Keywords

Competitive Advantage, Innovation, Market Orientation, Market Performance, Learning Orientation.

Introduction

There is a need to measure company performance in order to determine whether it has been able to achieve its objectives. This can be in the form of the current level of performance, predicting the future, or carefully monitoring ongoing processes, and one of the major indicators of this performance is marketing. Several factors have been reported to be influencing this concept such as innovation and competitive advantage (Prasetyo et al., 2021; Prasetyo et al., 2020). This is associated with the findings that the offering of innovative and unique products in the market usually leads to high performance (Salim et al., 2021).

Several studies also showed that learning orientation has a more positive impact on organizational performance than market orientation (Kaya & Patton, 2011; Liu et al., 2002; Mahmoud et al., 2016; Perin & Sampaio, 2003; Hongming et al., 2007; Mahmoud et al., 2016). Meanwhile, previous empirical results showed that market orientation is a key factor to gain a competitive advantage (Hongming et al., 2007). This company's advantage which is also known as comparative competitive advantage or cooperative advantage also has the ability to directly affect the process of improving company performance (Day & Wensley, 1988).

Several empirical studies showed the effect of market orientation on organizational performance but there has not been final agreement among the scholars (Hongming et al., 2007). This was confirmed by Langerak (2003) after reviewing 51 relevant studies published in international journals that the positive impact of market orientation on organizational performance is questionable. This means there is a need for further studies to determine the relationship between these concepts. Therefore, this study was conducted to analyze the effect of market and learning orientation on innovation and competitive advantage and their subsequent impact on marketing performance. It also focused on analyzing the intervening roles of innovation and competitive advantage on the effect of market and learning orientation on marketing performance at PT Pegadaian. The findings are expected to be used in making empirical recommendations for the managerial financial industry and to promote business leaders to immediately implement strategic steps towards improving marketing performance considering the emergence of several competitors in the financial industry.

Literature Review

Relationship between Learning Orientation and Innovation

Knowledge-based resources are important for innovation because they increase the ability to discover and take advantage of enterprise opportunities. Meanwhile, a theory of knowledge-based firms requires that resources be defined precisely enough to determine the firms with more significant knowledge and explain how it leads to competitive advantage. It is important to note that these resources cannot be easily imitated by competitors, thereby leading to the differentiation of companies in the market.

Knowledge-based resources are intellectual properties developed based on specialized knowledge which play an important role in enterprise innovation and deter competitors from copying them. They usually include organizing principles, skills, and processes guiding organizational action. Moreover, the dissemination of knowledge throughout an organization usually helps in increasing its capacity for environmental awareness, thereby leading to an increase in the overall potential for better outcomes in innovation based on more insight and reflection of the workforce. This means knowledge-based resources are important in determining several factors such as the new product and its design as well as ensuring optimal design, cost, and reliability. Furthermore, the application of these resources based on market knowledge and awareness of competitors' capabilities normally forces companies to engage in innovative actions.

Several studies showed that learning orientation has an impact on organizational innovation (Hongming et al., 2007). This was observed from the findings of Perin & Sampaio (2003) that learning orientation can increase innovation ability in the same organizational conditions. It also leads to innovation, specifically in knowledge-intensive industries, which is driven by personal orientation and learning to serve as a source of sustainable competitive advantage. This means the impact of learning orientation abilities is not only at the initial stage of innovation but also at the implementation stage.

Relationship between Market Orientation and Innovation

Market orientation has a positive effect on (1) product quality, (2) new product success, (3) innovation performance, and (4) overall company profitability (Kaya & Patton, 2011). There are conflicting explanations concerning the relationship between market orientation and incremental innovation (Mahmoud et al., 2016). It was discovered that customer orientation stops radical innovation due to the willingness of customer-oriented companies to respond to customer demands at all times. Scholars also argued that radical innovation cannot always be realized from customers' self-described needs but customer orientation was observed to focus on product, process, and administrative innovation, despite these arguments. Moreover, market orientation is expected to allow companies to improve innovation performance in the medium and long term (Varadarajan, 2020).

Relationship between Innovation and Competitive Advantage

Previous studies related to strategic marketing showed that corporate innovation and competitive advantage processes are closely intertwined and that any type of innovation can lead to sustainable competitive advantage. It was also argued that innovation is not only central to marketing strategy but also serves as a major source of competitive advantage. This was associated with the fact that sustainable development in enterprises requires new ways of thinking and acting towards developing new products, services, and technologies. This means the quest for sustainable development is a stimulant for organizational change and an undeniable source of innovation opportunities which has the ability to generate value for companies and society as a whole (Prasetyo et al., 2020).

An innovation-based sustainability strategy can be in the form of new technologies, products, and/or processes designed to (a) minimize the environmental impact costs of business activities or (b) increase the efficiency of the use of materials and energy (Mahmoud et al., 2016; Mariadoss et al., 2011). The ability of these measures to ensure cost savings or improvements in the quality and consistency of products and services indicates their capability to serve as a major source of cost advantage (Prasetyo et al., 2021; 2020). This was confirmed by the relationship found between sustainable strategies based on innovation and competitive advantage (Mariadoss et al., 2011).

Relationship between Innovation and Marketing Performance

The resource-based view shows that competitive strategy and performance are highly dependent on the firm's specific organizational resources and capabilities. The application of this view to the strategic domain of the firm's environment also indicates that a firm's competitive advantage is rooted in its ability to facilitate environmentally sustainable economic activities. It is also important to note that the environmental strategy of company depends on its ability to distribute resources towards the development of basic strategic competencies. This was further confirmed by previous studies that enterprise capabilities have the ability to play an important role in developing innovation-based sustainability strategies.

These capabilities are different competencies considered to be new, valuable, present positive value to the market, and difficult for current competitors to imitate and replace (Gunarto et al., 2021). The ability of company's sustainability-based innovation strategy to drive its market study efforts, selection of its target markets, product development processes, market communication programs, and delivery processes is very critical to the movement of its products or services through the value chain. Previous studies also argued that marketing ability affects all types of innovations conducted by companies and that its performance is influenced by innovation-based sustainable strategies (Mariadoss et al., 2011). This indicates the possible effect of innovation and competitive advantage on marketing performance.

Relationship between Competitive Advantage and Marketing Performance

Marketing resources represent a broad value proposition which affects stakeholders in any business as well as company that generally uses them to gain a competitive advantage in the marketplace. These resources include tangible or intangible value propositions, physical or human processes, and intellectual or relational property which vary in their direct or indirect contribution to competitive advantage.

According to the multidimensional approach, business performance in the context of this study was assessed based on marketing effectiveness which is broadly defined to include the introduction of new products in line with study innovation. Therefore, the marketing effectiveness concept captures sales growth, gains in market share, and successful product introduction. Meanwhile, market share is considered a strong performance metric and a strong predictor of cash flow and profitability. This is based on the logic that firms benefitting from the scale effect usually have the ability to lower costs and earn higher profits than competitors with lower market shares. This means a gain in market share can be used as a more appropriate and accurate measure because it reflects the adaptation to a changing environment.

The concepts explained were used to develop the study framework as indicated in Figure 1.

Study Methods

The scope of this study is related to market and learning orientation, innovation, and competitive advantage, as well as their effects on marketing performance while the objects are the agents of PT. Pawnshops in Indonesia. It was conducted to determine and explain the influence of independent variables on the dependent variable, either directly or indirectly through the intervening variables.

There are 814 pawnshops spread across South Sumatra, Indonesia, and all their agents were classified as the population for this study while the samples used were those at the PT Pegadaian. The number of those to be selected was based on the requirement of SEM used for data analysis, and this is in line with the findings of Gunarto et al. (2021) that the simulation conducted using Maximum Likelihood (ML) estimation produced valid and stable results but the validation level is expected to increase with the increase in the sample size. Moreover, it was suggested that the sample for the SEM method is 200, but an increase to >400 usually causes more sensitivity, thereby, leading to a bad Goodness of fit. Therefore, Hair et al. (2014) recommended the use of 100-400 as samples in the SEM-BC method.

Characteristics of Respondents

The survey was conducted on 220 respondents who are PT Pegadaian agents, and their characteristics are presented in the following Table 1.

Table 1 Characteristics Of Respondents
Characteristics		Frequency	Percent
Gender	Male	88	40.0
	Female	132	60.0
Respondent Age	<20 Years	3	1.4
	20-30 Years	19	8.6
	30-40 Years	101	45.9
	40-50 Years	77	35.0
	>50 Years	20	9.1
Agent Age	2 Years	22	10.0
	3 Years	97	44.1
	4 Years	90	40.9
	>5 Years	11	5.0
Turnover	<100 Million	50	22.7
	100 - 500 Million	93	42.3
	500 - 1 Billion	55	25.0
	>1 Billion	22	10.0

The characteristics represent the trend among the population with most of PT Pegadaian agents discovered to be women, between 30-40 years, have 3-4 years of experience, and generate monthly turnover between 100-500 million.

Measurement Model

The measurement model for each variable was analyzed using confirmatory factor analysis (CFA), and the results of the validity and reliability test conducted on the Market Orientation model are presented in the following Table 2.

Table 2 Loading Factor And Reliability Values Of The Market Orientation Model
Dimension	Indicator	Factor loading (?)	Quadratic Factor loading (?2)	Error (e)	Notes
Customer Orientation	OPEL1	0.74	0.548	0.452	Valid
	OPEL2	0.83	0.689	0.311	Valid
	OPEL3	0.82	0.672	0.328	Valid
	OPEL4	0.76	0.578	0.422	Valid
Competitor Orientation	OPES1	0.83	0.689	0.311	Valid
	OPES2	0.87	0.757	0.243	Valid
	OPES3	0.77	0.593	0.407	Valid
	OPES4	0.77	0.593	0.407	Valid
Coordination between Functions	KOAF1	0.79	0.624	0.376	Valid
	KOAF2	0.86	0.740	0.260	Valid
	KOAF3	0.88	0.774	0.226	Valid
	KOAF4	0.86	0.740	0.260	Valid
TOTAL		9.78	8.00	4.00
Construct Reliability (CR)		0.960			Reliable
Average Variance Extract (AVE)		0.666

The Market Orientation Model was declared valid because all its 12 indicators have a loading factor (λ) greater than 0.5 as indicated in Table 2. It was also declared reliable because the CR value is greater than 0.7 (CR=0.960) and the AVE value is greater than 0.5 (AVE=0.666). This means the indicators formulated in the measurement model of the Market Orientation variable are valid and reliable.

The results of the validity and reliability test of the Learning Orientation model are also presented in Table 3.

Table 3 Loading Factors And Reliability Values Of The Learning Orientation Variables
Dimension	Indicator	Factor loading (?)	Quadratic Factor loading (?2)	Error (e)	Notes
Commitment to learning	KB1	0.89	0.792	0.208	Valid
	KB2	0.91	0.828	0.172	Valid
	KB3	0.68	0.462	0.538	Valid
Shared Vision	VB1	0.89	0.792	0.208	Valid
	VB2	0.91	0.828	0.172	Valid
Various Views	BP1	0.89	0.792	0.208	Valid
	BP2	0.85	0.723	0.278	Valid
TOTAL		6.02	5.22	1.78
Construct Reliability (CR)		0.953			Reliable
Average Variance Extract (AVE)		0.745

The Learning Orientation CFA model which has seven indicators from three aspects was also declared valid because all its indicators have a loading factor value (λ) greater than 0.5 as presented in Table 3. It was also declared reliable because its CR value is greater than 0.7 (CR=0.953) and the AVE value is greater than 0.5 (AVE=0.745). This means the indicators formulated in the measurement model of the Learning Orientation variable are valid and reliable.

The results of the validity and reliability test of the Innovation model are indicated in Table 4.

Table 4 Loading Factors And Reliability Values Of The Innovation Variables
Dimension	Indicator	Factor loading (?)	Quadratic Factor loading (?2)	Error (e)	Notes
Product Expansion	INOV1.1	0.83	0.689	0.311	Valid
	INOV1.2	0.92	0.846	0.154	Valid
	INOV1.3	0.78	0.608	0.392	Valid
Product Imitation	INOV2.1	0.78	0.608	0.392	Valid
	INOV2.2	0.87	0.757	0.243	Valid
New product	INOV3.1	0.90	0.810	0.190	Valid
	INOV3.2	0.85	0.723	0.278	Valid
TOTAL		5.93	5.04	1.96
Construct Reliability (CR)		0.947			Reliable
Average Variance Extract (AVE)		0.720

The Innovation CFA model which consists of seven indicators and three aspects was also declared valid because all its indicators have a loading factor (λ) value of more than 0.5. It was also declared reliable considering the fact that its CR value is greater than 0.7 (CR=0.947) and the AVE value is greater than 0.5 (AVE=0.720). This means the indicators formulated in the measurement model of the Innovation variable are valid and reliable.

The results of the validity and reliability test of the Competitive Advantage model are shown in Table 5.

The CFA Competitive Advantage model with nine indicators and three aspects was also found to be valid due to the fact that all its indicators have a loading factor (λ) value of more than 0.5 as presented in Table 5. It was also declared variable because its CR value is greater than 0.7 (CR=0.955) and the AVE value is greater than 0.5 (AVE=0.701). This means the indicators formulated in the measurement model of the Competitive Advantage variable are valid and reliable.

Table 5 Loading Factor And Reliability Values Of The Competitive Advantage Variables
Dimension	Indicator	Factor loading (?)	Quadratic Factor loading (?2)	Error (e)	Notes
Product Uniqueness	CA1.1	0.87	0.757	0.243	Valid
	CA1.2	0.87	0.757	0.243	Valid
	CA1.3	0.80	0.640	0.360	Valid
Product quality	CA2.1	0.81	0.656	0.344	Valid
	CA2.2	0.88	0.774	0.226	Valid
	CA2.3	0.87	0.757	0.243	Valid
Competitive Price	CA3.1	0.78	0.608	0.392	Valid
	CA3.2	0.82	0.672	0.328	Valid
	CA3.3	0.83	0.689	0.311	Valid
TOTAL		7.53	6.311	2.689
Construct Reliability (CR)		0.955			Reliable
Average Variance Extract (AVE)		0.701

The results of the validity and reliability test of the Marketing Performance model are shown in Table 6.

The CFA Marketing Performance model with nine indicators and three aspects was also declared valid due to the fact that all its indicators have a loading factor (λ) value of more than 0.5 as presented in Table 6. It was also declared reliable because its CR value is greater than 0.7 (CR=0.985) and the AVE value is greater than 0.5 (AVE=0.878). This means the indicators formulated in the measurement model of the Marketing Performance variable are valid and reliable.

Table 6 Loading Factor Value And Reliability Of Marketing Performance Model
Dimension	Indicator	Factor loading (?)	Quadratic Factor loading (?2)	Error (e)	Notes
Sales Volume	MP1.1	0.91	0.828	0.172	Valid
	MP1.2	0.93	0.865	0.135	Valid
	MP1.3	0.92	0.846	0.154	Valid
Customer Growth	MP2.1	0.93	0.865	0.135	Valid
	MP2.2	0.94	0.884	0.116	Valid
	MP2.3	0.94	0.884	0.116	Valid
Profit Increase	MP3.1	0.96	0.922	0.078	Valid
	MP3.2	0.96	0.922	0.078	Valid
	MP3.3	0.94	0.884	0.116	Valid
TOTAL		8.43	7.898	1.102
Construct Reliability (CR)		0.985			Reliable
Average Variance Extract (AVE)		0.878

Structural Model Analysis

CFA for each variable was followed by an analysis of the full structural model and the estimation results are presented in Figure 2.

Figure 2 shows the magnitude of the parameter values in the relationship between the existing latent variables and of the loading factor values for each indicator that forms the latent variable. The existing parameter values showed that the relationships between exogenous and endogenous variables are negative while some are positive. Moreover, the magnitude of the direct influence and the role of each intervening variable is presented in the figure, and it was discovered that exogenous have positive effects on endogenous variables except for the effect of Market Orientation on college performance.

The test results for each parameter of the structural model are presented in Table 7.

Table 7 Results Of The Relationship Between Latent Variables
Models	Endogenous Variables		Exogenous/ Endogenous Variables	Estimate	S.E.	t- Value	Notes	R2
Model (1)	Innovation (INNOVATI)	←	Market Orientation (MARKET_O)	0.46	0.10	4.53	Significant	0.77
	Innovation (INNOVATI)	←	Learning Orientation (LEARNING)	0.44	0.12	4.32	Significant
Model (2)	Competitive Advantage (COMPETIT)	←	Market Orientation (MARKET_O)	0.50	0.12	4.17	Significant	0.60
	Competitive Advantage (COMPETIT)	←	Learning Orientation (LEARNING)	0.30	0.12	2.56	Significant
Model (3)	Marketing Performance (PERFORME)	←	Market Orientation (MARKET_O)	-0.00	0.10	-0.03	Not Significant	0.82
	Marketing Performance (PERFORME)	←	Learning Orientation (LEARNING)	-0.16	0.09	-1.59	Not Significant
	Marketing Performance (PERFORME)	←	Innovation (INNOVATI)	0.49	0.09	5.30	Significant
	Marketing Performance (PERFORME)	←	Competitive Advantage (COMPETIT)	0.64	0.07	9.09	Significant

Table 7 shows that 6 out of 8 hypotheses proposed are accepted and significant while 2 are not significant. Those observed not to be significant because their t-values are less than 1.96 include the effect of Market Orientation on Marketing Performance and the effect of Learning Orientation on Marketing Performance.

Discussion

Model (1) shows that market and learning orientation simultaneously affect Innovation. This means an increase in these two factors has the ability to improve the innovation ability of PT Pegadaian. Their influence was observed to be partially the same with each contributing 45% each and the magnitude of their influence was recorded to be 75% while the remaining 25% is caused by other factors such as competence, uniqueness of resources, and several others.

This shows that market and learning orientation are both resources used by companies to achieve a competitive advantage. In the context of product innovation, market orientation represents the extent to which company acquires, distributes, uses, and ultimately relies on customer, competitor, and supplier market information as input in the innovation process (Gunarto et al., 2021; Prasetyo et al., 2021; Prasetyo et al., 2020). Meanwhile, learning orientation embodies the extent to which company is committed to systematically challenging the fundamental beliefs and practices that define the innovation process itself.

This was further confirmed by previous study that both market and learning orientation are keys to successful innovation and product performance (Prasetyo et al., 2021). Several companies are market-oriented but cannot increase the success rate of their new products. It was discovered from this study that the marketing concept existing for several years in these companies is one of the strategic frameworks to provide a sustainable competitive advantage (SCA). This is associated with the findings that strong market orientation can increase the ability to develop service products desired by customers and its combination with the desire to understand customer desires usually leads to strong competitive advantage.

The factor with the most dominant influence on marketing performance was found to be competitive advantage followed by innovation. This means a higher competitive advantage of company usually leads to higher marketing performance. Meanwhile, recent studies conducted to understand the role of market and learning orientation on innovation processes and organizational performance have not been able to measure the relative importance of the two constructs because they do not examine their effects simultaneously. This is an important issue for managers because it is better to inform them about organizational traits with possible effects on market performance. The finding of this present study is not in accordance with the previous estimation that market and learning orientation do not have a direct effect on marketing performance but have an indirect effect through innovation and competitive advantage.

The main contribution of this study to marketing performance is the development of a model that simultaneously tests the ability of market and learning orientation to directly affect marketing performance and indirectly through innovation and competitive advantage. Moreover, the main implication is that market and learning orientation have an equally important role in increasing innovation which ultimately has an impact on marketing performance at PT Pegadaian.

These results reinforce previous study and suggest that both market and learning orientation mediated by innovation and competitive advantage are the keys to company's successful marketing performance. This study also shows new findings that market and learning orientation are driving forces for innovation and competitive advantage which further have a direct influence on marketing performance. It is also important to reiterate that marketing performance is one of the indicators of company’s achievement which determines its success in the market. Moreover, businesses need internal support such as innovation and external support such as market search, promotion, and technology (Salim et al., 2021) which are normally used to determine the performance of their products in the market. According to Ferdinand (2003), marketing performance is a factor often used to measure the impact of the existing strategies implemented by company. Meanwhile, organizational performance is the outcome produced after a process and compared with company targets (Yuliansyah et al., 2021). It is important to note that the improvement in the marketing performance of local products normally leads to an increase in foreign market opportunities.

Product innovation has the capacity to create several product designs required to increase alternative choices, benefits, or value for consumers and ensure the expected increase in product quality (Varadarajan, 2020; Hongming et al., 2007). It is also considered important in the business world due to its ability to support the creation of a new product in terms of appearance, system, process, and other aspects. It has also been previously reported that innovative and products usually perform excellently in the market (Salim et al., 2021). Meanwhile, innovation is defined as the creativity of an individual which has an important influence on marketing performance, and this was confirmed by the findings of previous study that innovation has a positive effect on marketing performance (Mariadoss et al., 2011; Prasetyo et al., 2021; Prasetyo et al., 2020; Yuliansyah et al., 2021). This means an increase in product innovation is expected to lead to a significant improvement in marketing performance (Salim et al., 2021).

Conclusion

Market and learning orientation directly have a significant effect on innovation with both observed to have a balanced influence. They were also observed to have a direct significant influence on competitive advantage but learning orientation was more dominant in this case. This means innovation and competitive advantage are good intervening variables for the relationship between market orientation and marketing performance as indicated by the fact that the direct effect is smaller than the indirect and the same trend was also observed for the relationship between learning orientation and marketing performance.

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Received: 21-Jan-2022, Manuscript No. ASMJ-22-10941; Editor assigned: 24-Jan-2022, PreQC No. ASMJ-22-10941(PQ); Reviewed: 04-Feb-2022, QC No. ASMJ-22-10941; Revised: 14-Feb-2022, Manuscript No. ASMJ-22-10941(R); Published: 21-Feb-2022