Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5, 1923-1939 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i5.1924 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: 1272100059@suret.untag-sby.ac.id Ambidextrous leadership, customer orientation, environmental innovation to improve service innovation capability through digital capabilities and technological capabilities as mediating variables in Umkm in Berau District, East Kalimantan Hasnawati1*, Amiartuti Kusumaningtyas2, Ida Bagus Cempena3 1,2,3Faculty of Economics and Business, 17 August 1945 University of Surabaya, Indonesia; 1272100059@suret.untag-sby.ac.id (H.) amiartuti.k@untag-sby.ac.id (A.K.) ib_cempena@untag-sby.ac.id (I.B.C.). Abstract: Berau District is in the northern part of East Kalimantan Province and borders directly with North Kalimantan Province. As of 2014, the administrative territory of Berau District was divided into 13 districts with a total of 100 villages and 10 villages. Micro, Small and Medium Enterprises (MSMEs) are economic drivers in Berau district that are still faced with classical problems such as infrastructure, licensing, marketing, distribution and financing as well as post- 19 recovery processes. In connection with the problem, to build micro, small enterprises, and corporations, it is necessary to support the healthy real sector to combat poverty through the strengthening of the purchasing power of better society and the help of financing with light interest. The purpose of this research. Based on the background and the formula of the problems that have been outlined earlier, then the purpose of this research is to develop a model of the conceptual framework by means of proof and analysis; (1). The impact of ambidextrous leadership on digital capabilities on MSME perpetrators in Berau district (2), the impact of customer orientation on digital capacity on MSE perpetrator in Beru district (3), the effect of environmental innovation on digital Capabilities in MSE Perpetrator in Berau district (4). The effect of digital capability on technological capacities in the UMKM Perpetrant in Berea district (5), the influence of digital capacities on service innovation capability in UMM Perpetrator at Beraus district (6). The total sample that meets the criteria in this study is 353 samples and is processed using SmartPLS data processing. The results of this study indicate that there is a direct relationship between the impact of Ambidextrous Leadership, Customer Orientation, Environmental Innovation on Service Innovation Capability. Keywords: Berau, Dynamy capability, Technology, UMKM. 1. Background For an organization, creativity and innovation are vital needs, because creativity is the backbone for organizational survival. Creativity is the ability to develop new ideas and new ways of looking at problems into opportunities, while innovation is the ability to apply creative solutions to problems and opportunities for the growth of a business (Zimmerer and Scarborough, 2019). In order to create a creative organization, it is necessary for the organization to be able to make rapid environmental changes, both in technology and product standards. Given that in the current era technology plays a very important role, it requires the ability of organizations to provide innovative services by utilizing technology. The utilization of technology has now been used in various circles, one of which is small-scale business actors. Almost all sectors now utilize technology for progress. The more sophisticated the technology used by, the easier and 1924 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate faster the activities carried out. The need for time and cost efficiency causes entrepreneurs to feel the need to apply technology in their company. In addition, in this era of globalization, almost all business entities are required to make changes to increase their competitiveness. This can be realized if there is ambidextrous leadership, namely a leader who is still able to develop existing businesses, as well as being able to create new profitable businesses. In addition, it is necessary to form a customer-oriented mindset, and try to create an atmosphere of environmental innovation. These factors will further encourage organizations to implement/use digital capability. The use of digitized information will further encourage organizations to utilize technology for automation. This certainly aims to facilitate work that was previously done manually. In the long run, the organization will be able to provide innovative services for customers. The conceptual framework model as described, will then be tested on Micro, Small and Medium Enterprises (MSMEs) in Berau Regency, East Kalimantan. Berau Regency is one of the autonomous regions in East Kalimantan Province, has considerable potential in the tourism industry, this can be seen from the many tourist attractions in Berau Regency. The type of tourism that is in great demand by people is nature tourism. Improving the quality of human resources, one of which can be done by opening up the widest possible employment opportunities for the community. Table 1. Micro, small and medium enterprises in berau regency. District 2019 2020 2021 Tanjung Redeb 806 884 4.592 Sambaliung 42 602 2.419 Gunung Tabur 117 104 988 Teluk Bayur 63 346 1.321 Kelay 10 33 55 Segah 24 52 131 Derawan Island 76 147 779 Maratua 22 200 340 Tabalar 23 79 502 Biatan 51 32 51 Talisayan 45 386 673 Batu Butih 39 300 351 Biduk-Biduk 54 69 836 KTP outside Berau - - 59 Total 1.372 3.234 13.097 Source: Dinas Koperidag Berau, 2023 Based on the data obtained related to MSMEs in Berau Regency, the general problem faced by MSMEs in Berau Regency is that MSMEs grow rapidly but are less able to compete in utilizing technology. On the other hand, the ability to carry out management and problems at the institutional level. According to Tambunan (2018), MSME actors tend to face problems such as lack of capital, lack of raw materials, unavailability of markets and lack of qualified human resources, which has implications for income and financial performance. In fact, a study by Mshenga et al. (2013) found that MSME leadership behavior plays a role in technological capabilities. This indicates that efforts are needed to overcome the problems faced by business actors dominated by MSMEs in order to improve the leadership behavior and income of business actors. For this reason, it is necessary to understand the factors that influence leadership behavior in MSME business actors in Berau Regency. Based on the above background, the research problem can be formulated as follows: 1. Does ambidextrous leadership have a significant effect on digital capability in MSME players in 1925 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate Berau Regency? 2. Does customer orientation have a significant effect on digital capability in MSME players in Berau Regency? 3. Does environmental innovation have a significant effect on digital capability in MSME players in Berau Regency? 4. Does digital capability have a significant effect on technological capabilities in MSME players in Berau Regency? 5. Does digital capability have a significant effect on service innovation capability in MSME players in Berau Regency? 6. Do technological capabilities have a significant effect on service innovation capability in MSME players in Berau Regency? 2. Overview 2.1. Dynamic Capabilities The dynamic capabilities theory was first developed by Teece and Pisano (1994), according to them dynamic capabilities are related to the organization's ability to create, reshape, assimilate knowledge and skills in order to remain standing strong in a rapidly changing competitive environment. 2.2. Ambidextrous Leadership Ambidextrous leadership is defined as the ability to encourage explorative and exploitative behaviors by increasing or decreasing variance in their behaviors and the flexibility of switching between them. Ambidextrous leadership style, which has both opening and closing leadership behaviors, is considered more effective in innovation (Alghamdi, 2018; Ketkar & Puri, 2017; Tian et al., 2020). 2.3. Customer Orientation In achieving superior performance, an organization must create sustainable superior value for its customers. The desire to create superior value for customers drives businesses to create and maintain market orientation (Narver and Slater, 1990). As mentioned by Slater and Narver (1994:22), an organization is market oriented when "its culture is systematically and fully committed to continuously creating superior customer value". 2.4. Environmental Innovation Following a (natural) RBV perspective, it is claimed that SMEs that adopt an environmental orientation are more likely to acquire valuable, rare, inimitable and irreplaceable new resources (Hart, 1995; Sinha & Akoorie, 2010; Hart & Dowell, 2010) and, in turn, are in a better position to generate product and process innovations. This is especially true if companies, and SMEs more specifically, target the development of environmental innovations or 'eco-innovations'. 2.5. Digital Capabilities Digital "capabilities" means the abilities or skills required to perform a specific task (Day, 1994; Drucker, 1985; Li & Calantone, 1998) or, in other terms, "the collection of abilities and expertise needed to achieve a target." Digital capabilities can be thought of as skills needed to go beyond pure IT to include specific technologies, such as social media or mobile, as analytical skills to drive value from big data, and we can also conceptualize them as digital outcomes or operations. 2.6. Technological Capabilites Changes in product and process technology are closely related to competition, which is concerned with the adoption of an innovation that is sustained by the firm in the production, distribution and 1926 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate sale of new products or services (Zander & Kogut, 1995). Organizational capabilities can provide firms with the ability to adopt industry innovations, and in this case these capabilities are defined as technological capabilities. 2.7. Service Innovation Capability Service innovation capability is defined as the ability to apply useful knowledge from multiple resources to creative new services, processes, and systems (Atuahene-Gima 2005; Boer et al. 2000; Hurley and Hult 1998; Yang et al. 2009). Examining the underlying mechanisms for cultivating service innovation capabilities is critical to enhancing hotels' competitive advantage. With proportions based on theoretical and empirical studies, it will explain how many hypotheses and how the influence between the variables. After identifying the variables and how the influence between the variables, the next step is to describe the conceptual framework. The conceptual framework can be seen in Figure 1, as follows: Figure 1. Conceptual framework research. 2.8. The Influence of Ambidextrous Leadership on Digital Capabilities Ambidextrous leadership refers to a leader's ability to manage day-to-day operations (exploitation) and develop new innovations (exploration) simultaneously. Benner and Tushman (2015) point out that the logic of innovation activities has fundamentally changed due to the dramatic decrease in communication and information processing costs triggered by digitization and the internet. Thus, the question arises as to whether and how ambidextrous learning affects organizational performance in Digital Capabilities. Thus, entrepreneurial leadership may be an antecedent of ambidextrous learning in digital transformation, yet its important role does not seem to have attracted attention. Therefore, Ambidextrous Leadership is considered to improve Digital Capabilities. Thus the following hypothesis is proposed: H1: Ambidextrous Leadership has a significant effect on Digital Capabilities. 2.9. The Effect of Customer Orientation on Digital Capabilities Previous research has shown that market orientation has a positive and significant impact on firm performance, and market-oriented firms contribute to the firm's success in strategy development (Atuahene-Gima, 1996). Scholars regard Customer Orientation as the most decisive factor in market- oriented strategy, and it is regarded as a set of beliefs that give the highest priority to the interests of 1927 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate customers (Deshpandé, 1993). Therefore, Customer Orientation is considered to play an important role in building Digital Capabilities. Thus the following hypothesis is proposed: H2: Customer Orientation has a significant effect on Digital Capabilities. 2.10. The Effect of Environmental Innovation on Digital Capabilities Digital "capabilities" means the abilities or skills required to perform a specific task (Day, 1994; Drucker, 1985; Li & Calantone, 1998) or, in other terms, "the collection of abilities and expertise needed to achieve a target." Digital Capabilities can be thought of as the skills required to go beyond pure IT to include specific technologies, such as social media or mobile, as analytical skills to drive value from big data, and we can also conceptualize them as digital outcomes or operations. Environmental Innovation helps companies to recruit, motivate, and retain human resources with Environmental Innovation. In addition, Ardito et al. (2021) found a relationship between Environmental Innovation and Digital Capabilities. Thus the following hypothesis is proposed: H3: Environmental Innovation has a significant effect on Digital Capabilities. 2.11. The Effect of Digital Capabilities on Technological Capabilites Technological Capabilites have enabled organizations to create opportunities to support their competitive advantage. In this case, understanding the dynamics that affect the adoption of digital technologies becomes critical to their success El-Haddadeh (2020). examines the specific aspects of digitalization that affect technology adoption in organizations Karimi and Walter (2015). analyzes the impact of dynamic capabilities on digital disruption in firm performance. Digital disruption reduces intermediation costs (Sutherland, 2018) and combines technologies more efficiently (Karimi & Walter, 2015). Digital Capabilities in this sense are then considered to influence Technological Capabilites. Thus the following hypothesis is proposed: H4: Digital Capabilities has a significant effect on Technological Capabilites.\ 2.12. The Effect of Digital Capabilities on Service Innovation Capability Kohli and Grover (2008) define Digital Capabilities as the internal ability to provide customer information when needed. According to Lyytinen, Yoo and Boland (2016), Digital Capabilities are digital systems that produce new results and structures without the participation of uncoordinated third-party actors and without deliberate planning by system creators. Service Innovation Capability is defined as the ability to apply useful knowledge from various resources to creative new services, processes and systems (Atuahene-Gima 2005; Boer et al. 2000; Hurley and Hult 1998; Yang et al. 2009). Good Digital Capabilities will increase Service Innovation Capability. Thus the following hypothesis is proposed H5: Digital Capabilities have a significant effect on Service Innovation Capability. 2.13. Effect of Technological Capabilites on Service Innovation Capability Technological capability refers to a firm's ability to develop new products and services by aligning its strategy with innovative processes (Wang, 2007). Such capabilities involve knowledge and skills in acquiring, using, absorbing, adapting, improving, and generating new technologies (Bell & Pavitt, 1995 Malhotra, Mathur, Diddi & Sagar, 2021;). These capabilities enable the development of new products and technologies, improve manufacturing processes and quality control skills, and predict technological changes in the industry (DeSarbo, 2005). Whereas Service Innovation Capability is defined as the ability to apply useful knowledge from various resources to creative new services, processes, and systems (Atuahene-Gima 2005; Boer et al. 2000; Hurley and Hult 1998; Yang et al. 2009). Good Technological Capabilites can improve Service Innovation Capability. Thus, the following hypothesis is proposed: H6: Technological Capabilites has a significant effect on Service Innovation Capability. 1928 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate 3. Research Methods Based on the background and problem formulation, the research design used is Causal Explanatory Research, which is research used to show the position of the variables studied and the influence between one variable and another. (Sugiyono, 2019). This Causal Explanatory Research research is used to test the independent variables of ambidextrous leadership, customer orientation, environmental innovation on digital capabilities, and their consequences on technological capabilites and service innovation capabilities. The sampling method in this study used purposive sampling method. The number of MSMEs that use technology in this study is 3,000 businesses. The population contained in this study is 3,000 MSME actors divided into 13 sub-districts in Berau Regency, East Kalimantan Province, Indonesia. Based on the above calculations, the number of samples determined is 353 MSME business actors who use technology in running a business. The number of respondents is considered representative to obtain writing data that reflects the state of the population. Samples were taken based on probability sampling techniques; simple random sampling, where researchers provide equal opportunities for each MSME actor in the population to be selected as a sample which is done randomly by taking into account the 13 sub-districts in Berau Regency in the population itself. Structural equation modeling (SEM) is a combination of multvariate techniques that analyze the relationship simultaneously between dependent and independent variables and provide complete information about the relationship between constructs and their indicators, and provide complete information about the relationship between constructs that have been hypothesized simultaneously. In general, there are two types of SEM that have been widely recognized, namely covariance-based structural equation modeling (CB-SEM) developed by Joreskorg (1969) and partial least squares path modeling (PLS-SEM) or often called variance or component-based structural equation modeling developed by World (1974) (Bookstein, 1982). 4. Research Results 4.1. Descriptive Statistics Descriptive statistical analysis provides an overview or description of data seen from the average value (mean), median, standard deviation, maximum, minimum (Ghozali, 2014). Descriptive analysis is useful for understanding, describing, explaining data or events collected in a study and not up to generalization. Category Classification of Mean Score: 1 - < 1,8 : Very low 3.4 - < 4.2 : High 1,8 - < 2,6 : Low 4,2 - < 5,0 : Very high 2,6 - < 3,4 : Medium Table 2. Descriptive statistics. Variable N Min. Mix. Mean Std. deviation Ambidextrous leadership 353 8 39 18.54 6.020 Customer orientation 353 6 28 15.54 4.875 Environmental innovation 353 4 20 10.03 3.695 Digital capabilities 353 5 23 11.18 3.471 Technological capabilities 353 4 16 8.80 2.889 Service innovation capability 353 4 19 8.79 3.205 Valid N (listwise) 353 The descriptive test results in Table 2 show the minimum (4), maximum (39), and average (18.54) Ambidextrous Leadership values of 353 data, and have a standard deviation of 6.020. The Customer Orientation variable has a minimum value (6), maximum (28), average (15.54), and standard deviation 1929 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate (4.875) with a total of 353 data. The Environmental Innovation variable has 353 data with a minimum value (4), maximum (20), average (10.03), and standard deviation (3,695). The Digital Capabilities variable has a total of 353 data with a minimum value (5), maximum (23), average (11.18), and standard deviation (3.471). Technological Capabilities variable has a total of 353 data with a minimum value (4), maximum (16), average (8.80), and standard deviation (2.889). Furthermore, the Service Innovation Capability variable has a total of 353 data with a minimum value (4), maximum (19), average (8.79), and standard deviation (3.205). 4.2. Evaluation of the Measurement Model (Outer Model) To assess the Fit Model of a research model, the analysis technique using the PLS- based SEM method requires 2 stages, namely by assessing the outer model and inner model. Figure 2. Display of PLS algorithm calculation results. 4.3. Validity Test There are two tests in using data analysis techniques in SmartPLS 3.0 to assess the outer model, namely convergent validity and discriminant validity. 4.4. Convergent Validity A high loading factor value indicates that each construct indicator converges at one point. The rule of thumb commonly used to assess convergent validity is that the loading factor value must be more than 0.7 for confirmatory research and the loading factor value between 0.6-0.7 for explanatory research is still acceptable. The following is a table of 3 loding factor values of all statements in the questionnaire (Haryono, 2017). 1930 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate Table 3. Outer loading. Variables AL CO EI SIC DC TC AL1 0.793 AL2 0.774 AL3 0.827 AL4 0.770 AL5 0.822 AL6 0.867 AL7 0.878 AL8 0.782 CO1 0.909 CO2 0.907 CO3 0.907 CO4 0.944 CO5 0.907 CO6 0.892 DC1 0.881 DC2 0.894 DC3 0.851 DC4 0.843 DC5 0.806 EI1 0.945 EI2 0.945 EI3 0.942 EI4 0.931 SIC1 0.918 SIC2 0.912 SIC3 0.914 SIC4 0.909 TC1 0.912 TC2 0.925 TC3 0.806 TC4 0.842 Based on table 3 above, the results show that the overall loading factor value from G to U can be said to be valid because the loading factor value is above 0.5, which means that construct validity has been met. This makes it clear that the statements on the questionnaire instrument have been able and accurate in measuring the research variables. 4.5. Discriminant Validity Evaluation of discriminant validity aims to determine whether the construct has adequate discriminant. The evaluation is carried out by comparing the discriminant validity and AVE values. If a construct has a discriminant validity value greater than AVE, it can be declared a valid construct. The recommended AVE value is greater than 0.5 (Haryono, 2017). The following is table 4 of the results of the comparison of discriminant validity with AVE. 1931 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate Table 4. Comparison of discriminant validity and AVE values. Variables AL CO EI SIC DC TC AVE AL 0.665 CO 0.767 0.830 EI 0.740 0.895 0.885 SIC 0.760 0.782 0.771 0.834 DC 0.764 0.813 0.869 0.740 0.732 TC 0.836 0.812 0.857 0.817 0.836 0.761 Table 4 states that the discriminant validity value of each construct has a value greater than AVE, so it can be concluded that each construct used is valid and in accordance with the indicators that researchers use in research. 4.5. Cross Loading Discriminant validity is also carried out based on cross loading measurements with constructs. If the construct correlation on each indicator is greater than other constructs, it means that the latent construct can predict indicators better than other constructs. Table 5. Discriminant validity column cross loadings. Variables AL CO EI SIC DC TC AL1 0.793 0.591 0.595 0.621 0.596 0.646 AL2 0.774 0.568 0.502 0.559 0.504 0.561 AL3 0.827 0.581 0.611 0.555 0.633 0.619 AL4 0.770 0.523 0.449 0.485 0.463 0.533 AL5 0.822 0.575 0.561 0.559 0.585 0.628 AL6 0.867 0.614 0.606 0.626 0.599 0.666 AL7 0.878 0.636 0.604 0.617 0.604 0.673 AL8 0.782 0.633 0.617 0.587 0.601 0.656 CO1 0.684 0.909 0.825 0.696 0.720 0.714 CO2 0.654 0.907 0.791 0.676 0.713 0.642 CO3 0.674 0.907 0.760 0.677 0.695 0.732 CO4 0.681 0.944 0.787 0.694 0.723 0.693 CO5 0.656 0.907 0.761 0.646 0.670 0.687 CO6 0.616 0.892 0.763 0.657 0.644 0.669 DC1 0.688 0.688 0.712 0.616 0.881 0.712 DC2 0.647 0.724 0.747 0.578 0.894 0.673 DC3 0.592 0.703 0.755 0.608 0.851 0.631 DC4 0.562 0.585 0.640 0.569 0.843 0.595 DC5 0.528 0.549 0.613 0.549 0.806 0.627 EI1 0.693 0.791 0.945 0.699 0.779 0.768 EI2 0.645 0.784 0.945 0.637 0.742 0.720 EI3 0.660 0.828 0.942 0.703 0.780 0.770 EI4 0.643 0.824 0.931 0.705 0.757 0.738 SIC1 0.643 0.677 0.676 0.918 0.648 0.705 SIC2 0.652 0.687 0.682 0.912 0.617 0.701 SIC3 0.624 0.661 0.640 0.914 0.594 0.650 1932 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate SIC4 0.671 0.680 0.665 0.909 0.634 0.683 TC1 0.720 0.728 0.748 0.722 0.694 0.912 TC2 0.714 0.707 0.736 0.659 0.704 0.925 TC3 0.571 0.529 0.578 0.568 0.555 0.806 TC4 0.659 0.656 0.702 0.658 0.680 0.842 Based on Table 5 above, it shows that each question indicator has the highest loading factor value on each intended latent construct than other latent constructs, meaning that each question indicator is able to be predicted well by each latent construct in other words, discriminant validity is valid. 4.6. Instrument Reliability Test 4.6.1. Composite Reliability Composite reliability is to determine whether the construct has high reliability or not. The composite reliability value is above 0.7, so it can be said that the construct is reliable. Table 6. Composite reliability. Variables Composite reliability (rho_a) Composite reliability (rho_c) AVE AL 0.931 0.941 0.665 CO 0.960 0.967 0.830 EI 0.957 0.969 0.885 SIC 0.935 0.953 0.834 DC 0.911 0.932 0.732 TC 0.902 0.927 0.761 In Table 6 above, it is known that the composite reliability and AVE values are reliable or trustworthy because the values are more than 0.8, 0.7, and 0.6. So it can be concluded that all constructs meet the criteria for reliability and validity in accordance with the specified criteria so that they can be used to continue the research. Table 7. Cronbachs alpha. Variables Cronbach's alpha AL 0.928 CO 0.959 EI 0.957 SIC 0.934 DC 0.908 TC 0.895 4.7. Cronbachs Alpha Table 7 above shows that the AL (0.928), CO (0.959), EI (0.957), SIC (0.934), DC (0.908), and TC (0.895) constructs are greater than 0.6, so Cronbachs Alpha has been met. A valid Cronbachs Alpha value will strengthen and support the composite reliability value, which means that there is no reliability/undimensionality problem in the model. so in other words, the construct is reliable. 4.8. Structural Model (Inner Model) 4.8.1. R-Square Test To assess the model with SmartPLS 3.0 starts by looking at the R-Square (R2) for each dependent 1933 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate latent variable. The results of the R-Square (R2) estimation using SmartPLS 3.0 are presented in Table 8. Table 8. R square. R-square Adjusted R-square SIC 0.780 0.777 DC 0.702 0.700 TC 0.736 0.734 From the results of Table 8 obtained above, it shows that the exogenous constructs of Ambidextrous Leadership, Customer Orientation, Environmental Innovation can explain the diversity of endogenous constructs of Service Innovation Capability in improving service capabilities to MSMEs by 0.780 or 78.0% and in improving digital capabilities by 0.702 or 70.2%. Meanwhile, in increasing technological capabilities by 0.736 or 73.6%. Sipayung (2021) states that the R-square value of 0.67 is declared strong, 0.33 is declared moderate and 0.19 is declared weak. So it can be concluded that the results obtained from the R-square value of SIC (Service Innovation Capability) of 0.780 and DC (Digital Capabilities) of 0.702 and TC (Technological Capabilites) of 0.736 can be declared moderate. 4.9. Predictive Relevence (Q )2 The second step for testing the inner model is done by looking at the Predictive Relevence value (Q 2) To calculate Q 2, the formula can be used: Q2 = 1 - (1-R21 ) (1- R22 ) (1- R )2 Q2 = 1 - (1-0.780) (1- 0.702) (1-0.736) Q2 = 0.982 The results above show results greater than 0 (>0), so it can be concluded that this study has good observation values generated by the model and also its parameter estimates. 4.10. Goodness of Fit (GoF) The last inner model testing step is to determine the Goodness of Fit (GoF) value. Unlike CBSEM, the GoF value in PLS-SEM must be calculated manually. There are several research classifications in assessing GoF, small GoF value = 0.1, medium GoF = 0.25 and large GoF = 0.38. The formula for determining the GoF value is: 𝐺𝑜𝐹 = √𝐴𝑉𝐸 𝑥 𝑅2 Then the GoF value can be calculated as : 𝐺𝑜𝐹 = √0,665 𝑥 0,780 GoF = 0.636 From the above calculations, it can be concluded that the data to be processed meets the assumptions of the structural equation model. 4.11. Hypothesis Testing Hypothesis testing to see the significance of a variable relationship is through the t-statistic value on the Path Coefficients. The results of the Path Coefficients test are presented in table 9 below: 1934 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate Table 9. Path coefficients. Original sample (O) Sample mean (M) Standard deviation (STDEV) T-statistics P-values AL -> DC 0.237 0.241 0.062 3.824 0.000 CO -> DC 0.139 0.132 0.084 1.662 0.048 EI -> DC 0.527 0.531 0.092 5.736 0.000 DC -> SIC 0.269 0.268 0.054 4.940 0.000 DC -> TC 0.758 0.759 0.033 23.072 0.000 TC -> SIC 0.546 0.547 0.053 10.303 0.000 4.12. The Effect of Ambidextrous Leadership on Digital Capabilities The results of hypothesis 1 (one) show that ambidextrous leadership has a positive effect on digital capabilities. This is consistent with the research of Mueller, Renzl, & Will (2020) who found that there is a positive relationship between ambidextrous leadership and digital capabilities in increasing the ability to encourage exploratory and exploitative behaviors for an employee in team members Leaders encourage and stimulate the creativity of the work team while ensuring that the business is run efficiently. This research is also similar to the research of Rosing, Frese, & Bausch (2011). This is in line with the theory of dynamic capabilities related to the ability of organizational leaders to create, reshape, assimilate knowledge and skills to remain standing strong in a rapidly changing competitive environment. This result is in accordance with the research of Darjat Sudrajat (2013) and Chien S. Y and Tsai C. H (2012) which found that ambidextrous leadership is considered to increase digital capabilities. The results of this study are in accordance with previous research conducted by Kaehler et al. (2014), Biedenbach and Müller (2012) and Wang and Ahmed (2007) which state that there is a significant positive effect of ambidextrous leadership on digital capabilities. So, it can be concluded that digital capabilities are important for umkm to improve digital capabilities. 4.13. The Effect of Customer Orientation on Digital Capabilities The results of hypothesis 2 (two) show that customer orientation has a positive effect on digital capabilities. The findings of this study reveal how important it is for MSMEs to have customer capabilities. Looking back, several studies show that customer capabilities have a significant effect on the performance of micro, small and medium enterprises (MSMEs) (Avlonitis, G.J. and Giannopoulos, A.A, 2012; Cavazos-Arroyo & Puente-Diaz, 2019; Phiri, 2020; Santos Vijande et al., 2012). A study conducted in Jordan found that customer capabilities have a significant effect on technological capabilities among MSMEs (Alshamayleh et al., 2013). Some researchers argue that this orientation is limited by the current level of customers only to incremental improvements that cannot create radical innovations (Im & Workman, 2014). However, many researchers see a positive relationship between customer orientation and successful innovation in digital capabilities (Grinstein, 2008). Therefore, customer orientation is considered to play an important role in building digital capabilities. 4.14. The Effect of Environmental Innovation on Digital Capabilities The results of hypothesis 3 (three) show that environmental innovation has a positive effect on digital capabilities, this shows that this study supports previous research conducted by Septiana Novita Dewi, Aris Tri Haryanto (2016) and Benner, M.J. and Tushman, M.L (2013) which found a relationship between environmental innovation and digital capabilities. Furthermore, according to legitimacy theory, companies implement environmentally friendly innovations to get positive value from society or consumers. The public accepts the company as a company that cares 1935 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate about the environment while carrying out its business activities for profit (Agustia et al., 2019; Mardiana & Wuryani, 2019; D. Zhang et al., 2019; F. Zhang et al., 2020), but that contradicts the findings of research conducted (Husnaini & Tjahjadi, 2021; Mariyamah & Handayani, 2019; Utomo, 2016). The results of this study are in accordance with previous research conducted by Wang and Ahmed (2007), Woiceshyn and Daellenbach (2005) and Zahra and George (2002) which state that there is a significant positive effect of Environmental Innovation on Digital Capabilities. So, it can be concluded that Environmental Innovation is important for MSMEs to improve Digital Capabilities. 4.15. The Effect of Digital Capabilities on Technological Capabilites The results of hypothesis 4 (four) show that digital capabilities have a positive effect on technological capabilities. This study confirms research (Alyahya, 2021; Bader et al., 2022; Nuseir & Refae, 2022; Purwanti et al., 2022), digital capabilities have a significant effect on technological capabilities. One study found that digital capabilities have a significant impact on improving business performance (Gunawan & Sulaeman, 2020). Another study found that the impact of digital marketing capability strategies has consequences on profit margins and the ability of businesses to grow (Phiri, 2020). Consistent with Yoo, Boland, Lyytinen and Majchrzak (2012), multiple products or subsystems can be designed and controlled using the same digital tools. Researches found that there is a strong influence of Digital Capabilities on Technological Capabilites of MSMEs (A. Owoseni & Twinomurinzi, 2018), and in other contexts, technological capabilities were also found to have an effect on increasing the ability to innovate an MSME and company (C. H. Chen & Cates, 2018; Masyhuri et al., 2021). It was also found that integrating technology in a business line can hoist innovative capabilities in an effort to improve performance (Raymond et al., 2013). Finally, responding to the dominance of social media in marketing, Borah, Iqbal, & Akhtar (2022) found that the use of social media as another form of mobile application can improve MSME performance through the encouragement of innovative capabilities. Digital capabilities in this sense are then considered to influence technological capabilities. 4.16. The Effect of Digital Capabilities on Service Innovation Capability The results of hypothesis 5 (five) show that digital capabilities have a positive effect on service innovation capability. This strengthens the findings of research conducted by Wardaya et al., (2019) found that digital capabilities have a mediating effect on the relationship between service innovation capabilities and marketing performance, with innovation as a mediator (Wardaya et al., 2019). Another study examined the impact of digital service innovation on improving MSME businesses and found that digital capabilities mediate the relationship between digital service innovation and firm performance (Jung & Shegai, 2023). The results of this study are in accordance with previous research conducted by Saunila (2014), Wang and Ahmed (2007) and Zhang (2004) which state that there is a significant positive effect of Digital Capabilities on Service Innovation Capability. So, it can be concluded that Digital Capabilities are important for companies to improve Service Innovation Capability. 4.17. Effect of Technological Capabilites on Service Innovation Capability The results of hypothesis 6 (six) show that technological capabilites have a positive effect on service innovation capability. The results of research conducted by Rajapathirana & Hui (2017) emphasize that technological capabilities can facilitate companies to apply the right process technology to develop new products that meet market needs and eliminate competitive threats. It helps to shape and manage the various capabilities of the company to support integrating capabilities and stimulus for innovation services successfully. Dadfar, Dahlgaard, Brege, & Alamirhoor (2013) have identified that superior innovation capabilities tend to implement and develop new product variations to the existing product portfolio. 1936 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate Technological Capabilites is stated as the company's capability to create Service Innovation Capability by developing and introducing to the market new products and services or reducing the costs that burden the value creation process (Pekka & Thomas, 2006). This result is in accordance with the research of Darjat Sudrajat (2013) and Chien S. Y and Tsai C. H (2012) which found the results that Technological Capabilites have a positive effect on Service Innovation Capability. 5. Conclusion This study provides empirical evidence regarding the influence of ambidextrous leadership, customer orientation, environmental innovation to improve service innovation capability through digital capabilities and technological capabilities as mediating variables in MSMEs in Berau Regency, East Kalimantan. The number of samples that met the criteria in this study amounted to 353 samples and were processed using SmartPLS data processing. Based on the analysis and discussion that has been carried out, it can be concluded that: 1) Ambidextrous leadership has a positive effect on digital capabilities. This shows that ambidextrous leadership plays an important role in creating and realizing the ability of MSMEs to improve digital capabilities for quality human resources. Ambidextrous leadership will always support and encourage employees to become active MSME business actors by increasing digital capabilities. 2) Customer Orientation has a positive effect on Digital Capabilities. This shows the most decisive factor in market-oriented strategies, and is considered a set of beliefs that can give the highest priority to customer interests, so that MSME players can improve marketing capabilities, including innovation performance, client satisfaction, and loyalty through improving digital capabilities. 3) Environmental Innovation has a positive effect on Digital Capabilities, indicating that environmental innovation in preserving the environment is so important today for the sustainability of an MSME business. Environmental issues have become one of the important factors that determine the sustainability of an MSME business. Where leaders do not consider that running a business is not only a matter of profit but must also consider that directing business to environmental innovation is also very important for business sustainability with the concept of environment, economy, the business can be developed because through digital capabilities it can reduce the impact of environmental damage. 4) Digital Capabilities has a positive effect on Service Innovation Capability, indicating that the higher the Digital Capabilities carried out by MSME players in Berau Regency, the higher the service innovation capability. Digital activities carried out by MSME players in Berau Regency are not limited by space and time because they have used digital media. The increase in Service Innovation Capability carried out will make new variants, modifications in accordance with customer tastes in creating new products, modifying old products, improving each product quality in order to compete and imitate competing products with their own characteristics. 5) Digital Capabilities has a positive effect on Technological Capabilites, indicating that the ability needed to thrive in this era is when it is able to dominate digital forms of information and communication. Capabilities in information technology are useful for reducing costs in business activities, especially for MSMEs to allocate and save their budget for other uses. Apart from being able to be used by MSME players to monitor competitors' activities, digital capabilities can also serve as additional information to MSME players regarding what good things have not been done by MSME players to increase their competitiveness in the market to generate, process, and disseminate information in every form. 6) Technological Capabilites has a positive effect on Service Innovation Capability, indicating that good technological capabilities can be able to build information that is useful in building the competitive advantage of MSMEs to increase service innovation. technological capabilities have a positive effect on competitive advantage, competitors make MSMEs use digital media to penetrate 1937 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 5: 1923-1939, 2024 DOI: 10.55214/25768484.v8i5.1924 © 2024 by the author; licensee Learning Gate the market to business competitors by differentiating business results. 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