Does Digital Leadership Impact Directly or Indirectly on Dynamic Capability: Case on Indonesia Telecommunication Industry in Digital Transformation?

The Journal of Social Sciences Research ISSN(e): 2411-9458, ISSN(p): 2413-6670 Special Issue. 2, pp: 832-841, 2018 URL: https://arpgweb.com/journal/journal/7/special_issue DOI: https://doi.org/10.32861/jssr.spi2.832.841 Original Research Academic Research Publishing Group Open Access Does Digital Leadership Impact Directly or Indirectly on Dynamic Capability: Case on Indonesia Telecommunication Industry in Digital Transformation? Leonardus W Wasono Mihardjo* Bina Nusantara University, Indonesia Riza A.N. Rukmana Telkom University, Indonesia Abstract Telecommunication sectors are the area where the digital disruption has taken significant influence to the incumbent firms. The market become more competitive and dynamic, hence, it will be required the incumbent firms to transform to have a dynamic capability. In digital era, The development of dynamic capability is driven from the role of digital leader. According to digital disruption view, the activities process derived from the customer and market orientation, and due to the nature of digital become global the alliance capability is important to study. Due to the important role of digital leadership and limitation study on the effect digital leadership in developing dynamic capability, this study will assess the effective path analysis of the role digital leadership in developing dynamic capabilities. Does the digital leadership has direct influence to dynamic capability, or indirect influence through market orientation capabilities or alliance capabilities?. The study was conducted on 88 respondents who are senior level from Indonesia telecommunication companies. The statistical data analysis used Smart-PLS application. The result explained that digital leadership impacts directly and indirectly through mediation variable of market orientation.. While the mediation role of alliance capability has shown not significant influence in relationship between dynamic capability and digital leadership.. This finding has implication on strategic initiative in dealing dynamic capability, where the digital leadership shall focus on market orientation to create the optimal value to face the current and future business challenges. Keywords: Digital leadership; Dynamic capability; Market orientation; Alliances capabilities. CC BY: Creative Commons Attribution License 4.0 1. Introduction Phenomenon of technology disruptive has challenged for incumbent firm to adapt to the changing and dynamical of market due to new business model brought by new entrances (Christensen, 1997). The incumbents did not have the inertia to adapt the changing of environment and market based on the customer mainstreams (Christensen and Bower, 1996). The innovation and management leader attentions focus on the innovation on exploit the existing asset and less focus the market. Hence the institutional are required to transform to have dynamic capability to renew business model innovation after disruptions (Chesbrough and Rosenbloom, 2002; Zott et al., 2011). Dynamic capability is defined as a holistic approach of the firm ability to integrate, build and reconfigure their resources and competence to address the changing of market environments’ (Teece et al., 1997). The capability to reconfigure will create innovation and change the paradigm of management firm. This capability hereinafter referred to as a transformation. The transformation is essential to have better response and enabling business agility to optimize business performance. In industry 4.0 where digital technology based on internet and cloud become more dominant, the incumbent firm have to embark to digital transformation. Digital transformation mostly uses an innovation of business model supported with the digital technology and applied in all aspects of human society (Stolterman and Fors, 2004). Digital transformation is mostly started through digitization that dealing with technological innovation (Kagermann, 2015). The case of book retail like borders in book industry is example of digital transformation from physical books to e-books (Liu, 2012). The case of market orientation and the changing of customer and social network due to Internet technology social has been discussed and become a main driver of incumbent to refocus the strategy (Berman, 2012). Digital transformation requires the capability to do collaboration and form alliance strategy (Belk, 2013; Berman, 2012) However, by the role of leader and human capital has significant influence in driving the digital transformation, especially in term of decision-making process (Kohli R. and Johnson, 2011; Liu, 2012). Study done by International Business Machine among 50 CEO in the world reveal to capture value from the new technologies, incumbents need to have dynamic capability by increasing external knowledge access through focus on market orientation and developing alliances capability (IBM Institute for Business Value, 2012). The leader vision especially in bringing digital leadership vision is important to set up the direction and guidance for long term in optimizing and reconfiguring new paradigm of transformation. The digital leadership has been introduced as the combining of culture and competence of leader in bringing new architype in exploring the benefit of use digital technology (Rudito and Sinaga, 2017; Wasono and Furinto, 2018). The study of Indonesia telecommunication market is interested to explore since Indonesia is the early stage of digital era (Das et al., 2016) but in term of *Corresponding Author 832 The Journal of Social Sciences Research innovation growth, Indonesia is part of a country that has high growth of innovation during last couple years (IMD, 2017). There was gap between Indonesia nation competitiveness and digital infrastructure competitiveness. The ranking of digital infrastructure was lack behind compare to Nation competitiveness (IMD, 2017). It is required acceleration of Indonesia firm in digital transformation to support nation competitiveness. Hence exploring the model digital transformation for incumbent firm in Indonesia are essential to be explored in development of dynamic capability focus on the role of digital leadership. In this paper, we intend to provide an empirical result on digital transformation for the role of digital leadership in development of dynamic capability. We will discuss the following questions: • Does the digital leadership impact directly or indirectly through market orientation or alliance capability on dynamic capability for Indonesia telecommunication industry in digital Transformation? • How does the effective path to transforms to form dynamic Capability? This paper is organized as follows: the literature review will be discussed in Section 2, thus section 3 describes the research methodology. The results, Discussion and implications of proposed digital transformations models are presenting in section 4 and Section 5 respectively. Finally, section 6 will explain the conclusion and provides further future study. 2. Literature Review 2.1. Dynamic Capability (DC) DC theory addresses the issues associate with the inertia, routines activities and rigidities of strategic firm resources and competences. It has been discussed and studies extensively since started published in science literature (Teece et al., 1990). DC defined as the firm's ability to integrate, build, renew and reconfigure resources and competencies either internal or external to adapt with the changing of environments (Teece et al., 1997). The study of DC was forming the use of DC as a process of organization learning to create new market by integrating, reconfiguring, gaining and releasing resources (Eisenhardt and Martin, 2000). This DC concept is aligned with the need of incumbent firm to have agility in adapting change of market and environment in disruptive market. In organization theory the dynamic capability is the organization capability to have the ability for learning and change. On response to learning and change, the incumbent firm can build innovation capability by alignment of exploration and exploitation (O’Reilly and Tushman, 2008), discontinuous change (Martin and Eisenhardt, 2004) and on radical innovation capabilities (O’Connor et al., 2008). The intangible of knowledge and learning is part of distinct management capability that enable the organization to have adaptive capability by building on the stock of existing knowledge in new domains (Cattani, 2008). The leadership and strategic vision are important to ensure the alignment, integration and interaction between top-management cognition in building strategic decision-making and for reconfiguring the firm resources base (Martin, 2010). Based on the literature above, this paper will use dimension of adaptive capability, innovation capability, management capability and strategic capability. 2.2. Digital Leadership In Digital transformation, the role of leader is a central to driving fast decision-making process and propelling the change (Kohli R. and Johnson, 2011; Liu, 2012). Digital leadership is combination of leadership style of transformation leadership and the uses of digital technology. Digital Leadership is defined as the combination of culture and competence of leader in optimizing the use of digital technology to create value to the firms (Rudito and Sinaga, 2017). It has the leadership characteristics as follow: technology leadership, digital visioning and digital execution (Rudito and Sinaga, 2017). Another study found that There are 5 characteristics: creative leader, though leader, global visionary leader, inquisitive leader and profound leader (Zhu, 2015). Since the competition become tight and hyper and complex dynamic of ecosystem due VUCA (volatility, uncertainty, complexity and ambiguity) factors, hence the leader is required to be creative and always thinking innovative through in build capability or collaboration (Sandel, 2013). The Global Visionary Leader is required to provide direction and to become an orchestra in transforming the digital business transformation. the digital technology based on internet and cloud drive the knowledge base, hence the leader has to have ability Inquisitive learning and has profound ability in knowledge and understand in depth in learning and change. In disruptive era, the role of digital leadership has impact in driving the innovation and (Wasono and Furinto, 2018). Hence based on the literature review, the dimension use for this study are creative, deep knowledge, Global vision and collaboration, thinker, inquisitive. 2.3. Market Orientation The market orientation has been studied extensively as the framework concept of the ability of firm to create value to the firm by focusing on customer, competitors, and coordination across function (Narver and Slater, 1990). The market orientation concept consists of behavior and cultural approach (Gaur et al., 2011)(. In behavior approach, market orientation is defined as activities focus on increasing customer satisfaction (Kohli A. K. and Jaworski, 1990), and in cultural approach, it defines as values and believe of the firm to put customer as first orientation (Narver and Slater, 1990). In disruption era, the market orientation, especially customer orientation is critical in sustaining the business, the use of analytical application is required to customize and personalize service to match with customers (Berman, 833 The Journal of Social Sciences Research 2012). The analytical data can provide intelligent generation of customer profile and also has intelligent dissemination based on customer profiling hence the company has ability to learn and responsive to the environment and market change (Protcko and Utz, 2014). This study uses the dimension as Intelligence generation, Intelligence dissemination, and Responsiveness align with study done by Protcko and Utz (2014) in response to disruptive era and digital transformation. 2.4. Alliance Capability The new entrants employing new disruptive models tends to represent a threat and induces incumbents to respond rapidly, through ―alliances and acquisitions‖ to speed up the process and minimize the gap with competitors. Study of the fail incumbent can be identified due to two caused: (1) Not proper resources allocation of incumbent firms, and (2) late anticipate the changing environments. Hence, incumbent firms need to form alliance capability and collaboration to match with emergence of entrants (Belk, 2013; Berman, 2012). The alliance capability can be developed through vertical and horizontal relation (Cravens et al., 2013). Vertical relation is defined as external relation with suppliers and customers relation where both or more parties form the alliance collaboration to create value. The relation type widely scopes from transactional relation up to alliance relation form the equity partnership. Horizontal relation is associated with internal and network or lateral relation. Internal relation is interrelated among business units and individuals. The lateral relation is linked to network connection among other firms to create the similar objectives. Hence according to literature review the dimension constructs of Alliance Capability consists of customer alliance, supplier alliance, internal alliance and lateral alliance. 2.5. Hypothesis Development and Research Model The relation of digital leadership and alliances capability and dynamic capability has been found in study on the non-linearity pattern of alliance capability (Khorakian and Salehi, 2015; Schweitzer, 2013). The impact of leadership to market orientation and customer was discussed in previous study as well (Petrick et al., 1999). In disruptive the relation of digital leadership to dynamic capability in Indonesia market is studied by Wasono and Furinto (2018). Based on this, the hypothesis is formulated as following: Hypothesis 1: Digital leadership has direct impact to dynamic capability, alliance capability in the Indonesian telecommunication industry. Khorakian and Salehi (2015) showed the mediation role of partnership on relationship of leadership and dynamic capability as well as the role of intervening of Market orientation (Dmour et al., 2012). According to these studies, the hypothesis is formulated as the following: Hypothesis 2: Digital Leadership has indirect impact on Dynamic capability by mediating variable of market orientation in the Indonesian telecommunication industry. Hypothesis 3: Digital Leadership has indirect impact on Dynamic capability by mediating variable of Alliance capability in the Indonesian telecommunication industry. Hence, Figure 1 below demonstrates the current research model. Figure-1. Research Model 3. Methodology This study uses a quantitative research design. The units of analysis in this study are telecommunication firms in Indonesia with the management of these firms as the observed unit. The sampling method used is purposive sampling. The questioner study has done from November 2017-January 2018. According to Hair et al. (2014) the recommended sample size is 52 respondents for the model with an endogenous construct has 2 arrows directed, 0.05 834 The Journal of Social Sciences Research significance level, 80% statistical power and minimum R2 = 0.25. The sample size is made up of 88 respondent higher than the recommended sample. The sample has 75% of as General manager and manager and the rest 25% is VP and Board leader.. 88% respondents are men and 12% are women. 83% respondents come from network provider, while 17% from service providers.. Data were collected via self-assessment through an online questionnaire and distributed through messenger, WhatsApp, Telegram and email. Since there is a limitation of data sample, the statistical a tool of analysis is SmartPLS. 4. Result 4.1. Evaluation of Measurement (Outer Model) The analysis of the outer model specifies the relationship between latent variables and their indicators. Tests performed on outer models include:  Convergent Validity. The value of convergent validity is the value of loading factor on the latent variable with its indicators. The expected value is above 0.7.  Discriminant Validity is a value of cross loading factor that is useful to assess whether the constructs have adequate discriminant by comparing the loading value on the intended construct is greater than the loading value with other constructs.  Composite Reliability. Data that has composite reliability over 0.7 considered as highly reliable.  Average Variance Extracted (AVE), expected to be more than 0.5.  Cronbach Alpha. Reliability test reinforced with Cronbach Alpha. The result is expected to have value of more than 0.6 for all constructs. Table -1. Construct Validity and Reliability Test Cronbach's Alpha rho_A Composite Reliability AVE Result Digital leadership Creative Deep Knowledge Global Vision and Collaboration Thinker Inquisitive Market Orientation Intelligent Generation Intelligent Dissemination Responsiveness Alliance Capabilities Internal Alliance Customer Alliance Supplier Alliance Lateral Alliance Dynamic Capabilities Adaptive Capabilities Innovation Capability Management Capabilities Strategic Capability 0.872 0.913 0.931 0.915 0.945 0.875 0.916 0.933 0.915 0.946 0.912 0.939 0.951 0.946 0.960 0.723 0.794 0.830 0.854 0.858 Valid Valid Valid Valid Valid 0.876 0.791 0.920 0.879 0.907 0.821 0.866 0.927 0.935 0.619 Valid 0.622 Valid 0.646 Valid 0.948 0.857 0.908 0.922 0.949 0.859 0.912 0.925 0.975 0.933 0.943 0.945 0.951 0.875 0.845 0.812 Valid Valid Valid Valid 0.917 0.817 0.915 0.851 0.918 0.826 0.922 0.865 0.948 0.892 0.940 0.900 0.858 0.734 0.797 0.694 Valid Valid Valid Valid Table 1 above shows that AVE value> 0.5, Cronbach Alpha> 0.6 and composite reliability> 0.7, which indicates that research variables have good reliability for all variables and dimensions. 835 The Journal of Social Sciences Research Dimensions Adaptive Capabilities 1 2 3 4 Table-2. Discriminant Validity 5 6 7 8 9 10 11 12 13 14 15 16 0.926 Customer Alliance 0.710 0.935 Deep Knowledge 0.581 0.784 0.891 Global Vision & Collaboration 0.537 0.729 0.878 0.911 Innovation Capability 0.765 0.732 0.684 0.607 0.857 Inquisitive 0.602 0.710 0.794 0.895 0.609 0.927 Intelligent Dissemination 0.684 0.734 0.644 0.588 0.700 0.597 0.789 Intelligent Generation 0.795 0.699 0.595 0.608 0.749 0.668 0.702 0.786 Internal Alliance 0.559 0.826 0.727 0.666 0.625 0.678 0.684 0.584 0.975 Lateral Alliance 0.696 0.763 0.697 0.614 0.694 0.671 0.689 0.661 0.721 0.901 Management Capabilities 0.779 0.808 0.801 0.729 0.789 0.754 0.747 0.746 0.749 0.709 0.893 Responsiveness 0.790 0.796 0.667 0.615 0.788 0.649 0.831 0.839 0.696 0.685 0.859 0.804 Strategic Capability 0.869 0.771 0.649 0.597 0.812 0.650 0.691 0.788 0.654 0.708 0.832 0.845 0.833 Supplier Alliance 0.590 0.759 0.799 0.728 0.660 0.725 0.627 0.581 0.779 0.770 0.696 0.665 0.637 0.919 Thinker 0.529 0.659 0.838 0.925 0.588 0.880 0.564 0.584 0.652 0.577 0.736 0.599 0.607 0.734 0.924 creative 0.808 0.797 0.729 0.665 0.811 0.661 0.697 0.739 0.624 0.734 0.815 0.782 0.774 0.691 0.628 0.850 Discriminant validity is shown in Table 2 with the diagonal bold numbers indicating the square root of AVE. This shows that all dimensions have good discriminant validity. The value of convergent validity is the value of the loading factor of outer path analysis where t-value> 1.96 and p-value < 0.05. This means that each indicator is valid Table-3. Outer Path Analysis AC1 <- Adaptive Capabilities AC2 <- Adaptive Capabilities AC3 <- Adaptive Capabilities IC1 <- Innovation Capability IC2 <- Innovation Capability IC3 <- Innovation Capability ID1 <- Intelligent Dissemination ID3 <- Intelligent Dissemination ID4 <- Intelligent Dissemination IG1 <- Intelligent Generation IG2 <- Intelligent Generation IG3 <- Intelligent Generation IG4 <- Intelligent Generation IG5 <- Intelligent Generation IG6 <- Intelligent Generation IT1 <- Inquisitive IT2 <- Inquisitive IT3 <- Inquisitive IT4 <- Inquisitive K1 <- creative K2 <- creative K3 <- creative K4 <- creative KC1 <- Customer Alliance KC2 <- Customer Alliance KI1 <- Internal Alliance KI2 <- Internal Alliance KL1 <- Lateral Alliance KL2 <- Lateral Alliance KL3 <- Lateral Alliance KL4 <- Lateral Alliance KS1 <- Supplier Alliance KS2 <- Supplier Alliance Path 0.952 0.923 0.903 0.891 0.894 0.780 0.596 0.886 0.798 0.771 0.746 0.841 0.756 0.801 0.799 0.917 0.940 0.903 0.946 0.756 0.910 0.864 0.864 0.939 0.932 0.974 0.976 0.863 0.930 0.885 0.924 0.931 0.935 Standard Deviation 0.012 0.020 0.028 0.025 0.021 0.059 0.091 0.029 0.048 0.047 0.059 0.031 0.044 0.053 0.039 0.020 0.018 0.022 0.016 0.040 0.020 0.042 0.048 0.014 0.017 0.008 0.007 0.047 0.015 0.027 0.015 0.017 0.019 T Statistics 80.626 46.717 32.289 35.495 41.862 13.134 6.553 30.424 16.716 16.303 12.713 27.157 17.117 15.103 20.310 45.761 51.452 41.634 60.111 18.843 45.009 20.365 18.022 69.270 54.643 116.969 136.270 18.350 63.043 32.732 61.064 54.462 48.761 P Values 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Result Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid 836 The Journal of Social Sciences Research KS3 <- Supplier Alliance MC1 <- Management Capabilities MC2 <- Management Capabilities MC3 <- Management Capabilities MC4 <- Management Capabilities P1 <- Thinker P2 <- Thinker P3 <- Thinker PM1 <- Deep Knowledge PM2 <- Deep Knowledge PM3 <- Deep Knowledge PM4 <- Deep Knowledge R1 <- Responsiveness R2 <- Responsiveness R3 <- Responsiveness R4 <- Responsiveness R5 <- Responsiveness R6 <- Responsiveness R7 <- Responsiveness R8 <- Responsiveness SC1 <- Strategic Capability SC2 <- Strategic Capability SC3 <- Strategic Capability SC4 <- Strategic Capability VG1 <- Global Vision and Collaboration VG2 <- Global Vision and Collaboration VG3 <- Global Vision and Collaboration VG4 <- Global Vision and Collaboration 0.892 0.919 0.862 0.881 0.909 0.916 0.930 0.927 0.844 0.901 0.913 0.905 0.768 0.873 0.698 0.899 0.870 0.777 0.831 0.687 0.879 0.902 0.771 0.771 0.925 0.921 0.879 0.918 0.034 0.018 0.033 0.031 0.020 0.018 0.015 0.019 0.036 0.025 0.018 0.023 0.051 0.038 0.073 0.024 0.034 0.063 0.049 0.092 0.022 0.024 0.050 0.062 0.021 0.019 0.052 0.017 26.090 51.247 25.971 28.236 44.517 50.219 61.855 48.787 23.407 35.344 50.121 40.131 14.970 23.187 9.519 36.787 25.578 12.394 16.838 7.442 39.681 38.221 15.270 12.355 44.591 48.985 16.749 52.758 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Table 4 shows that all constructs have a path coefficient score with t-statistics >1.96 and p-value = 0.000 <0.05, which means that all constructs have significant effects on their respective dimensions. 4.2. Structural Model (Inner Model) Based on the blindfolding score results, Q2 was obtained for alliance capabilities = 0.461 ,market orientation = 0.285, and dynamic capability = 0.510. If Q2 >0, it indicates that the structural model has adequate predictive relevance. Hence, the model is robust and hypothesis testing can be done. The complete finding can be shown in Figure 2. Figure-2. Complete Path Diagram of Research Model 837 The Journal of Social Sciences Research 4.3. Hypothesis Testing The hypothesis testing can be accomplished through partial Test and simultaneous test to know the impact of respective Variable and dimension. The result of hypothesis testing can be shown in Table 4. Table -4. Testing of Hypothesis Partial Test Digital leadership -> Alliance Capabilities Digital leadership -> Dynamic Capabilities Digital leadership -> Market Orientation Alliance Capabilities -> Dynamic Capabilities Market Orientation -> Dynamic Capabilities Path 0.839 0.189 0.754 0.153 0.639 Standard Deviation 0.034 0.090 0.044 0.092 0.073 T Statistics 24.752 2.099 17.147 1.655 8.718 P Values 0.000 0.036 0.000 0.098 0.000 Result Supported Supported Supported Not Supported Supported * significant at =0.05 (T statistics > 1.96) Simultaneous Test Path Digital leadership -> Alliance 0.128 Capabilities -> Dynamic Capabilities Digital leadership -> Market 0.482 Orientation -> Dynamic Capabilities Standard Deviation T Statistics P Values Result 0.078 1.649 0.099 Not Supported 0.061 7.946 0.000 Supported * significant at =0.05 (T statistics > 1.96) Table 4 shows that within the degree of confidence of 95% (=0.05), where T>1.96 and p<0.05, there is supportive influence of digital leadership on alliance capability, digital leadership on dynamic capability, digital leadership on market orientation and market orientation on dynamic capability, whereas alliance capability has no direct effect on dynamic capability. On simultaneous test, it shown that digital leadership indirect impact on dynamic capability mediated by market orientation and not indirect effect on dynamic capability if intervened by alliances capability The direct effect test shows that the relationship between digital leadership and dynamic capability has a path coefficient score of 0.189 with t-statistics = 2.099 and p-value = 0.036<0.05. This means that H0 is rejected and H1 is accepted. This proves that digital leadership has a significant impact on dynamic capability. The second assessment is the relationship between digital leadership and alliance capability has a path coefficient score of 0.839 with t-statistics = 24.752 and p-value = 0.000. This means that H0 is rejected and H1 is accepted. This proves that digital leadership has a significant impact on alliance capability. The assessment on relationship digital leadership on market orientation has shown has a path coefficient score of 0.754 with t-statistics = 17.147 and p-value = 0.000. This means that H0 is rejected and H1 is accepted. This proves that digital leadership has a significant impact on market orientation. While the relation between alliance capability with dynamic capability has a path coefficient score of 0.153 with t-statistics = 1.655 and p-value = 0.098>0.05. This means that H0 is accepted while H2 is rejected. There is also no significant impact of alliance capability on dynamic capability. Lastly, the relationship between market orientation and dynamic capability has a path coefficient score of 0.639 with t-statistics = 8.718 and p-value = 0.000. This means that H0 is rejected and H1 is accepted. This also proves that market orientation has a supportive impact on dynamic capability. The indirect effect test shows that the mediating role of market orientation has a path coefficient score=0,482 with t-statistics = 7.946 and p-value = 0.000. This means that H0 is rejected and H1 is accepted. This proves that market orientation has supportive impact as mediating role on relationship between dynamic capability and digital leadership. While, the mediating role of alliance capability has a path coefficient score of 0.128 with t-statistics = 1.649 and p-value = 0.099>0.05. This means that H0 is accepted while H2 is rejected. There is also no significant impact of alliance capability in mediating role on relationship between dynamic capability and alliance capability. 5. Discussion and Implication The results are aligned with the study on disruption technology and innovation conducted by Christensen (1997), Markides (2006), and Khorakian and Salehi (2015) where the incumbent firm should adapt the changing of customer and market to sustain and driving digital transformation. digital leadership has a direct and indirect to dynamic capability mediated by market orientation. Global vision and collaboration bring significant value to digital leadership followed by inquisitive, deep knowledge and thinker. This finding supports Rudito and Sinaga (2017) and Wasono and Furinto (2018), who found that digital leadership supporting innovation capability in disruptive era. This finding brings the implication for incumbent firms to use digital leadership to establish dynamic capability through direct and indirect mediated by market orientation. While, the mediating role of alliance capability is not impact on relationship between dynamic capability and digital leadership. Market orientation is formulated by dominant responsiveness followed by intelligent generation and intelligent dissemination capability. These findings indicate that in term of market orientation, the culture and behaviour of the management and firms that adaptive to the change and responsive to the market create the value to customer and 838 The Journal of Social Sciences Research firms themselves. This finding align with the study before done by, Protcko and Utz (2014) and Narver and Slater (1990). The dynamic capability is dominant influenced by strategic capability, followed by management capability, adaptive capability and innovation capability. It means that the long-term view of management and firm in anticipating the market dynamic is important for incumbent firms. This is indicating that the long-term view through transformation is taken priority for incumbent firm in facing disruptive era. The alliances capability as mediating role was not supporting in relationship of dynamic capability and digital leadership. This finding shown the important in development of internal capability rather than the alliance strategy. Based on resources-based view that provide the distinctive organization capability is important through providing internal resources that valuable, rare, imperfectly imitable, and on-substitutable capabilities (Barney, 1991). Incumbent firms are required to develop the core competence to compete with new entrance in disruptive era. 6. Implication The findings reveal the antecedents of digital transformation. According to the result finding, We configure the model of digital transformation for Indonesia incumbent firms base on a framework study conducted by Mader (2012) as shown in figure 3. Figure-3. Digital Transformation Model based on Mader’s Framework (2012) (source: maider and internal analysis) Di sti nc tiv Ca e O pa rg or bi an ma lit iz tio y at Kn n io Ca ow n pa led b ge ili ty Ca pa bil ity Inn Dig ov ital at ion tati on a b il ity Cu s Exp tome erie r n ce Find Digital Experience network Rep u ans - I al tr Digit inary BM pl disci a ry iplin l e -disc Inter ess Mod Busin vation s In no sines ry Bu n plina vatio Disci I nn o l el Mode Mod ness Busi ovation Inn Digital Transformation Inf Dig Adv ital oca cy l na tio ip c h sa l a n ers na Tr ead tio L a rm hip sf o r s a n ea d e r T L l ita ip Dig ersh ad Le Innovating Experience Quality of Interaction Co-creation Strategy Digital transformation is started from digital leadership and vision to bring the digital transformation for all activities and process. This digital leadership will drive the distinctive organization capability since it has 2 face which are digital innovation and effective cost reduction. The market orientation could drive customer experience since with distinctive capabilities it could create personalize to customer. After getting the customer experience the customer is the major partner in building product and service together called by co-creation. Crowdsourcing with customer could provide long-term and long tail partnership. By the end of the day the culture innovation in creating business model will become the new paradigm of incumbent firms in facing digital transformation. 7. Conclusion, Limitation and Further Study 7.1. Conclusion Based on the results of hypotheses testing, it can be concluded that digital leadership has direct and indirect impact to dynamic capability, where the market orientation has a mediating role on relationship between dynamic capability and digital leadership. The alliance capability was not a mediating role in the relationship of dynamic capability and digital leadership. 839 The Journal of Social Sciences Research 7.2. 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