How to Boost Your Firm's Digital Marketing Capability?

The development of information technology, media, and telecommunication technology, in this case, digitalization, impacts consumer and producer behavior changes. Companies must undergo marketing transformations in order to improve their marketing performance in the digital era. Research on the adoption of digital marketing, the factors that drive the use of digital marketing, digital transformation, and digital marketing capability have been widely carried out. However, research that aims to investigate the relationship between these four concepts simultaneously and in an integrated model is still very rare, especially research models to build the digital marketing capability of companies in Indonesia. This study aims to develop a strategy for improving the firm's Digital Marketing Capability (DMC) in Indonesia based on the innovation ecosystem readiness, adoption, and digital transformation. We collect samples from 2,759 business contacts from one of Indonesia's national television stations via email and WhatsApp applications. After that, we have 217 volunteers who fill out a website with these research questions. Partial Least Squares Structural Equation Modeling (PLS-SEM) is used to analyze data successfully collected. The innovation ecosystem readiness directly impacts a firm's digital marketing capability, as well as digital transformation and digital marketing adoption. Furthermore, digital transformation and adopting digital marketing technologies significantly mediate the relationship between innovation ecosystem readiness and digital marketing capability. Therefore, companies must build an innovation ecosystem readiness, carry out digital transformation, and adopt digital marketing in order to improve their firm's DMC.

Digital marketing capability; Digital transformation; International Disability Alliance (IDA) strategic circle; Partial Least Squares-Structural Equation Modeling (PLS-SEM)

The development of information technology, media, and telecommunication technology has improved consumer-producer interaction. Consumers with specific motivations and awareness can search, discuss, provide suggestions, and even receive direct responses while looking for a company's product or service (Agus et al., 2021; Noyola-Medina, Pinzón-Castro, and Maldonado-Guzmán, 2018; Teixeira et al., 2018; Bakhtieva, 2017). Firms prepare themselves to respond to the needs and interests of their consumers. They also learn how to reach and engage their consumers through valuable information. In this regard, businesses are confronted with a new marketing paradigm and and must adapt to unprecedented changes in the marketing landscape (Miklosik et al., 2019; Nielsen CMO Report, 2018; Sathya, 2017; Yasmin et al., 2015; Järvinen et al., 2012).

Digital marketing has become a part of global life which is a new way for business actors to carry out communication and marketing activities to their consumers. In its development, digital marketing methods are applied through various digital media such as cellular technology, websites, social media platforms, and other digital media. This has implications for every business actor to continue to adopt new ways to communicate with consumers through digital media that continue to grow (Datareportal, 2022; Alghizzawi, 2019; Taiminen and Karjaluoto, 2015). Research on the adoption of digital marketing, the factors that drive the use of digital marketing, digital transformation, and digital marketing capability have been widely carried out (Gillpatrick, 2020; Morakanyane, 2020; Field, Patel, and Leon, 2019; Srividhya, 2019; Vial, 2019; Yaseen, 2019; Gibson, 2018; Chaffey and Smith, 2017; Chaffey and Ellis-Chadwick, 2016; Trainor et al., 2010).   However, research that investigates the relationship between these four concepts simultaneously and in an integrated model is still very rare.

Furthermore, previous research on digital marketing has concentrated on the consumer level rather than the corporate level (Tiago and Veríssimo, 2014). This study presents a concurrent relationship between the innovation ecosystem readiness with digital marketing capability, as well as the adoption of digital marketing and the digital transformation of companies in one integrated model from the perspective of business actors. Figure 1 depicts the research framework.

Figure 1 Research Framework

Some of the hypotheses proposed in this study are as follows:

H1:   Innovation ecosystem readiness has a positive effect on digital transformation
H2:   Innovation ecosystem readiness has a positive effect on digital marketing adoption
H3:   Innovation ecosystem readiness has a positive effect on digital marketing capability
H4:   Digital transformation has a positive effect on digital marketing adoption
H5:   Digital transformation has a positive effect on digital marketing capability
H6:   Digital marketing adoption has a positive effect on digital marketing capability
H7:   The combination of digital transformation and digital marketing adoption mediates the relationship between innovation ecosystem readiness and digital marketing capability.

2.1. Population and sample

      The study population consists of 2,759 business contacts from one of Indonesia's national television channels, with relevant data on company owners, directors, general managers, and or managers whose companies have advertised on television in the previous five years. The final sample consists of respondents who voluntarily agreed to complete this survey.

2.2. Data collection method

We used 2,759 business contacts obtained from an Indonesian national television station, which included information on firm owners, directors, general managers, managers, and/or those involved in boosting the company's marketing performance.  Throughout July and December 2021, all company contacts were routed to a website containing research questions via email and the WhatsApp application. This study collected 217 responses who successfully completed the questionnaire via the research website, utilizing the voluntary sample survey sampling method as a new non-probability sampling design (Muraiwa, 2015).

2.3. Sample Size

        Sample size recommendations in PLS-SEM can be based statistical power analysis rules of thumb (Hair Jr et al., 2017). This study would require a minimum of 179 observations to achieve a statistical power of 80%. A larger number of samples will increase the precision of the Partial Least Square-Structural Equation Modelling (PLS-SEM) estimation. In this regard, this study succeeded in obtaining a voluntary sample size of 217 which was ready to be analyzed from 2,759 business contacts who were successfully contacted via email and WhatsApp application.

3.1.   Respondent Characteristics

According to the findings of this study, as shown in Table 1, more than 57 percent of respondents are Gen-X (1965-1979) or in the age range of 42-56 years, and 36 percent are Millennials (1980-1994) or in the age range of 27-41 years. This study also discovered that only a few, or about 7%, were Baby Boomers (1944-1964) or older than 56 years. The gender distribution of respondents was 71 percent for men and 29 percent for women. The education profile data reveal an intriguing finding: more than half of respondents are postgraduates, 47 percent are undergraduates, and only 1 percent have a diploma education background.

In terms of tenure, approximately 40% have worked for more than 10 years, 25% have worked for 5 to less than 10 years, 20% have worked for 2 to less than five years, and the remaining 15% have worked for less than two years. According to the data, 13% own businesses, 21% are directors and or CEOs, and 33% are general managers and or senior managers. The remaining supervisors have 33% of the vote.

Companies where respondents work are from various industrial sectors in Indonesia, including office equipment, computer, communications, financial, education, medicine or pharmaceutical, media, food, industrial products, transportation, travel, property, beverages, toiletries & cosmetics, automotive, apparel or personal accessories, smoking, household equipment & appliances, retail, household product, and baby & maternity product. In this study, approximately 60% of companies have more than 100 employees, and 73% of companies have been in operation for more than ten years.

Table 1 Respondent characteristics

3.2. PLS-SEM Evaluation for Firm's Digital Marketing Capability

The model for improving digital marketing capability has three latent variables with reflective measurement models (i.e., DMAER (Digital Marketing Adoption Eco-System Readiness), DT (Digital Transformation), and DMC (Digital Marketing Capability)) as well as a single-item construct (DMA Index (Digital Marketing Adoption Index)). Figure 2 shows PLS-SEM results for this research model. All outer loadings have a significant (p-value <0.05) estimated value for the relationships between the reflective latent variables and their indicators. On the DMC latent variable, the indicator Reach has the smallest outer loading value (0.711), while the indicator Governance has the highest indicator outer loading value (0.848). On the DT latent variable, the indicator Technology Leadership has the smallest outer loading value (0.688), while the indicator Improving Operation has the highest outer loading value (0.843).   On DMAER latent variable, the indicator of innovation infrastructure has the smallest outer loading value (0.574), while the indicator of organizational readiness has the highest outer loading value (0.842).

In general, indicators with outer loading values less than 0.4 can be directly omitted from the model, while values between 0.40 - 0.70 can be considered omitted from the measurement model if and only if the 'disappearance' increases the value of the composite reliability. In this study, eliminating indicators in the interval of 0.4 - 0.7 did not increase composite reliability. Another reason to avoid eliminating indicators with an outer loading value of 0.70 is that content validity factors will change the meaning of research variables (Hair Jr et al., 2017).

H1: The innovation ecosystem readiness has a positive effect on digital transformation

The results of this study show that innovation ecosystem readiness significantly influences digital transformation (path coefficient = 0.772, p-value < 0.05). The higher readiness of the innovation ecosystem owned by the company will encourage the digital transformation process within the company. Organizational readiness, managerial innovativeness, flexibility, and perceived usefulness are the most dominant indicators in increasing the readiness of the innovation ecosystem (outer loading > 0.80), while improving operation, governing the transformation, and reinvention of business models are the most dominant indicators in enhancing transformation enterprise digital (outer loading > 0.80). This can mean that the attitude in responding to business changes will increase the company's efforts to carry out digital transformation.

H2: The innovation ecosystem readiness has a positive effect on digital marketing adoption

The results of this study show that the innovation ecosystem readiness does not significantly influence digital marketing adoption (path coefficient = 0.114, p-value = 0.318 or >0.05). The higher readiness of the innovation ecosystem owned by the company does not necessarily encourage companies to adopt digital marketing tools and techniques. This means that attitudes in responding to business changes do not necessarily directly affect companies adopting digital marketing.

        H3: The innovation ecosystem readiness has a positive effect on digital marketing capability

        The results of this study show that innovation ecosystem readiness significantly influences digital marketing capability (path coefficient = 0.259, p-value<0.05). The higher readiness of the innovation ecosystem owned by the company will encourage the company’s efforts to increase digital marketing capability. This means that attitudes in responding to business changes have direct implications for companies to improve digital marketing capability.

        H4: Digital transformation has a positive effect on digital marketing adoption

        The results of this study show that digital transformation significantly influences digital marketing adoption (path coefficient = 0.336, p-value <0.05). The higher the digital transformation carried out by the company will increase the company's activities to adopt more effective digital marketing. Improving operations, governing the transformation, and reinvention of business models are the most dominant indicators in increasing the company's digital transformation (outer loading > 0.80). This means that changes made by companies to improve digital capability and leadership capability will directly affect companies' adoption of effective digital marketing.

        H5: Digital transformation has a positive effect on digital marketing capability

        The results of this study show that digital transformation significantly influences digital marketing capability (path coefficient = 0.555, p-value < 0.05). The higher the digital transformation the company carries, the higher its digital marketing capability. This means that changes made by the company to improve digital and leadership capabilities will directly impact companies to improve their digital marketing capability.

        H6: Digital marketing adoption has a positive effect on digital marketing capability

        The results of this study show that digital marketing adoption significantly influences digital marketing capability (path coefficient = 0.125, p-value < 0.05). The more effective the adoption of digital marketing by the company will increase its digital marketing capability.

        H7: The combination of digital transformation and digital marketing adoption is a mediator for the relationship between innovation ecosystem readiness and digital marketing capability

        The indirect influence of DMAER on DMC is significant, confirming that the interaction between DT and DMA acts as partial mediation (complementary mediation) between DMAER and DMC. DMAER's indirect influence on DMA via DT is particularly significant, whereas DMAER's direct influence on DMA is negligible, confirming that DT acts as full mediation or indirect-only mediation between DMAER and DMA. Table 2 shows each research construct's direct, indirect, and total influence.

Table 2 Significance and relevance of mediation variable

        These findings support the seventh hypothesis of the study, which states that the combination of digital transformation and digital marketing adoption serves as a mediator in the relationship between innovation ecosystem readiness and digital marketing capability.

        Based on the results of measurement model testing, structural model testing, and model accuracy testing, it is possible to conclude that the research model has been able to measure the role of innovation ecosystem readiness on digital marketing capability, either directly or indirectly via a combination of digital transformation and digital marketing adoption.

3.3.   Strategy to Improve Firm's Digital Marketing Capability in Indonesia

We propose the IDA business strategy based on established research hypotheses. The IDA circle is a strategy to improve the company's digital marketing capability. As illustrated in Figure 3, the IDA circle represents a synergy of three aspects of increasing digital marketing: (1) optimizing the readiness of the innovation ecosystem, (2) building and developing digital transformation, and (3) utilizing digital marketing tools and techniques. The competitive strategy using the IDA circle relies on three competitive strategy models in marketing, namely (1) a market-based strategy, (2) a resource-based strategy, and (3) a dynamic-capability strategy. Furthermore, this research finds that Companies that tend to use a resource-based strategy will not have better digital marketing capability than companies that rely on a market-based strategy, while companies that use dynamic capability will have much higher digital marketing capability compared to a company that uses a resource-based or market-based strategy. The IDA circle emphasizes the need for resource-based implementation through the use of technology and digital marketing techniques owned by the company, market-based implementation through the readiness of external, internal, and technological ecosystems, and finally, through the application of dynamic capability as a company's internal adaptive response to changes in its external business environment. A digital transformation is a form of dynamic capability companies carry to adapt to their business environment.

Figure 3 The IDA strategic circle as a business strategy to improve the company's digital marketing capability

Building the innovation ecosystem readiness cannot be separated from managerial innovativeness, organizational readiness, and perceived usefulness (Babkin et al., 2021; Bencsik, 2020). Managerial innovativeness is a characteristic of attitudes in dealing with change, future orientation, proactiveness, and support for change (Doe et al., 2017). This is related to leadership orientation (Doe et al., 2018). While organizational readiness is the scope, size, managerial structure, organizational resources, business processes, creativity, and openness owned by the organization (Doe et al., 2017). This is related to organizational learning (Doe et al., 2018). Perceived usefulness is the extent to which a person believes that using digital technology will improve performance or work results (Doe et al., 2017; Krapf, 2022; Ritz, Wolf, and McQuitty, 2019). The three most important indicators in the innovation ecosystem readiness variable can be applied through developing a growth mindset owned by leaders and organizations to offer value propositions to customers in the realm of digital marketing.

Building and developing digital transformation cannot be separated from improving operations (0.843), governing the transformation (0.838), and reinvention of a business model (0.808). Westerman, Bonnet, and McAfee (2014) stated that improving operations and reinventing business models is one way for companies to build digital capabilities, or in other words, build a better business through technology, not the technology itself. Employee experience and business model innovation, digital platforms, will strengthen other elements and enable continuous innovation if structured and managed properly (Smart Insight, 2022; Smart Insight, 2020; MIT Sloan Management Review, 2018).

Digital marketing techniques and methods used by companies in Indonesia show that more than 70% of companies use websites, social media, mobile marketing, online advertising, content marketing, and digital analytics. The combination of these methods is considered to be able to produce an effective digital marketing strategy, which can increase consumer reach and engagement with the company.

    The results of this research have found that the innovation ecosystem readiness directly influences increasing the company's digital marketing capability, as well as for digital transformation and adoption of digital marketing technology. In addition, digital transformation and the adoption of digital marketing technology significantly mediate the relationship between innovation ecosystem readiness and digital marketing capability. Companies with a good innovation ecosystem readiness will tend to carry out digital transformation (0.772) rather than directly adopt digital marketing (0.114) because they understand that digital marketing adoption without digital transformation will result in low digital marketing capability levels. This study confirms that digital marketing capability is about more than just implementing digital marketing technology; it is also about how companies can integrate these technologies into their business processes. Furthermore, companies that use dynamic capability will have much higher digital marketing capability compared to a company that uses a resource-based or market-based strategy only.   Finally, companies must use IDA strategic circle as a business strategy to improve their digital marketing capability by (1) building an innovation ecosystem readiness, (2) carrying out digital transformation, and (3) adopting digital marketing.

Recommendations

        Despite the study's success in demonstrating a framework model for increasing a company's digital marketing capabilities, the number of samples and discussions for each industrial sector in Indonesia needs to be expanded and deepened. The framework developed in this study can be used to conduct research on digital marketing capability in each industrial sector.

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