Harnessing soft innovation resources leads to neo open innovation

Abstract Advancement of the digital economy has transformed the concept of the growth crossover in nations and firms, both concerning input and output. Advanced economies have been confronting a dilemma between input increases and output decreases. Contrary to traditional expectations, excessive increase in input has resulted in a productivity decline in output. A solution to this dilemma can only be expected by harnessing the vigor of soft innovation resources that lead to neo open innovation in the digital economy. This paper attempts to demonstrate this hypothetical view. Based on an empirical analysis of the development trajectories of 140 countries and 500 global ICT firms, dynamism, resulting in bipolarization between a virtuous cycle and a vicious cycle between input increases and productivity enhancement, was discovered. Furthermore, an empirical analysis focusing on the development trajectories of two world ICT leaders, Finland and Singapore, identified a mechanism of neo open innovation that assimilates soft innovation resources into a national production system. This mechanism can substitute for research and development (R&D) and removes structural impediments to growth while providing relief from the increasing burden of R&D investment. The above findings provide insightful suggestions for drafting a roadmap towards neo open innovation in the digital economy.


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Introduction
Advances in information and communication technology (ICT) have generated the digital economy. This can largely be attributed to the dramatic advancement of the Internet. The further progression of digitalized innovation over the last two decades, such as mobile services, particularly of smartphones, has augmented this generation significantly.
The Internet promotes a free culture, the consumption of which provides utility and happiness to people but cannot be captured through the GDP that measures revenue (Lowrey, 2011). Authors have defined this Internet-driven added value as uncaptured GDP (Watanabe et al., 2015a). The shift in people's preferences from economic value to supra-functionality beyond economic value (encompassing social, cultural, and economic values) (MacDonagh, 2008) induces the further advancement of the Internet, which intensifies the increasing dependence on uncaptured GDP.
Thus, the technological shift from the computer age to the Internet and the abundance of freely available digital products and services in the digital economy (Brynjolfsson et al., 2014) has resulted in a new co-evolution among people's shifting preferences, the advancement of the Internet, and the increasing dependence on uncaptured GDP

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A C C E P T E D ACCEPTED MANUSCRIPT 3 A solution to this dilemma can only be expected by harnessing the vigor of soft innovation resources, which are a condensate and crystal of the advancement of the Internet (Tou et al., , 2018c. Soft innovation resources arouse and activate latent self-propagating functions of ICT, which induce functionality development, leading to a supra-functionality beyond economic value that corresponds to people's shift in preferences, as illustrated in the lower part of Fig. 1.

Fig. 1. The Hybrid Role of Soft Innovation Resources.
Thus, the survival strategy of ICT-advanced economies against the foregoing dilemma reacts to the spontaneous creation of uncaptured GDP and leverages the emergence and utilization of soft innovation resources. The advancement of the Internet, induced by a preferences shifting to a supra-functionality beyond economic value, awakens and induces soft innovation resources, as they are a condensate and crystal of the advancement of the Internet. Inspired by the foregoing, spinning-off, co-evolutional innovation among ICT advancements, paradigm shifts, and people's preferences, this paper attempts to demonstrate this hypothetical view. Based on an intensive review of preceding studies and an empirical analysis of the development trajectories of 140 countries and 500 global ICT firms, dynamism resulting in bipolarization between a virtuous cycle and a vicious cycle between input increases and productivity enhancement was discovered. Furthermore, an empirical analysis, focusing on the development trajectories of two world ICT leaders, Finland and Singapore, identified a mechanism of neo open innovation that assimilates soft innovation resources into a national production system. This mechanism substitutes for R&D and removes structural impediments to growth while providing relief from the increasing burden of R&D investment.
The above findings provide insightful suggestions for drafting a roadmap towards neo open innovation in the digital economy.
The structure of this paper is as follows. Section 2 discusses unique features of ICT. Section 3 analyzes neo open innovation in the digital economy. The hybrid role of soft innovation resources is analyzed in Section 4. The mechanism of the hybrid role of soft innovation resources is investigated in Section 5. Finally, Section 6 summarizes the noteworthy findings, policy suggestions, and future research.

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Simultaneous Dissemination
The digitalization of the economic activity can be broadly defined as the incorporation of data and the Internet into production processes and products, new forms of household and government consumption, fixed-capital formation, cross-border flows, and finance (IMF, 2018a).
Consequently, this activity is subject to unique features of ICT, centered on the advancement of the Internet. This feature can be characterized as simultaneous dissemination, logistic growth, and the two-faced nature of price formation.
The simultaneous dissemination features of ICT can be attributed to the Internet's functional features of self-propagating permeation, homogeneous ICT stock creation, and co-evolutionary advancement with new functional devices.

(1) Self-propagating Permeation
The dramatic advancement of the Internet has generated the digital economy, which has changed the way business is conducted and daily life (Tapscott, 1994). The further progression of digitized innovation over the last two decades, such as cloud services, mobile services, and artificial intelligence, has augmented this change significantly. This has accelerated the permeation of the Internet into ICT in general , and has provided us with unprecedented services and conveniences (DBCDE, 2009).

(2) Homogeneous ICT Stock Creation
Such permeation creates homogeneous ICT stock that plays a locomotive power in the IoT society.
By means of a bibliometric approach, authors traced the trend in the transforming factor of R&D into ICT stock 1 in 27 ICT-related key scientific research articles consisting of (i) Internet R&D, (ii) Internet-related peripheral R&D, and (iii) other ICT R&D over the period of 1980-2015 (see the details in . Above analysis demonstrated that while the values of the transformation factor were diverged by 2005, they have been converging through 2010-2015; thereby, technology stock, both of the Internet and other broad ICT, can be treated as a sum of respective R&D that is leading to homogeneous ICT stock creation.

(3) Co-evolutionary Advancement with New Functional Devices
The dramatic advancement of the Internet and its further progression of digitized innovation have augmented the permeation of the Internet into not only broad ICT but also into all production factors leading to an IoT society .
In this permeation process, digitalized innovation mutually stimulates each other, leading to co-evolutionary dynamics, and creates a new social ecosystem (OECD, 2016).
This is quite similar to the co-evolutionary development of personal computers (PCs) and printers through coopetition (cooperation and competition) strategies in the 1990s, as illustrated in Fig. 2.

Fig. 3-2. The Correlation between the GDP Per Capita and Smartphone
Ownership Ratio in 40 Countries (2015).
Source: Pew Research Center (2016). Fig. 3 demonstrates that ICT simultaneously permeates into 40 countries, regardless of economic development stage. Previously, a delay in economic development was a fundamental impediment in emerging and developing economies, resulting in a vicious cycle between economic development and technological advancement. However, Fig. 3 demonstrates that countries in emerging and developing economies enjoy the Internet and smartphone usage, notwithstanding their low level of economic development.
Moreover, Fig. 4 demonstrates that, contrary to traditional technology, the discrepancy of the speed of dissemination of advanced ICT, such as the Internet and mobile phones, between high-income countries and low-income countries has dramatically decreased. Such simultaneous worldwide dissemination creates a new, ICT-driven social ecosystem (UNESCO, 2015). In this dissemination process, digitalized innovation mutually stimulates each other, leading to co-evolutionary dynamics, and creates a new social ecosystem. Fig. 5 and Table 1 demonstrate a strong correlation between Internet use and smartphone ownership in 40 countries regardless of economic level. Such a strong correlation stimulates the co-evolutionary development of ICT advancement, leading to the creation of a new social ecosystem.  All of these demonstrate ICT's simultaneous dissemination crossover to a techno-economy, and this can be seen as one of the unique feature of ICT.

Logistic Growth
Logistic growth nature is identical feature of ICT. Simultaneous dissemination of ICT centered on the advancement of the Internet as reviewed in the preceding sub-section highlights logistic development and diffusion, bi-polarization fatality, and self-propagating potential.
(1) Logistic Development and Diffusion ICT in which network externalities function to alter the correlation between innovations and institutional systems which creates new features of the innovation leading to exponential increase (Watanabe et al., 2004). Schelling (1998) portrayed an array of logistically developing and diffusing social mechanisms stimulated by these interactions. Advancement of the Internet further stimulates these interactions and accelerates ICT's logistically developing and diffusing feature.
(2) Bi-polarization Fatality Given the logistic development and diffusion, ICT-driven growth follows a sigmoid trajectory which continues to grow until it reaches carrying capacity (upper limit of growth). In this trajectory, while growth rate continues to increase before reaching to inflection point corresponding to the half level of carrying capacity, it changes to M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT decrease after exceeding the inflection point. Thus, contrary to simultaneous dissemination, ICT-driven logistic growth incorporates bi-polarization fatality, increase and decrease of marginal productivity between before and after the inflection point. Fig. 6 demonstrates development trajectories in 140 countries in the world and 500 global ICT firms in 2016 taking ICT advancement and its marginal productivity to GDP per capita and sales, respectively. Fig. 6 demonstrates clear bi-polarization between ICT-growing economies and ICT-advanced economies. While the former enjoys a virtuous cycle between ICT advancement and productivity increase, the latter suffers a vicious cycle as further ICT advancement results in productivity decrease.

(3) Self-propagating Potential
While growth will stagnate as growth rate decreases after the inflection point and closing to the upper limit in the ICT-driven growth, in particular innovations, the correlation of interaction between innovation and institutions display a systematic change in the process of growth and maturity. This leads to the creation of a new higher carrying capacity in the processes of its development. This functions to enhance the level of carrying capacity as development proceeds. This suggests that ICT-driven growth incorporates self-propagating potential (Watanabe et al., 2004). Arose and activation of this potential may provide a solution to productivity decrease as a consequence of bi-polarization fatality.  Advanced ICT, initiated by the advancement of the Internet, incorporates a contrasting nature, bipolarization derived from its two-faced nature with respect to price formation. While the advancement of ICT generally contributes to the enhanced prices of technology through the development of new functionality, the dramatic advancement of the Internet reacts to decreased prices of technology due to its nature, consisting of freebies, easy and free replication, and mass standardization (Watanabe et al., 2015b). Thus, advancement of the Internet beyond a certain level reverses the increasing prices to decreasing prices. These prices are equivalent to the marginal productivity of ICT under the maximum profit option in the competitive circumstances. This corresponds to the aforementioned bi-polarization fatality, stemming from logistic growth. Fig. 7 illustrates this dynamism regarding 500 global ICT firms that demonstrate bipolarization between price increase and decrease, depending on the ICT advancement. Consequently, such bipolarization has become inevitable in the competitive game of global ICT firms. Provided that these firms seek to maximize profit in the competitiveness market, prices decrease as a consequence of the excessive ICT advancement results in their marginal productivity of ICT decline. Fig. 6 also demonstrates such phenomena concerning 500 global ICT firms in 2016. This figure demonstrates explicit bi-polarization between high R&D-intensive firms (HRIFs) and the remaining low R&D-intensive firms (LRIFs). HRIFs have fallen into a vicious cycle between R&D expenditure centered on ICT and its marginal productivity, as the former's increase results in a decline for the latter. On the contrary, LRIFs have maintained a virtuous cycle, as an R&D increase leads to marginal productivity Global ICT firms endeavor to achieve sales growth by leveraging ICT's contribution to this growth, consisting of an increase in the marginal productivity of ICT (MP) and R&D intensity (RS). The product of both factors (MP x RS) represents the contribution of ICT to the sales growth rate. Fig. 8 illustrates this strategy through the stages of global position according to R&D level (R). This strategy can be attained by constructing a virtuous cycle between MP and R (an R increase leads to an MP increase, which, in turn, induces further R increases), as far as global ICT firms remain LRIFs (stage A in Fig. 8). However, once they move up to HRIFs (stage B), they fall into a vicious cycle (an R increase results in declining MP (stage C)). In this pitfall, MP recovery can be attained by reducing R (moving back to A) which results in diminishing the target sales growth.

RS RS
In order to attain the target sales growth that is essential for the survival of global ICT firms HRIFs should find disruptive innovation solutions to overcoming this dilemma. This solution can be found through: (i) Incorporation of the vigor of LRIFs that enjoy a virtuous cycle between R and MP, and/or, (ii) Harnessing the vigor of external innovation resources that do not accelerate a vicious cycle.
The former option can be expected by harnessing the vigor of emerging and developing countries (who remain at stage A) that also enjoy the benefit of digital innovation simultaneously. Authors (e.g., Watanabe et al., 2015a) have postulated the significance of co-evolutionary acclimatization strategies for this option, given the possibility of further ICT advancement in the ICT-advanced economies. 3 However, as confronting the rising capital intensity in ICT-advanced economies subsequently increases the burden of such investment (The Economist, 2018), this option no longer fits reality. The Economist (2018) revealed the serious concern on rising capital intensity of global ICT leaders by pointing out that "Investors love tech stocks for their high margins and low investment. But this view no longer fits reality. For the world top eight ICT firms total investment has tripled since 2013, to $180 bn a year. Internet firms are now the corporate world's largest spenders, but exhibit little of the rigor seen at conventional big investors such as Shell or Intel. The probable result is lower returns as firms throw cash at mediocre new businesses and enter the markets of rivals." Consequently, the latter option has become a more promising option that can be expected by means of neo open innovation, which harnesses the vigor of soft innovation resources (which are external to R) corresponding to the digital economy. The next section discusses the consequences of this option.

Endeavors against Productivity Decline (1) Consequences of R&D-driven Logistic Growth
Confronting the aforementioned dilemma, ICT-advanced economies have been endeavoring to find a practical solution by transforming into a new business model. Given that this dilemma stems from the unique feature of ICT, logistic growth with simultaneous dissemination, as reviewed in Section 2, this feature should be reviewed first (see the details of the mathematical demonstration in the column 1). Table 2 analyzes ICT-driven developing strategies in 136 countries across the world as well as in 500 global ICT firms in 2016 by comparing their linear growth (model A) and logistic growth (model B).  Table 2 demonstrates that ICT-driven logistic growth trajectories (model B) were statistically more significant both in the 136 countries and 500 ICT firms examined. Consequently, they are subject to bi-polarization fatality, as reviewed earlier and given the two-faced nature of price formation, they cannot avoid the foregoing dilemma between R&D increase and productivity decline.

Column 1: Mathematical demonstration
Digital value V created by in an IoT society can be depicted as follows: where I g : gross ICT stock = I (ICT stock) +J (internet dependence); X: other production factors.
I g embodies into X in an IoT society as follows: where p x and r x : coefficients.

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Synchronizing equations (2) and (3): This demonstrates that V is governed by I g under the above circumstances.
As the Internet permeates into ICT in general, I g increases proportional to gross R&D represented by gross R&D expenditure (see Note 1).
where R j : R&D related to the Internet, and R i : R&D related to other ICT; ρ: rate of obsolescence of ICT, and g: R&D growth rate at initial stage.

Note 1 ICT stock at time t
ICT stock can be appropriated proportional to gross R&D: where m: time-lag between R&D and commercialization.
Substituting equation (5) for Ig in equation (4): Thus, digital value is governed by gross R&D in an IoT society. Given the logistic growth nature of ICT, V can be developed by an R-driven logistic growth function.
where N: carrying capacity; and a: velocity of diffusion. Equation (7) develops the following simple logistic growth function (SLG): This function leads to bipolarization as follows: (2) Self-propagating Function Confronting such circumstances, ICT-advanced economies endeavor to transform their business model. As far as the development trajectory depends on the simple logistic growth (SLG) trajectory, its digital value, V s (R), saturates with the fixed upper limit. However, once the trajectory shifts to logistic growth within the dynamic carrying capacity (LGDCC) trajectory that incorporates the self-propagating function, enhancing the upper limit dynamically as growth proceeds, its digital value, V L (R), can continue to increase, supported by this function.
Recalling particular innovation, which creates new carrying capacity during the process of diffusion, transforming endeavors in response to the foregoing dilemma corresponds to shifting to a LGDCC trajectory (see the details of the mathematical demonstration in the column 2). Table 3 analyzes the development trajectories of 500 global ICT firms in 2016 by comparing the SLG and LGDCC.  LGDCC. This endeavor corresponds to their efforts in arousing and activating the latent self-propagating function incorporated in ICT.

Column 2: Mathematical demonstration
In particular innovation which creates new carrying capacity N(R) during the process of diffusion, equation (7) is developed as follows: Equation (12) develops the following logistic growth within a dynamic carrying capacity LGDCC) which incorporates self-propagating function as carrying capacity increases corresponding to V(R) increase as depicted in equation (14) Induced by this self-propagating function, functionality (FD) spirally increases corresponding to V(R) increase as depicted in equation (15): As far as the development trajectory depends on SLG trajectory, its digital value (; % () saturates with upper limit depicted by fixed N without self-propagating function, once the trajectory shifts to LGDCC, it can continue to increase supported by self-propagating function and led by dynamically enhancing upper limit E U % (. Therefore, the magnitude of self-propagating function (MSPF) can be estimated by the ratio of E U % ( and ; % ( as follows (Watanabe et al., 2017b):

Note 2 Inflection point in LGDCC
LGDCC function by equation (13) can be approximated by the following SLG function (Watanabe et al., 2009) Inflection level in LGDCC is higher than that of in SLG function without self-propagating function.

Note 3 Assessment of self-propagating function
As reviewed in Section 2.2, ICT incorporates self-propagating potential. This potential can be measured by equation (14) which is governed by the growth rate and the level of development trajectory (V L (R)). This level in LGDCC is identified by the third term of the denominator of equation (13). This term constitutes SLG function in which a coefficient a k plays a significant role in determining the initial level and velocity of this function.

The Transformative Direction Initiated by Global ICT Leaders
Based on these analyses, Fig. 9 illustrates the dynamism of HRIFs in 2016 in transforming the productivity decline into supra-functionality beyond economic value that satisfies people's preferences in the digital economy (  This inflection level in LGDCC is much higher than that of in SLG, without the self-propagating function, which implies that global ICT firms can avoid the productivity decline to some extent by attempting to increase the self-propagating function, as illustrated in the middle-left of Fig. 9 (see the details of this mechanism in Notes 2 and 3 of the column in Section 3.2). However, there exists a certain limit to maintaining the productivity increase by only such an effort. Thus, the excessive dependence on R&D (proportional to ICT that incorporates a two-faced nature of price formation) necessitates the effective utilization of external resources (e.g., the vigor of LRIFs that enjoy a virtuous cycle between R and MP and/or the external resources that do not accelerate a vicious cycle) to compensate for the productivity decline, as reviewed in Section 2.

Transformation into a Disruptive Business Model (1) The Disruptive Business Model Initiated by Global ICT Leaders
The above analyses demonstrate the new disruptive business model initiated by the global ICT leaders for increasing functionality development by exploring and utilizing external resources that arouse and activate the latent self-propagating function indigenous to ICT. The activated self-propagating function induces functionality development, leading to supra-functionality beyond economic value that corresponds to people's preferences shift. This shift, in turn, induces the further advancement of the Internet and leverages the co-evolutionary advancement of innovation in the digital economy, as illustrated in Fig. 10.

Fig. 10. The Disruptive Business Model Initiated by Global ICT Leaders.
As postulated in Section 2, these external resources could be an incorporation of the vigor of LRIFs that enjoy a virtuous cycle between R and MP and/or of external innovation resources that do not accelerate a vicious cycle. Harnessing the vigor of emerging and developing countries that not only enjoy the benefit of digital innovation simultaneously with countries of advanced economies but that also demonstrate a leapfrogging accomplishment in the IoT society should be considered as a promising solution to the former option. However, as reviewed in Section 2, considering the rising capital intensity in ICT-advanced economies and the subsequent increasing burden of such investment (The Economist, 2018), the latter option has become more promising.

(2) Neo Open Innovation by Harnessing Soft Innovation Resources
Neo open innovation that harnesses the vigor of soft innovation resources that correspond to the digital economy has, thus, become a promising solution to the critical dilemma.

Soft Innovation Resources in the Global ICT Leaders
Confronting the foregoing dilemma between R&D expansion and marginal productivity of ICT decline, HRIFs have been endeavoring to transform into a new business model that creates supra-functionality by harnessing the vigor of soft innovation resources, which arouse and activate the latent self-propagating function, as demonstrated in Fig. 12. Thus, the absorption and assimilation of soft innovation resources can be counted as contributors to growth but not counted as additional expenditures, as suggested in Fig.  11.

Dynamism in Performing the Hybrid Function
Soft innovation resources arouse and activate the latent self-propagating function indigenous to ICT, which induces functionality development, leading to supra-functionality beyond economic value. This corresponds to people's preferences shift and induces further advancement of the Internet. Furthermore, this advancement accelerates the increasing dependence on uncaptured GDP, which leverages the harnessing of the vigor of soft innovation resources, as reviewed earlier. At the same time, the advancement of the Internet arouses and induces soft innovation resources, as they are a crystal of the Internet. Thus, a virtuous cycle exists between the emergence and utilization of soft innovation resources, supra-functionality beyond economic value, advancement of the Internet, uncaptured GDP dependence, and further leverage to soft innovation resources emergence, as illustrated in Fig. 1.
In addition, it cannot be overlooked that soft innovation resources also contribute to captured GDP increases by removing the structural impediments to its growth. . This observation reinforces a plausible view that the "well-being of the Finnish people has developed in a more positive direction than one might conclude by GDP data" (Ylhainen, 2017); furthermore, it prompts the hypothetical view that Finland has depended on uncaptured GDP more largely than Singapore by spinning-off from the traditional co-evolution of economic value, traditional ICT development, and GDP growth into a new co-evolution of people's preferences shifting towards supra-functionality beyond economic value (encompassing social, cultural, and emotional values), advancement of the Internet for further functionality, and increasing dependence on uncaptured GDP, as illustrated in Fig. 1  (Watanabe et al., 2015b).
However, the recent reversal trend in GDP growth between the two digital leaders (Finland's resurgence and Singapore's stagnation during a reversal in R&D dependence) reveals that Finland's resurgence can be attributed to soft innovation resources that function by removing structural impediments in growth. Soft innovation resources act to remove structural impediments of GDP growth, such as conflict between the public, employers, and labor unions, gender disparity, and increasing discrepancy concerning an aging society .
Thus, the spontaneous creation of uncaptured GDP through the effective utilization of soft innovation resources contributes to growth through its hybrid function, as illustrated in Fig. 1 (Watanabe et al., 2018b).

Assessment of Soft Innovation Resources as a Crystal of the Internet
Based on the augmented permeation of the Internet into broad ICT and the subsequent creation of a new social ecosystem, particularly with smartphones, as reviewed in Section 2, the innovation dynamism in the IoT society that has been activated by soft innovation resources can be described as follows: (i) Since global ICT firms are at the forefront of the IoT society, soft innovation resources, especially their critical resources against productivity decline in the digital economy, seem to be a condensate and crystal of the Internet/smartphones.
(ii) Soft innovation resources arouse and activate a latent self-propagating function indigenous to ICT, which can be attributed to the Internet permeating into soft innovation resources.
(iii) The activated self-propagating function induces functionality development, which leads to supra-functionality beyond economic value, corresponding to a shift in people's preferences. This shift, in turn, induces further advancement of the Internet.
Based on these three postulates, the assessment of the conceptualization and operationalization of soft innovation resources can be undertaken through the three approaches, as illustrated in Fig. 13.

(1) Resources Assessment
First, considering typical soft innovation resources, the correlation with the advancement of the Internet/smartphones was examined.

1) Sleeping Resources
Following the preceding analysis on "Uber's Ride-sharing Revolution" (Watanabe et al., 2016b, 2017a), the effect of the advancement of the Internet on Uber's increase was examined. Given the close relationship between the Internet and smartphone dependence, as demonstrated in 2.1 (3), a monthly trend in smartphone dependence was used. Summarized in Table 4, the results of analysis were statistically significant and demonstrated that the advancement of the Internet (via smartphone) significantly contributed to the utilization of sleeping resources by reducing prices typically observed with Uber. The figures in parentheses indicate the t-statistics: all are significant at the 1% level except * 5%, ** 10% (same as following analyses).

2) Trust
Following the preceding analysis of the "Co-evolution between trust in teachers and higher education toward digital-rich learning environments" (Watanabe et al., 2016c), the effects of the advancement of the Internet on an increase in trust were examined. Summarized in Table 5, the results of the analysis were statistically significant and demonstrated that the advancement of the Internet contributed to an increase in trust in 12 ICT advanced countries.

3) Memory and Dream
Following the preceding analysis on the "Co-evolution between streaming and live music" (Naveed et al., 2017), the effect of the advancement of the Internet on the reactivation of live music was examined. Similar to Uber, monthly trends in smartphone dependence were used. Summarized in Table 6, the results of the analysis were statistically significant and demonstrated that the advancement of the Internet (via M A N U S C R I P T

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26 smartphones) significantly contributed to reactivation of live music.

4) Untapped Resources
Following the preceding analysis on "Harnessing women's potential as untapped resources" (Watanabe et al., 2017b), the effects of the advancement of the Internet on the utilization of untapped resources were examined. Summarized in Table 7, the results of the analysis were statistically significant and demonstrated that the advancement of the Internet contributed to gender balance improvement.  All cases demonstrated that soft innovation resources have been governed significantly by the advancement of the Internet and are considered as a condensate and crystal of the Internet.
(2) Self-propagating Function Assessment Next, the second postulate, that "attributed to the advancement of the Internet, soft innovation resources activate a latent self-propagating function", was examined. Table 8 summarizes the result of the correlation analysis between Internet dependence and the self-propagating function in UPM (a world circular economy leader; Watanabe et al., 2018e). The results were statistically significant and demonstrated that the advancement of the Internet contributed to a significant increase in the self-propagating function. Its contribution increased as Internet dependence increased. Table 8 The Correlation between Internet Dependence and the Self-propagating Function in UPN  ln

(3) Internet Inducement Assessment
Third, inspired by the preceding two demonstrations, the third postulate, that "activated self-propagating function induces functionality development, leading to supra-functionality, which, in turn, induces further advancement of the Internet", was examined. Table 9 summarizes the correlation between supra-functionality and the advancement of the Internet in Japan, which is sensitive to institutional innovation concerning external shocks and crises. Table 9 The Correlation between the Preferences Shift and the Advancement of the Internet in Japan  ln J = -35.87 + 9.08 D 1 ln Q + 9.64 D 2 ln Q + 9.77 D 3 ln Q adj. R 2 0.  Table 9 shows statistical significance and demonstrated that the shift of people's preferences to supra-functionality beyond economic value significantly induced the advancement of the Internet in Japan. This inducement increased as the Internet dependence increased.
All three analyses demonstrated the significant correlation between the advancement of the Internet and soft innovation resources or their subsequent, such as the self-propagating function, and, also, people's preferences shift to supra-functionality beyond economic value.
These results support the supposition that soft innovation resources could be considered as a condensate and crystal of the advancement of the Internet.
Given the co-evolution between these factors in the emerging innovation in the digital economy, as illustrated in Figs. 9 and 11, it is postulated that effective utilization of soft innovation resources would be critical for sustainable growth amidst mega competition in the digital economy.

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The Reversal Trend in ICT Leaders
(1) The Reversal Trend in GDP Growth Rate

(2) Factors Contributing to the Reversal
Aiming at elucidating the structural source of such a notable closing trend for these two digital leaders in recent years, Table 10 analyzes the contributors to the GDP growth rates in two leaders over the period from 2012-2017. Looking at Table 10, we note that, contrary to Singapore, Finland's recent GDP growth recovery can largely be attributed to its gross fixed capital formation, to which negative contribution in Singapore.
With such a notable contrasting observation, Fig. 16 compares the trend in the shares of gross service capital (centered on R&D) out of the gross fixed capital formation in both countries over a period from 2012-2017, as R&D is assumed to be a driver to such recovery. Fig. 16 reveals that while Singapore demonstrates stable or increasing share, as anticipated, Finland has been shifting to less dependence on gross service capital in M A N U S C R I P T

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its gross fixed capital formation, contrary to Singapore's performance. In light of the primal contribution of gross fixed capital formation (GC) to the recent notable resurgence of Finland's GDP growth and also the contrasting trend in dependence on gross service capital (GSC) in GC between the two leaders, contributors to GC were analyzed by dividing GC into GSC and gross tangible capital (GTC). Here, GSC is represented by intellectual property products (IPP) in the national accounts, encompassing R&D, software and databases, mineral exploration and evaluation, and entertainment, literary or artistic originals. GTC includes tangible assets, such as machinery, vehicles, plant, dwellings, buildings, and land improvements. Table 11 summarizes the comparison of GC growth contributors in Finland and Singapore over a period from 2012-2017 (see the details of the decomposition analysis in Table A2 in Appendix 1).   (3) Contrast in R&D Dependence Inspired by the above observation that Finland's recent notable resurgence in GDP growth has depended on GTC's increase while GSC demonstrates a negative increase against anticipation, the trend in the R&D dependence of the two leaders was reviewed.  Sources: Same as Table 10.
Both leaders experienced a sharp decrease in their R&D investment both in government and business enterprises after the Lehman shock in 2008. However, contrary to Singapore's prompt recovery from 2010 under strong government initiative, Finland suffered longer stagnation both in government and business enterprises.
In Finland, while business-funding R&D started to decline due to the Lehman shock in 2008, government funding of R&D continued to grow. However, it switched from an expansionary to a contractionary policy after 2010, which exacerbated a massive decline in business-funded R&D (Hutchenreiter et al., 2017).
Consequently, R&D intensity has shown a decreasing trend in Finland from 2010, as demonstrated in Fig. 19, which compares the trend in R&D intensity between Finland and Singapore over a period from 1995-2016. This trend also demonstrates the contrast between the two digital leaders after the Lehman shock in 2008. Such a contrast seems to be a consequence of the development trajectory management of the trade-off of R&D investment and productivity decline, as reviewed in Section 2. Sources: Same as Table 10.
Given the increasing burden of ICT R&D investment (The Economist, 2018), which shares the majority of GSC while its productivity has been declining as a consequence of the two-faced nature of ICT, Finland, based on neo-open innovation, appears to have transformed its trajectory into the utilization of the hybrid role of soft innovation resources, as reviewed in Section 4. Its growth of GTC while depending less on GSC prompts a hypothetical view that given its effective utilization of soft innovation resources, as reviewed in Section 4.1, these resources are substituted for GSC and remove structural impediments to GTC growth, leading to its significant contribution to GC growth, which is a primal contributor to the GDP resurgence in Finland.
The next Section attempts to demonstrate this hypothetical view.

The Dynamism Enabling Finland's Resurgence
(1) Dynamism Analysis in the preceding Section prompted a hypothetical view that soft innovation resources could substitute for GSC that spilled-over to GTC and removed its structural impediments in growth. Fig. 20 illustrates this hypothetical dynamism. (2) Demonstration By means of an empirical analysis of Finland's development trajectory, utilizing its national accounting statistics over a period from 1995-2018, this hypothetical dynamism was demonstrated.

1) Institutional Change in Finland
Critical institutional change in Finland in the period can be identified in Table 12.

2) Soft Innovation Resources Substituting for R&D
With the understanding that soft innovation resources can be considered as a crystal of the Internet, as demonstrated in Section 4.2, Table 13 demonstrates the soft innovation resources substituted for GSC, centered on R&D, after 2010.   Table 13 The Correlation between the I/R Ratio and Relative Price in Finland  I: Internet (soft innovation resources); R: R&D; P i , P j : prices of I and R (IPP price), respectively 6 .
The figures in parentheses indicate the t-statistics: all are significant at the 1% level. Table 14 demonstrates that soft innovation resources (by using the Internet as a proxy) impacted the GTC share increase out of GC after 2010, with particularly significance after 2016, which corresponds to the soft innovation resources substitution for GSC. All of these analyses demonstrated that soft innovation resources were substituted for GSC spilled-over to GTC and removed the structural impediments impeding its growth; thereby, GTC contributed to GC growth, leading to Finland's GDP growth resurgence.

The Contribution of Soft Innovation Resources to the Resurgence
Analyses in the preceding Sections suggested the following dynamism of soft innovation resources (SIRs) in removing the structural impediments in GTC growth, which contributed to the resurgence of the Finnish GDP growth.
(i) The Advancement of the Internet aroused and induced SIRs (Fig. 1).
(ii) The Competitiveness Pact spurred the effective utilization of SIRs (see below).
(iv) Through the substitution process, SIRs spilled-over and were incorporated into GTC via MFP (Table 14).
(v) MFP induced GTC by removing structural impediments to its growth (Table 14).
(vii) GDP growth, in turn, increased MFP, leading to a virtuous cycle.

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT
(viii) In addition, GDP resurgence instilled confidence in the Competitiveness Pact.
The effective utilization of SIRs, as well as dynamism with its substitution for GSC and incorporation of spilled-over SIRs in GTC, depends largely on the co-evolutionary acclimatization capacity of the nation (Chew et al., 2010).
Activation of this dynamism can be attributed to Finland's institutional elasticity and spurring by the Competitiveness Pact.
In light of long lasting stagnation and the understanding of the significant role of trust, after years of negotiations and strikes, Finland's government convinced the country's unions in June 2016 to accept a reform pact, the Competitiveness Pact. This historic and ambitious decision in June 2016 to shift away from centralized wage-setting towards company-level labor deals can largely be appreciated as a consequence of the effective utilization of SIRs, particularly of trust (Watanabe et al., 2016c). People's non-pessimistic mood in response to actual economic evidence has increased confidence in the Pact, as illustrated in Fig. 21, and aroused the nation's latent ability for sophisticated co-evolutionary acclimatization.
The full-fledged effects of the Competitiveness Pact should be expected; hence, further careful assessment should be indispensable. Some noteworthy signals to activate SIRs for removing structural impediments to GTC increase can be observed, and the effects of SIRs spillover have become a reality, as demonstrated in Fig. 21.

Conclusion
In light of a critical dilemma between R&D expansion and productivity decline, which global ICT leaders have been confronting due to the two-faced nature of ICT, dynamism resulting in such a dilemma and countermeasures against it were analyzed.
On the basis of an empirical analysis, focusing on forefront endeavors to this dilemma of global ICT leaders, their transformative direction into a disruptive business model was investigated.
Noteworthy findings included: (i) Transformation into a disruptive business model that creates supra-functionality beyond an economic value that satisfies people's preferences shift is a key direction.
(ii) For that, arousing and activating the self-propagating function indigenous to ICT and inducing a new functionality play a decisive role.
(iii) Soft innovation resources play a significant role in arousing and activating the latent self-propagating function.
(iv) Thus, neo open innovation that harnesses soft innovation resources can be a solution to this critical question.
(v) It depends largely on the assimilation capacity, which identifies, explores, and utilizes soft innovation resources and, then, absorbs and assimilates them into the whole value chain of production, diffusion, and consumption. (vii) This success can be attributed to the substitution of soft innovation resources for gross service capital, center on R&D, which spilled-over to gross tangible capital and removed the structural impediments to its growth.
These findings give rise to the following insightful suggestions for sustainable growth in the digital economy that incorporates a two-faced nature: (i) Neo open innovation should be sought on a priority basis.
(ii) The development of assimilation capacity should be endeavored.
(iii) Further exploration and utilization of soft innovation resources should be encouraged.
(iv) New concepts of R&D investment in the aforementioned transformation should be conceptualized.
(v) Similar dynamism, such as gross capital to export-driven growth, should be sought.
This analysis provides new insights for exploring a practical solution to the dilemma between R&D expansion and productivity decline in the digital economy.

Appendix 2 Trends in the People's Preferences
where I g : gross ICT stock = I (ICT stock) +J (internet dependence); X: other production factors.
I g embodies into X in an IoT society as follows: X = F(I g ) lnX = p x + r x lnI g where p x and r x : coefficients.
This demonstrates that V is governed by I g under the above circumstances.
As the Internet permeates into ICT in general, I g increases proportional to gross R&D represented by gross R&D expenditure (see Note 1).
where R j : R&D related to the Internet, and R i : R&D related to other ICT; ρ: rate of obsolescence of ICT, and g: R&D growth rate at initial stage. Substituting equation (5) for Ig in equation (4): where α ' = αβ ln( ρ + g ).
Thus, digital value is governed by gross R&D in an IoT society.
Given the logistic growth nature of ICT, V can be developed by an R-driven logistic growth function.  In particular innovation which creates new carrying capacity N(R) during the process of diffusion, equation (7) is developed as follows: Equation (12) As far as the development trajectory depends on SLG trajectory, its digital value (& R ) saturates with upper limit depicted by fixed N without self-propagating function, once the trajectory shifts to LGDCC, it can continue to increase supported by self-propagating function and led by dynamically enhancing upper limit + E . Therefore, the magnitude of self-propagating function

Note 3 Assessment of self-propagating function
As reviewed in Section 2.2, ICT incorporates self-propagating potential. This potential can be measured by equation (14) which is governed by the growth rate and the level of development trajectory (V L (R)). This level in LGDCC is identified by the third term of the denominator of equation (13). This term constitutes SLG function in which a coefficient a k plays a significant role in determining the initial level and velocity of this function.