The effect of continuous reconfiguration capability on disruptive business model innovation study on Indonesia digital startups

Chia sẻ: Nguyễn Thảo | Ngày: | Loại File: PDF | Số trang:9

Thêm vào BST

Báo xấu

22
lượt xem 3
download

Download Vui lòng tải xuống để xem tài liệu đầy đủ

This paper aims at examining the effect of continuous reconfiguration capability on disruptive business model innovation on Indonesia digital (tech) startups.

Chủ đề:

Bình luận(0) Đăng nhập để gửi bình luận!

Lưu

Nội dung Text: The effect of continuous reconfiguration capability on disruptive business model innovation study on Indonesia digital startups

International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 04, April 2019, pp. 22-30, Article ID: IJMET_10_04_004 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=4 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed THE EFFECT OF CONTINUOUS RECONFIGURATION CAPABILITY ON DISRUPTIVE BUSINESS MODEL INNOVATION STUDY ON INDONESIA DIGITAL STARTUPS Kurnadi Gularso Binus Business School, Doctor of Research in Management Bina Nusantara University, Jakarta, 11540, Indonesia Tirta Nugraha Mursitama International Relations Department, Faculty of Humanities Bina Nusantara University, Jakarta, 11480, Indonesia Pantri Heriyati, Boto Simatupang Binus Business School, Doctor of Research in Management Bina Nusantara University, Jakarta, 11540, Indonesia ABSTRACT Several studies have indicated that digital (tech) startups’ behaviors tend toward disruptive business model innovation in facing volatility, uncertainty, complexity, ambiguity (VUCA) environment. One of the necessary capabilities to perform such innovation as well as to attain an excellent firm operational performance is continuous reconfiguration capability. This paper aims at examining the effect of continuous reconfiguration capability on disruptive business model innovation on Indonesia digital (tech) startups. This study applied a quantitative method with a partial least-squares structural equation modeling (PLS-SEM) approach to analyze the data obtained. The survey was used to understand the perceptions of Founders/C-Level out of 107 Indonesia startups. This study showed an essential contribution to the literature about the role of transformational capability viz continuous reconfiguration capability for digital (tech) startups as an initiator in executing disruptive business model innovation. The study recommends startups to have this capability that should be followed by determining strategic orientations, especially entrepreneurship orientation, market orientation, and technology orientation. Key words: Continuous reconfiguration capability, Disruptive business model innovation, Digital startups http://www.iaeme.com/IJMET/index.asp 22 editor@iaeme.com
Kurnadi Gularso, Tirta Nugraha Mursitama, Pantri Heriyati, Boto Simatupang Cite this Article: Kurnadi Gularso, Tirta Nugraha Mursitama, Pantri Heriyati, Boto Simatupang, The Effect of Continuous Reconfiguration Capability on Disruptive Business Model Innovation Study on Indonesia Digital Startups, International Journal of Mechanical Engineering and Technology 10(4), 2019, pp. 22-30. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=4 1. INTRODUCTION Today, in the era of the digital economy, digitization has urged and promoted the implementation of business model innovation in incumbent and startup business (Hafkesbrink & Schroll, 2010; Birkinshaw & Ansari, 2015; Teece & Linden, 2017). Further, digital (tech) startups – hereafter in this paper is named “startups” – should create disruptive business model innovation to achieve a significant growth and viable business (PwC, April 2013); Balboni, Bortoluzzi, Tivan, Tracogna, and Venier, 2014; O’Connell, Delaney, & Moriarty, 2015). However, there is scant research on disruptive business model innovation by startups as the initiator. There are also a few research on the antecedents of disruptive business model innovation as first mover strategy particularly in the startups' industry which is facing VUCA (volatility, uncertainty, complexity, ambiguity) business environment. Dynamic capabilities have long been believed to be the ability of businesses to face fast- moving business environments which are characterized by rapid technological change (Teece, 2007) which is currently known as VUCA. Three dimensions of dynamic capabilities are sensing, seizing, and reconfiguring. Reconfiguring as a transformation capability plays an important role especially in the implementation of innovation. Reconfiguration should be continuously conducted to accommodate the continuous innovations being implemented in ever-changing and uncertainty environments. Startups have an entrepreneurial mentality that encourages them to search and create new opportunities to serve their targeted customers. Startups also have always to respond to the market changes and technological turbulence to make them viable and continue managing significant growth. Strategic orientations will align the startups’ organization to manage their goals. The research question here is “What are the effect of continuous reconfiguration capability on strategic orientation and eventually the achievement of disruptive business model innovation of Indonesia startups?” Hence, the general objective of this research is to understand the importance of building continuous reconfiguration capability for startups to make their business viable and get significant growth. The benefit of this study is to contribute to the theory that continuous reconfiguration capability requires the mediation of a strategic orientation for startups in applying the disruptive business model innovation. 2. LITERATURE REVIEW ‘Dynamic capabilities’ is the firm’s ability to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments. These enterprise capabilities are difficult to replicate and should adapt to changing customer and technological opportunities (Teece, Pisano, & Shuen, 1997; Teece, 2007). Reconfiguration or transformation entails recombining and modifying existing resources (Teece, 2014). The continuous aspect of reconfiguration capability is essential to respond to the ever- changing environment such as customers, competitors, and technologies (McGrath, 2013; Teece, 2014). Hawass (2014) suggested after his finding, to effectively develop a reconfiguration capability, a firm has to continuously participate in technological alliances and develop a close cooperative relationship with suppliers, customers, and rivals to acquire updated product-market information. http://www.iaeme.com/IJMET/index.asp 23 editor@iaeme.com
The Effect of Continuous Reconfiguration Capability on Disruptive Business Model Innovation Study on Indonesia Digital Startups In this research, continuous reconfiguration capability is defined as “the ability to transform by continually rearranging the company's resources in the form of intangible resources (such as capabilities) and tangible resources,” (McGrath, 2013; Banjongprasert, 2013; Teece, Pisano, & Shuen, 1997; Eisenhardt & Martin, 2000; Wang & Ahmed, 2007; Barreto, 2010). Strategic orientation represents aspects of leadership. It refers to one of eight dimensions of the leadership competency, i.e., critical thinking (Chung-herrera & Lankau, 2003). A growing stream of studies today endorse the adoption of different strategic orientations such as innovation orientation, technology orientation, entrepreneurial orientation, quality orientation, and productivity orientation (Voss & Giraud, 2011; Zhou, Yim, & Tse, 2005). Entrepreneurial orientation and learning orientation may combine or act in between the market orientation and technology orientation (Schindehutte, Morris, & Kocak, 2008; Hakala, 2010). The implications of strategic orientation are innovation capability/innovation success and competitive advantage towards market performance (Tutar, Nart, & Bingöl, 2015); market performance and financial performance (Hsu, Tsai, Hsieh, & Wang, 2014); firm performance (Mohd, Mohd, Mamun, & Breen, 2017; Gergely, 2016); organizational performance (Obeidat, 2016; Al & Province, 2016); business performance (Fernandes & Solimun, 2017), corporate entrepreneurship (Kakapour et al., 2016), growth with related resource moderation, (Gupta & Basu, 2014). Startups generally conduct strategies through DBMI, which is new to the industry because the business model is the primary driver to a startup’s growth (Balboni, Bortoluzzi, Tivan, Tracogna, & Venier, 2014;(PwC, April 2013). Many DBMIs searches for opportunities from unserved customers through low-cost offerings. That they will eventually take over the incumbents’ market share (Charitou, C. & Markides, C., 2003; Markides, 1997, 1998, 2006), as initiators of DBMIs, their explorative intentions are driven by perceptions of performance- reducing threats and risk experience (Osiyevskyy & Dewald, 2015). The theoretic objective of this research was primarily to predict and identify the effect of continuous reconfiguration capability on disruptive business model innovation with the guidance of strategic orientation, as depicted in Figure 1. The relationship between continuous reconfiguration capability and strategic orientation as well as DBMI was set out in the following three hypotheses: Figure 1 Conceptual Model H1: Continuous reconfiguration capability is positively related to strategic orientation. H2: Strategic orientation is positively related to disruptive business model innovation. http://www.iaeme.com/IJMET/index.asp 24 editor@iaeme.com
Kurnadi Gularso, Tirta Nugraha Mursitama, Pantri Heriyati, Boto Simatupang H3: Continuous reconfiguration capability is positively related to disruptive business model innovation. 3. RESEARCH METHODS For the purpose of this study, a quantitative research method was applied with particular reference to an empirical survey with the Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach to analyze the data. The data were obtained by using questionnaires with a Likert scale (1-4: Strongly disagree, Disagree, Agree, Strongly Agree), from respondents of Founder/C-Level Indonesia startups. The respondents were chosen randomly from the population of DailySocial, an Indonesia digital media startup. The study collected the data using a cross-sectional survey method with a questionnaire that consists of two parts: fill in information and Likert scale statements. The questionnaires were then distributed online through personal accounts, and a small amount was offline directly to the Founders/C-Level of Indonesia startups. This data collection took around five months, from January to May 2018. The total amount of Indonesia startups was recorded as 772 startups. Further, an amount of 265 questionnaires were distributed to the respondents who were taken randomly from the population. The returned questionnaires were 107 or equal to 40.4% response rate. 4. RESULTS AND DISCUSSIONS Descriptive analysis of the data from the “filling in” and “Likert scale” questionnaire together with the findings from some interviews and focus group discussions with Founders/C-Levels, and their related stakeholders would enrich the interpretative explanations. The respondent startups' types are SaaS, Media, On-Demand, E-Commerce, Marketplace, Fintech, Agtech, Edtech, Member Loyalty, and Others. The operating period of the majority of startups is around three years and below with a total of 78 (72.9%), which means that only 29 (27.1%) startups are more than three years old. Sales performance of majority startups as many as 56 (52.3%) are at levels above one billion rupiahs, 40 (37.4%) are at levels below one billion rupiahs, and the remaining 11 (10.3%) are not willing to state their sales performance. With sales growth of under 10% per year of 16 (15.0%); between 10% to 20% per year as much as 20 (18.7%); between 20% 50% per year as much as 24 (22.4%); and the majority or as many as 47 (43.9%) have sales growth of above 50% per year. However, only 37 (34.6%) stated that they had enjoyed profits, while the remaining 70 (65.4%) had not. Five questions that are used as indicators related to continuous reconfiguration capabilities are changes in organizational structure, marketing method or strategy, technological equipment or manufacturing process; aspects of renewing business processes and production/manufacturing processes; and the social-networking aspect with all values above 70% with a standard deviation between 0.62 to 0.72. The six indicators related to strategic orientation are entrepreneurship orientation (innovativeness and risk-taking), market orientation (competitive aggressiveness, customer orientation, and competitor orientation), and technology orientation (technological turbulence). The four indicators related to disruptive business model innovation are value creation (new capabilities); value proposition (new customer relationships); new market disruptive innovation; and low-end market disruptive innovation (efficient products/services). Score items are relatively high which are all above 80% with a standard deviation between 0.60 to 0.70. http://www.iaeme.com/IJMET/index.asp 25 editor@iaeme.com
The Effect of Continuous Reconfiguration Capability on Disruptive Business Model Innovation Study on Indonesia Digital Startups Table 1 Results Summary for Reflective Measurement Models Latent Variable Discriminant Composite Reliability Reliability Indicators Cronbach Indicator Loadings Validity Alpha AVE CRC crc_1 0.754 0.569 0.836 0.883 0.601 Yes crc_2 0.769 0.591 crc_3 0.794 0.630 crc_4 0.812 0.659 crc_5 0.747 0.558 SO so_1 0.623 0.388 0.798 0.858 0.508 Yes so_2 0.513 0.263 so_3 0.692 0.479 so_4 0.827 0.684 so_5 0.813 0.661 so_6 0.756 0.572 DBMI dbmi_1 0.718 0.516 0.740 0.835 0.560 Yes dbmi_2 0.784 0.615 dbmi_3 0.763 0.582 dbmi_4 0.725 0.526 Rather than applying the Cronbach's alpha, Hair et al. (2014) prescribe applying composite reliability to quantify internal consistency, in which all outcome values are within and above a satisfactory range of 0.70 to 0.90, (Nunnally & Bernstein, 1994). All AVE values are above the 0.50 threshold. It means the constructs illustrate the more significant part of the variance of its indicators. Table 1 presents the reflective measurement models. The significance of the path coefficients, the t-values, the level of R2 values, and the predictive relevance (Q2) will evaluate the structural models. While, the goodness-of-fit (GoF) measurement is not necessarily to be used (Hair et al., 2014). R2 values express that exogenous latent variable CRC explains 14.6% of the variance in the endogenous latent variable SO. Likewise, the latent variable SO explains 36.2% of the variance in the endogenous latent variable DBMI. The R2 value of DBMI is above 0.25, hence the number of sample size in this research (107) is adequate, (Cohen, 1992). All Q2 values are higher than 0, which implies that the exogenous construct has predictive relevance for the two endogenous constructs SO and DBMI. The path coefficient values which are aligned with the t-values. T-values determine the significance of the relationship between two variables with the minimum value of 1.96 is considered as a significance relation. The threshold derived from a two-tailed test with a significance level of 5%. Under this criterium, the results concluded that CRC has a significant positive influence to achieve SO and subsequently SO has a significant positive influence in attaining DBMI. However, the results also showed that CRC does not have a significant direct effect on DBMI. Following, examine the mediating effect of SO in this research model by directly analyzing the relationship between CRC and DBMI by removing the SO variable. The analysis shows that this relationship has a path coefficient of 0.357 with t-value of 3.933. These results indicate that CRC has a significant positive relation with DBMI. For this reason, the mediating effect of SO is calculated, with the VAF (Variance Accounted for) result is 57.5%. Because this result http://www.iaeme.com/IJMET/index.asp 26 editor@iaeme.com
Kurnadi Gularso, Tirta Nugraha Mursitama, Pantri Heriyati, Boto Simatupang is in the range of 20% ≤ VAF ≤ 80%, it is concluded that SO gives a ‘partial mediation’ in the relationship between CRC and DBMI. These results indicate that CRC affects SO positively and significantly in achieving DBMI while CRC is not significantly positive in influencing DBMI achievement directly. Likewise with SO which shows its role as a mediator of the two variables CRC and DBMI partially. The study shows that the variable continuous reconfiguration capabilities play a critical role in transforming startups to attain disruptive business model innovation. It is different from common reconfiguration capabilities, the nature of “continuous” reconfiguration is to attain optimum performance of innovation implementation in responding to customers, competitors, and technologies change (Rindova & Kotha, 2001; Teece, 2007). Continuous reconfiguration capabilities will influence the startups’ strategic orientations which consist of entrepreneurial orientation (innovation & risks), market orientation (aggressiveness, customers, competition), and turbulence technology. Further, strategic orientation as a mediator will influence the achievement of disruptive business model innovation (Hakala, 2010; Johnson, Martin, & Saini, 2012; Frambach, Fiss, & Ingenbleek, 2016; (Mutterlein M. A. & Kunz, 2017). Interviews and forum group discussions showed that startups focus on customer-centric while profit-oriented is considered as a consequence if startups have succeeded in innovating by providing solutions for low-end customers and/or customers who have not been well served and even ignored by incumbents (Frambach, Fiss, & Ingenbleek, 2016; Mütterlein & Kunz, 2017). One of the startup founders argued: "We established startups instead of focusing on the profits we were targeting, but we focused on products/services including how to deliver them to targeted customers." These proved the role of strategic orientation as a guideline for organizations in implementing disruptive business innovation model. 5. CONCLUSIONS Indonesia startups should implement disruptive business model innovation to survive and get significant growth in facing VUCA business environment. Hence, startups need to have dynamic capabilities in the form of entrepreneurial activities. The role of continuous reconfiguration capability as a capability of transformation through reconfiguring both internal as well as external assets is essential during innovation implementation. Continuous reconfiguration is applicable to respond to the ever-changing environment such as market changes as well as technology turbulence. The continuous reconfiguration capability also influences the need always to search and create new opportunities. Consequently, the strategic orientations are needed to guide the organization in seizing these opportunities. Entrepreneurial orientation, market orientation, and technology orientation will mediate this reconfiguring capability to attain disruptive business model innovation. This study also gives insight that startups have some characteristics which distinguish them with traditional business. Startups implement disruptive innovation continuously instead of sustaining innovation done by incumbents, to serve and resolve customer needs and wants and think how always to get significant growth to beat the market. Eventually, the continuous reconfiguration capability is the necessary capability for startups. This study has several limitations and recommendations. Because of the dynamic nature of the business and its environment, quantitative methods may not be adequate to study the behavior of disruptive innovations. The construct of disruptive business model innovation could have been ideally measured by assessing its disruptive impact on the incumbent’s traditional business model and market by objective measures including the affected financial performance http://www.iaeme.com/IJMET/index.asp 27 editor@iaeme.com
The Effect of Continuous Reconfiguration Capability on Disruptive Business Model Innovation Study on Indonesia Digital Startups as well as potential market loss. However, it is not easy to obtain financial data from incumbents, including their market share data which was eroded by the disruptor. The next research may need to test other variables that are also relevant and effective so that it can improve the role of continuous reconfiguration capability to increase predictive value in achieving disruptive business model innovation. Such as the uses of top management time and line manager involvement are seen as essential aspects of avoiding problem areas. Although, the results of this study are satisfactory as preliminary research to be followed up by further studies on strategy and growth management of digital startups. Future researches should consider aspects such as the age and scale of organization, the existence of investors/venture capitals, and the maturity of Founders/C-Level that can be used as control variables. REFERENCES [1] Attias D. (2017) The Autonomous Car, a Disruptive Business Model? In: Attias D. (eds) The Automobile Revolution. Springer, Cham 99–113. [2] Balboni, B., Bortoluzzi, G., Tivan, M., Tracogna, A., & Venier, F. (2014). The Growth Drivers of Start-up Firms and Business Modelling: A First Step toward a Desirable Convergence. Management, 9(2), 131-154. [3] Banjongprasert, J. (2013). An Empirical Investigation of Dynamic Capabilities At the Individual Level : the Context of New Service. [4] Barreto, I. (2010). Dynamic Capabilities: A Review of Past Research and An Agenda for the Future. Journal of Management, 36(1), 256-280. [5] Birkinshaw J, Ansari S (2015) Chapter 5 Understanding Management Models: Going Beyond “What” and “Why” to “How” Work Gets Done in Organizations. In: Foss NJ, Saebi T (eds) Business model innovation: the organizational dimension. Oxford University Press, Oxford, pp 85–103 [6] Chang, C. C., & Kuo, C. G. (2013). Exploring Dynamic Capabilities of Executives for Core Strategy. African Journal of Business Management, 7(40), 4188-4198. [7] Charitou, C. & Markides, C. (2003). Responses to disruptive strategic innovation. Sloan Management Review. 44 (2), pp. 55-63. [8] Chen, M. J., Lin, H. C., & Michel, J. G. (2010). Navigating in A Hypercompetitive Environment: The Roles of Action Aggressiveness and TMT Integration. Strategic Management Journal, 31(13), 1410-1430. [9] Chu R. (2017) Business Model Revolution: Four Cases of the Fastest-Growing, Disruptive Companies of the Twenty-First Century. In: Brem A., Viardot E. (eds) Revolution of Innovation Management. Palgrave Macmillan, London. [10] Chung-Herrera, B. G., Enz, C. A., & Lankau, M. J. (2003). A Competencies Model: Grooming Future Hospitality Leaders. Cornell Hotel and Restaurant Administration Quarterly, 44(3), 17-25. [11] Cohen, J. (1992). Quantitative Methods in Psychology: A Power Primer, Psychological Bulletin 112(1), 155–159. http://www.iaeme.com/IJMET/index.asp 28 editor@iaeme.com
Kurnadi Gularso, Tirta Nugraha Mursitama, Pantri Heriyati, Boto Simatupang [12] Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic Capabilities: What are They? Strategic Management Journal, 21(10‐11), 1105-1121. [13] Frambach, R. T., Fiss, P. C., & Ingenbleek, P. T. (2016). How Important is Customer Orientation for Firm Performance? A Fuzzy Set Analysis of Orientations, Strategies, and Environments. Journal of Business Research, 69(4), 1428-1436. [14] Hakala, H. (2010). Configuring Out Strategic Orientation, (232). [15] Hamid Hawass, H. (2010). Exploring the Determinants of the Reconfiguration Capability: A Dynamic Capability Perspective. European Journal of Innovation Management, 13(4), 409-438. [16] Hsu, T. T., Tsai, K. H., Hsieh, M. H., & Wang, W. Y. (2014). Strategic Orientation and New Product Performance: The Roles of Technological Capability. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 31(1), 44-58. [17] Johnson, J. L., Martin, K. D., & Saini, A. (2012). The Role of A Firm's Strategic Orientation Dimensions in Determining Market orientation. Industrial Marketing Management, 41(4), 715-724. [18] Markides, Constantinos (1997). Strategic Innovation. Sloan Management Review 38(3):9– 23. [19] Markides, Constantinos (1998). Strategic Innovation in Established Companies. Sloan Management Review 39(3):31–42. [20] Markides, C. (2006). Disruptive innovation: In need of better theory. The Journal of Product Innovation Management, 19–25. [21] McGrath, R. G. (2013). The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business. Harvard Business Review Press. [22] Mütterlein M.A., J., & Kunz, R. (2017). Influence of Entrepreneurial and Alliance Orientation on Business Model Innovation. EMMA Conference: Value Creation in Media Markets: Business Models, Clusters and Eco Systems 49(0), 0–13. [23] Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York: McGraw-Hill, Inc. [24] O’Connell, K., Delaney, K., & Moriarty, R. (2015). Digital Business Transformation: Disrupt To Win, (June), 1–12. [25] Osiyevskyy, O., & Dewald, J. (2015). Explorative versus exploitative business model change: the cognitive antecedents of firm‐level responses to disruptive innovation. Strategic Entrepreneurship Journal, 9(1), 58-78. [26] PwC. (April 2013). The Startup Economy: How to support tech startups and accelerate Australian innovation. Australia: Google. [27] Rindova, V. P., & Kotha, S. (2001). Continuous Morphing: Competing through Dynamic Capabilities, Form, and Function. The Academy of Management Journal, 44(6), 1263–1280. http://www.iaeme.com/IJMET/index.asp 29 editor@iaeme.com
The Effect of Continuous Reconfiguration Capability on Disruptive Business Model Innovation Study on Indonesia Digital Startups [28] Schindehutte, M., Morris, M. H., & Kocak, A. (2008). Understanding Market‐Driving Behavior: The Role of Entrepreneurship. Journal of Small Business Management, 46(1), 4- 26. [29] Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319-1350. [30] Teece, D. J. (2014). The Foundations of Enterprise Performance: Dynamic and Ordinary Capabilities in An (Economic) Theory of Firms. Academy of Management Perspectives, 28(4), 328-352. [31] Teece, D. J., & Linden, G. (2017). Business Models, Value Capture, and the Digital Enterprise. https://doi.org/10.1186/s41469-017-0018-x [32] Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18(7), 509-533. [33] Voss, G. B., & Giraud, Z. (2011). Strategic Orientation and Firm Performance in an Artistic Performance Environment. Journal of Marketing, 64(1), 67–83. [34] Wang, C. L., & Ahmed, P. K. (2007). Dynamic Capabilities: A Review and Research Agenda. International Journal of Management Reviews, 9(1), 31–51. [35] Zhou, K. Z., Yim, C. K. (Bennett), & Tse, D. K. (2005). The Effects of Strategic Orientations on Technology- and Market-Based Breakthrough Innovations. Journal of Marketing, 69(2), 42–60. http://www.iaeme.com/IJMET/index.asp 30 editor@iaeme.com