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Introduction
Tight competition and business growth require companies to compete with other similar companies. Marketing activities are the spearhead of the company's success in maintaining its existence (Bozidar Jakovic, 2014). For this reason, a strategy is needed to support it. The right strategy that can be applied in a company is a personalized marketing strategy (Karina Kusuma Halim, 2019). This strategy is useful to produce products that fit with consumer tastes so that the products are sold properly in the market. Service, communication can attract customer attention and it has an impact on customer loyalty.
Collaboration between companies has an impact on relational capability which is a solution to the problems that occur (Salisu, 2019) ; gaining knowledge to achieve economic scale, efficient technology; and being able to utilize the owned resources so that itcan expand market share (Dorleta Ibarra, 2018). Companies must be able to face the competition that is happening at this time because the competition shifts from individual competition to business network competition (Christine Musselin, 2018). Relationship development becomes relevant for companies in increasing resources so that it generates economic value (Cooper-Thomas, 2018).
Companies that are able to keep promises and provide good service to consumers have a positive impact on consumer’s viewabout the organization (Smith, 2019). Reputation perception can be obtained by consumers by collecting other consumer information or through media. Various information and company performance information will form a good company reputation
Indicator of the impact from implementing company’s strategy is marketing performance. The marketing performance is multi-dimensional. It contains various objectives and types of organization or it is a result achieved by the company to meet consumer tastes.
Research results (Chuang, 2020) explain that relational capability is the process of identifying, developing, strengthening relationships between consumers and companies. (R.P. Jayani Rajapathirana, 2018), (Gao, 2010), states that relational capability can improve marketing performance with two-way communication steps, manage mutually beneficial relationships between customers and companies. On the other hand, researches (Chuang, 2020); (R.P. Jayani Rajapathirana, 2018), (Gao, 2010) , state that the company's capability to build relationships with customers and competitors cannot improve marketing performance because customers are more concerned with the goods quality, great service and low prices.
Based on the gap between background of the problem and the research, the research question of this study is described as follows: what are the influences of knowledge and relational capabilities on marketing networks that have an impact on marketing performance?
Literature review
Knowledge agility
Knowledge is human capital in determining management knowledge. Knowledge is something that is stored in the human brain coming from past experience. The information is, then, recorded and stored in the brain (Lisa Beesley, 2008). One element to achieve company success is determined by factors of knowledge and experience. Therefore, each member of the company must carry out the knowledge and learning process. (Żur, 2020), learning can help managing the corporate knowledge capital in order to achieve the competitive advantage. Effective knowledge utilization creates superior value and even can improve organizational performance (Fatemeh Torabia 2017).
Relational capability
Relational capability is one form of organizational dynamic capability that is useful for creating, expanding, modifying business of organization resources (Salisu, 2019). (Schwenk, 2009) define relational capability is tangible resource for creating social relationships, facilitating each activity so that competitive advantage is achieved. Relational capability is needed by the company because it is able to create complementary capabilities, to improve access to knowledge and information, the learning process for organizations and to manage effectively (Risto Rajala, 2018).The ability to build relationships can increase innovation and co creation value (Blomkamp, 2018). Relationships with customers can create customer value (Chris Rygielski a 2002), with the company that brings some benefits related to service quality improvement such as cost, revenue, and building new competencies (Paul Brous, 2020).
Marketing network
Networking is the competence that runs activities (Richa Awasthy, 2020). Businessman develops networks to achieve various objectives including obtaining information and knowledge about the market, information on decision making; and increasing efficiency (El-Mallah, Aref, & Sherif, 2019). Network members can provide the skills needed by employers (Catherine K. Hart, Chelly Dykes, Rachel Thienprayoon, & Jennifer Schmit, 2015) . Relationships between networks can have their own resources. Networks can also have an impact a company's bargaining power, help identifying new market opportunities, and influence marketing activities. The ability to build networks includes four dimensions, namely coordination, skills, market knowledge and internal communication.
Marketing performance
Marketing performance is one indication in building overall company performance (El-Mallah et al., 2019); (Hendar, 2018). Marketing performance is used to measure achievement in company marketing activities and is the application of corporate strategy (Gao, 2010). (Sugiyarti & Ardyan, 2017) explains that the so-called marketing performance is a corporate strategy directed to produce company performance. Three indicators of marketing performance are sales value, sales growth, and market share. Sales growth depends on the number of customers or product units sold. The high sales value indicates that more products are being sold. The market share is the amount of product contribution dominates the market of similar products compared to competitors.
Hypotheses
Relationship between knowledge capability with marketing networks
Finding (Lisa Beesley, 2008), explains that company can improve marketing performance through competence and marketing knowledge management. Marketing knowledge management effectively increases marketing capabilities that have an impact on the increase of business performance (Fatemeh Torabia 2017). The effect of marketing knowledge capability has a direct effect on market knowledge towards marketing performance; and knowledge capability has a significant influence on marketing networks (Heru Sulistyo, 2020) . From the description above, the first hypothesis can be proposed:
H1: Knowledge capability has a positive relationship on marketing networks.
Relationship between relational capabilityand marketing networks
In principle, relational capability is a long-term relationship and bond between producers, consumers and suppliers (Blomkamp, 2018). There is a continuous bond and exchange as well as mutual trust. There is also dependency that marketers strongly emphasize the importance of long-term good relationships with consumers so as to create relationships awareness and commitment. Finding (Scholer, 2018) shows the suitability of the company's network capabilities to initiate connections is embedded in networks between organizations including customers, suppliers, research institutions and others (Catherine K. Hart et al., 2015). This study discusses the ability of companies to join relevant networks so that it has an effect on the ability to market/to sell through networks. Based on the description above, the second hypothesis is:
H2: Relational capability has a positive relationship on marketing networks.
Relationship between knowledge capability and marketing performance
The causal relationship is aligned between the two variables. Marketing capability is the result of the organizational learning process because one goal of the organization is to form competencies as a result of continuous learning (Francesco Gangi & Varrone, 2019). They explain the knowledge capability has a significant effect on marketing performance (Taryn Jane Bond-Barnard, 2017) . (Scholer, 2018) describe three key marketing networks namely market orientation, deadline for corporate strategic decision making, and company capabilities positioning. Based on the description above, the third hypothesis is:
H3: Knowledge capability has a positive relationship on marketing performance
Relationship between relational capability and marketing performance
(Schwenk, 2009) explain that empirically there is a relationship between relational capability and company performance. R.P. Jayani Rajapathirana, (Gao, 2010) show a significant positive relationship between relational capability and company performance. The results of their research explain about building relationships with other companies and predicting the maximum level of change in relational capability. (Schwenk, 2009) state that the company's relational ability to maintain high-quality relationships needs an appropriate mechanism. Based on the description above, the fourth hypothesis is:
H4: Relational capability has a positive relationship on marketing performance.
Relationship between marketing network and marketing performance
(Scholer, 2018) examined the role of social networking in the performance of small and medium-sized companies in the international market. Their findings explain that industry networking influences the export performance and financial performance (Catherine K. Hart et al., 2015) . (Sugiyarti & Ardyan, 2017) explain the understanding of creating relationship will improve a company's ability to generate value from the relationships that have impacts on its marketing performance. Three mechanisms to improve marketing performance are using network resources directly to expand opportunities; producing combination of resources and directly gaining some benefits from network resources. Based on the description above, the fifth hypothesis is:
H5: Marketing networks have a positive relationship on marketing performance
Research method
Sample and data collection procedures
Data collection of this study used survey. The primary data were from small and medium business owners on various issues. Structure Equation model (SEM) version 16.0 was used for quantitative data.
A sample of 250 small and medium enterprises in Indonesia was used to test models and hypotheses. Sampling was done through purposive sampling technique. Some criteria are described as follow: have a minimum workforce of 5 people, a minimum of 3-years business experience, a minimum business capital of IDR 15,000,000. Then, data normality test was carried out. The feasible data obtained was 215.
Research variables
Operational variable can be seen on the Table 1 as follows:
Table 1 Operational variables
| Variable | Core Meaning | Operational Measures | Source |
|---|---|---|---|
| Knowledge agility | The ability to increase knowledge and experience | 1. Accumulation | (Taryn Jane Bond-Barnard, 2017) |
| 2. Interaction | |||
| 3. Collaboration | |||
| Relational capability | The ability to use external resources by maintaining social relationships | 1. Team work | (Risto Rajala et.al., 2018) |
| 2. Response | |||
| 3. Communication | |||
| 4. Building a network | |||
| Marketing network | Consumer-oriented | 1. Commitment | (Scholer, 2018) |
| Marketing with networking | 2. Market adjustment | ||
| 3. Harmonization of relationships | |||
| Marketing performance | A concept to measure marketing achievements of a company | 1. Sales growth | Sugiyarti,G., Elia Ardyan (2017) |
| 2. Sales volume growth | |||
| 3. Retain old customers | |||
| 4. Expanding the marketing area |
Source: Sugiyarti, G.; Elia ardyan (2017): (Taryn Jane Bond-Barnard, 2017); (Risto Rajala et., al, 2018), (Risto Rajala et., al, 2018).
Data analysis and discussion
Data screening
Theoretically, data on social research is difficult to distribute normally (J. Hair, Ringle CM & Sarstedt, 2011).Therefore, it is necessary to normalize the data. (Tabachnick & Fidell, 2012). For data with positive direction, the skewness must be changed by 1 / X. Data based on the 1 / X formula produces a series of data with a normal distribution pattern. Based on normalized data, indicator of the ability to understand customers has a smaller value than 0.6. The item is then omitted from the analysis. All AVE values for each variable are above the required value of 0.5. Construct of the reliability value for each variable is greater than the cut-off (> 0.60).
Structural model analysis
Hypothesis testing using the SEM-AMOS tool is structurally full model through two stages of hypothesis testing (J. Hair, Ringle, C. and Sarstedt, M., 2011) . First, tested the goodness of fit using SEM criteria with a significance level of chi-square χ2 = 85.734, significance level = 0.023; DF = 179; GFI = .927; AGFI = .908; CFI = 0.980; TLI = 0.957; RMSEA = 0.061, CMIN/DF = 1.147. it is concluded that the model is fit. Second, testing the causal relationship between variables using CR criteria equal to or greater than 2.0 (Arbuckle, 2013).
The results of testing 5 hypotheses can be seen in Table 2 below:
Table 2 Hypothesis Testing
| Estimasi | SE | CR | P | Supported | |
|---|---|---|---|---|---|
| Marketing network - Knowledge capability | 0.354 | 0.078 | 2.865 | 0.001 | Yes |
| Marketing network - Relational capability | 0.534 | 0.134 | 2.897 | 0.002 | Yes |
| Marketing performance - Knowledge capability | 0.455 | 0.133 | 3.954 | 0.003 | Yes |
| Marketing performance - Relational capability | 0.543 | 0.143 | 1.885 | 0.059 | No |
| Marketing performance Marketing network - | 0.433 | 0.133 | 3.799 | 0.002 | Yes |
Source: Primary data processed, 2020
Mediation testing
Network marketing is a concept of mediating the effect of relationship capabilities on marketing performance. The Sobel Statistical Test was conducted online at http://www.danielsoper.com. The findings of the concept of network marketing are able to mediate the relational capabilities of marketing performance because the sobel test value is greater than 1.96, namely 2.23232705, with tests smaller than 0.05, namely 0.00241304, and the test of 0.00614617.
Discussion
First, the knowledge capability hypothesis has a positive effect on network marketing is accepted. The results of data processing found that the CR value on the relationship between the knowledge capability variable in the marketing network was 2.865, with a P value of 0.001, shown in Table 2. The results meet the requirements above 1.96 for CR and below 0.05 for P. It is concluded that the first hypothesis is proven to be significant, namely that knowledge capabilities directly have a significant effect on network marketing. It means the higher degree of knowledge capability, the higher the marketing network. The results of this study reinforce previous research (Lisa Beesley, 2008), (Fatemeh Torabia 2017). Knowledge competency becomes a key of organizational competency to build marketing networks that have a positive impact on marketing performance. Marketing managers are required to develop their business networks to gain benefits from networking. Networking makes it easy for companies to understand changes in the environment so they can seize opportunities.
Second, the hypothesis that relational capability has a positive effect on marketing networks is accepted. From the data processing results, it is known that the CR value on the relationship between variables of relational capabilities on the marketing network is 2,897, with P value of 0.002. These values indicate the results meet the requirements which are above 1.96 for CR and below 0.05 for P. It can be concluded that the second hypothesis is proven significant, that relational capability directly has a significant effect on marketing networks. It means the higher the degree of relational capability, the higher the marketing network. The results of this study are in line with (Scholer, 2018), (Catherine K. Hart et al., 2015) explain that relational capability makes a real contribution, and it is able to maintain connections of the embedded network in the relationships between organizations so as to grow the network.
Third, the hypothesis that knowledge capability has a positive effect on marketing performance is accepted. From data processing results, it is known that the CR value on the relationship between variables of knowledge capability on the marketing network is 3,954, with P value of 0.003. These values indicate the results meet the requirements which are above 1.96 for CR and below 0.05 for P. It can be concluded that the third hypothesis is proven significant, that knowledge capability directly has a significant effect on marketing performance. It means the higher the degree of relational capability, the higher the marketing performance. The results of this study reinforce the findings from previous researchers (Taryn Jane Bond-Barnard, 2017) and (Scholer, 2018). Knowledge capacity is the company's ability to accumulate, to interact with various parties, and to collaboratewith all parties to improve marketing performance.
Fourth, the hypothesis that relational capability has a positive effect on marketing performance is not accepted. From data processing results, it is known that the CR value on the relationship between variables of relational capabilities on marketing performance is 1,885, with P value of 0.059. These values indicate the results do not meet the requirements which are below 1.96 for CR and above 0.05 for P. It can be concluded that the fourth hypothesis is proven insignificant that relational capability does not directly affect marketing performance. It means the higher the degree of relational capability, the lower marketing performance or vice versa. These results are in line with (Chuang, 2020); (R.P. Jayani Rajapathirana, 2018), (Gao, 2010), stating that relational capability has no effect on marketing performance. Companies that are given customer trust do not necessarily show good performance ( Alberto Badenes-Rocha, 2019). The company's ability to build relationships with customers and competitors cannot improve company performance because it is more concerned with quality, service, and low prices. They are not concerned with relationships because they are short-term and have interests.
Fifth, the hypothesis that marketing networks have a positive effect on marketing performance is accepted. From data processing results, it is known that the CR value on the relationship between variables of relational capability on marketing performance is 3,799, with P value of 0.002. These values indicate that the results meet the requirements which are above 1.96 for CR and below 0.05 for P. It can be concluded that the fifth hypothesis is proven as significant that marketing networks directly have a significant effect on marketing performance. It means the higher the level of marketing networks, the higher the marketing performance. These results are in line with (Patricia Martínez García de Leaniz, 2018) , (Sugiyarti & Ardyan, 2017) , marketing performance which is strongly influenced by social networks. This meansif companies are able to build and utilize social networks, marketing performance will increase. It is because companies are able to know what customers want so that companies can make products based on consumer tastes.
Conclusions
Based on testing and discussion of the hypotheses, the following conclusions are obtainedas follows:
Marketing performance can be improved through a number of alternatives including: intensifying relational capability by developing networks−doing relationship approach; and developing knowledge capability by understanding customer desires through desired products, affordable prices and good service standards.
Managerial implications
The results of study were developed into strategy formulation and effort to improve marketing performance in small and medium industries in Indonesia. Managers in every company should pay attention to factors that can affect marketing performance.
First, it encourages an increase of collaboration ability with various parties.It increases knowledge and experience in order to produce products that meet customer tastes.
Second, it improves coordination with network members to meet customer needs.
Third, it improves the ability to understand the dynamics of environmental change, and it increases the ability to understand partners.
Research limitations
First, because the research area is within a country, it is recommended that the number of samples to be increased so that it can be used for generalization.
Second, if it is viewed from the knowledge capability, the indicator of the ability to understand customer produces normality values below 0.6 so that it needs to be eliminated.Therefore, the future studies needto use indicators that support this research. Limitations are on the number of UKM and knowledge capability indicators being studied. The empirical model built from this study was only tested in a few large cities, so that this could limit the generalization of research results.
Future research agenda
Future research agenda is related to the research sample. This study uses 250 respondents as the study population. After data normality test was done, the data is ready to be processed as many as 215 respondents. In future studies, however, this number should be added for the purpose of increasing the generalization of research results. In addition, future research should use samples that are considered more representative of the study population. As a result, it can increase the generalization of research results.
