in years. Relationship age

3.Please indicate the length of relationship with your major buyer in years. Firm location

4.Please choose where your organization is located. a) the Netherland

b) Greece c) China Firm ownership

5.Please choose the type of ownership of your organization. a) State owned

b) Domestic private c) Joint venture d) Foreign invested

Knowledge acquisition (Source: Yli-Renko et al.,2001) 6.To what extent do you agree with the following statement:

(a) Our company obtains a substantial amount of market knowledge from this buyer

(a) Our company obtains valuable information with respect to customer needs and trends from this buyer

(c) Our company obtains substantial amounts of technical know-how from this buyer (d) Our company obtains most of its valuable technical knowledge related to supplying our

product/service

Supplier learning (Source: Lema, 2012)

7. To what extent do you agree with the following statement: (a) Our firm encourages ideas of improvement and innovation.

(b) Our firm invests a lot in external relationships.

(c) Our firm invests a lot to acquire external firms or business units. (d) Our firm puts strong efforts to acquire knowledge from buyers. Knowledge protection (Source: Olander et al., 2014)

8. To what extent do you agree with the following statement:

(a) Our major buyer protects its knowledge through Intellectual property rights. (b) Our major buyer protects its knowledge through restrictive contract.

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