Identifying the Dynamics of Intangible Resources for Industry 4.0 Adoption Process

Industry 4.0 is a socioeconomic phenomenon that affects all industries, transforming not only products, processes, and services, but also business models, organizational structures, and strategies, placing human beings at the center of this digital transformation. Researchers have already demonstrated the importance of intangible resources in the Industry 4.0 adoption process. Nevertheless, there is still a gap in empirical research on how these factors evolve during the process. Therefore, the main objective of this study is to identify how these factors influence each other across different Industry 4.0 maturity levels. To achieve this goal, a qualitative approach was used with multiple case studies comparing responses from companies at higher Industry 4.0 maturity levels and contrasting them with the responses from companies at lower levels, distilling aggregate dimensions through an inductive coding procedure. Experts evaluated the results to find relations between the aggregate dimensions, their evolution and influence on each other. As a result, a conceptual framework was developed that demonstrates the dynamics of intangible factors that could be used by any company to nurture its own Intellectual Capital as a groundwork for the adoption of Industry 4.0. Among these dynamics, the central role of engaged leaders was highlighted in developing structural capital factors. Future studies should conduct interviews with more companies from other industrial sectors as well as on the implementation and management of Intellectual Capital in manufacturing companies to assess the applicability of the proposed conceptual framework.

tors, where traditional products are replaced by similar digital 23 ones, or at least equipped with digital functionalities [2]. The associate editor coordinating the review of this manuscript and approving it for publication was Justin Zhang . advanced production systems with the aim of increasing 30 the productivity and efficiency of the national industry [3]. 31 Industry 4.0 integrates a stream of research concerned with 32 industrial processes which has paid significant attention to 33 smart manufacturing and its base technologies, including the 34 Internet of Things (IoT), cloud, big data, analytics, and arti-35 ficial intelligence [5]. Researchers and practitioners believe 36 that Industry 4.0 empowers companies to increase their oper-37 ational efficiency and innovate faster [6], [7]. In this sense, the 38 ultimate goal is to become a learning, agile company capable 39 of continuous adaptation to a changing environment [8], [9]. 40 However, addressing the developments associated with the 41 Fourth Industrial Revolution from a technological perspec-42 tive is insufficient. Companies also need to transform their 43 This paper is divided into five sections. First, we concep-100 tualize intangible resources within the scope of Industry 4.0. 101 Section 3 presents the methodology employed to identify 102 the intangible factors in companies with higher Industry 103 4.0 adoption levels and how they influence each other. 104 Section 4 presents and discusses the results and the proposed 105 conceptual framework of this study. In section 5, we conclude 106 with the findings and implications of this study. In the modern age, organizations find themselves in complex 115 environments of ever-increasing dynamism and uncertainty. 116 Developing and acquiring tacit resources and knowledge is 117 vital for the success of an organization [17], [19]. A mod-118 ern organization is composed of a fluid structure, strategic 119 partnering, empowered employees, groupware, multimedia 120 network marketing, and vital reservoirs of human intellectual 121 resources [12]. These factors are hidden to investors. One 122 emerging paradox is that investing in the areas of human 123 capital and IT leads to a short-term deterioration of profits, 124 reducing the value of the balance sheet, and consequently the 125 book value of the organization. To put it briefly, the paradox is 126 that the more an organization invests in knowledge upgrading 127 and IT, the lower its value [20]. 128 One way to appreciate the role of IC is metaphorical, 129 by picturing a company as a living organism, as a tree [12]. 130 Organizational charts, annual reports, quarterly statements, 131 company brochures, and other documents would be its trunks, 132 branches, and leaves. However, assuming these to be the 133 entire tree, because they represent everything visible, is obvi-134 ously a mistake. Half of a tree -or sometimes more -is 135 underground, in its root system. Instead of studying its fruits 136 and leaves, which provide evidence of how healthy the tree 137 is today, understanding what is going on in its roots is a far 138 more effective way to learn how healthy the tree will be in 139 the years to come. This points to the importance of IC -the 140 study of a company's roots, the measurement of the hidden 141 and dynamic factors that form the basis of a company's 142 tangible assets. According to the collective research project 143 ''Intellectual Capital Statement -Made in Europe'': human 144 capital, structural capital, and relational capital [21], these 145 hidden factors typically comprise three dimensions:  [13], [14]. It sheds light on the role 210 of leaders in strategy development, supporting initiatives for 211 new technology adoption and for a decentralized decision-212 making process [13], [15].

213
Technical subsystem: This subsystem comprises elements 214 of the production operation and how it is performed [13], 215 [30]. This dimension highlights the importance of small pilot 216 projects with limited budgets, focusing on testing and under-217 standing the cause-effect relationship between new technolo-218 gies, innovative capacities, and performance gains in the 219 manufacturing process [13], [14], noting the importance of 220 lean manufacturing tools in a 'chicken or egg' dilemma, more 221 mature companies have implemented lean tools as the basis 222 for digitization [13].

223
Work organization subsystem: Work organization con-224 siders the way in which work is designed in a firm, com-225 prising aspects such as rules, operational procedures, work 226 instructions, information flow, team organization, employee 227 shifts, training for operation, task planning and integration, 228 and other aspects of the work to be conducted [13], [30]. 229 It emphasizes the role of project teams in new technology 230 adoption, pilot projects, strategy development, and engage-231 ment with the decision-making process [13], [14]. It also 232 highlights the importance of corporate culture, including 233 aspects such as openness to the new, acceptance of fail-234 ures, open communication, and encouragement of creative 235 activity [14], [15].

236
Environmental subsystem: The environmental subsys-237 tem can be viewed through two lenses: external and internal 238 environmental factors [13], [30]. Among the internal factors, 239 the role of knowledge management is highlighted through the 240 ideation process, best-practice sharing, and cross-functional 241 communication, enhancing the exchange of experiences [13], 242 [14], [15]. Regarding external environmental factors, the role 243 VOLUME 10, 2022 The maturity level of a company was obtained from the    on observations of the SENAI consultant. Consequently, the 297 reliability of this study was strengthened [35].  These companies were contacted by e-mail, and then by 308 video calls, to explain the goals of this research, as well as 309 to discuss their interest in participating. All contacted com-310 panies initially accepted to participate as part of this study, 311 and interviews were scheduled. As a result, eight companies 312 were selected to respond to a semi-structured questionnaire, 313 as presented in Table 3. Amongst them, one is at a very 314 low maturity level while five represent the highest Industry 315 4.0 maturity level. The names of the companies were kept 316 confidential. To identify the hidden dynamic factors (i.e., the intangible 319 factors that influence companies the most toward achieving 320 higher Industry 4.0 maturity levels) and how they influence 321 each other across different maturity levels, semi-structured 322 interviews were used as primary data collection method. 323 This kind of interview allows for structured data collec-324 tion while maintaining an adequate and necessary level of 325  was tested with two manufacturing companies for fine tuning 331 before the main interviews were conducted (see Table 2 for 332 the interview script). Since these constituted preparation work

358
The coding procedure started with a first-order analysis, 359 contrasting responses from companies at higher maturity 360 levels in Industry 4.0 with the responses from companies 361 at lower maturity levels. The four sociotechnical dimen-362 sions previously presented in this study were considered 363 as a ground concept model [13]. The first aggregation 364 was created following the terms reliably reported by the 365 interviewees. Next, these categories were synthesized into 366 second-order themes to further converge the similarities and 367 contrast differences between them. Subsequently, the emerg-368 ing second-order themes were distilled into aggregate dimen-369 sions. Obtaining a set of emergent categories related to 370 second-order themes and aggregate dimensions provides a 371 basis for constructing a data structure, which is a key com-372 ponent for demonstrating rigor in qualitative research [14], 373 [37]. This entire process was conducted by a research team 374 comprising the six authors of this paper as experts on both 375 themes: Industry 4.0 and Intellectual Capital management, 376 which certainly increases the validity and objectivity of the 377 coding procedure [38]. 378 Finally, the experts involved in this research developed a 379 relationship between all the aggregate dimensions, revealing 380 how each factor influences the others toward higher levels 381 of Industry 4.0 maturity. The authors also suggested relation-382 ships between the aggregate dimensions and the list of harmo-383 nized IC factors presented in Table 1. These suggestions were 384 made according to their previous experience in assessing and 385 implementing intellectual capital statements in more than 386 Table 4, are the most likely to be 389 nurtured to develop the corresponding aggregate dimension. 390 However, practitioners and researchers are encouraged to 391 begin replicating this study from these suggestions but also 392 to expand to other IC factors as well.

394
The results based on the semi-structured interviews distilled 395 eight aggregate dimensions and thirteen second-order themes 396 that were related to the list of harmonized IC factors to present 397 a suggested correlation between them. This data structure, 398 presented in Table 4, was used to suggest a conceptual frame-399 work summarizing how the aggregate dimensions interact 400 with each other to achieve higher Industry 4.0 maturity levels. 401

402
The first distilled dimension was distilled from the social 403 subsystem dimension, as the interviewees highlighted that 404 successful adoption of Industry 4.0 requires systematic 405 employee training, not only for technical re-skilling, for 406 instance, in areas such as automation and data science, but 407 also for the development of socioemotional skills like col-408 laboration, communication, and leadership problem-solving 409 skills. It was possible to observe that employees feel more 410 confident when they can share ideas, lessons learned, and 411 aspects related to initiatives to implement new technologies. 412 They understand that these initiatives could be an opportunity 413 to move forward in their careers rather than a threat. They 414 VOLUME 10, 2022 The third distilled dimension was identified from the work 471 organization subsystem dimension, considering that the most 472 mature companies presented clear and well-defined strate-473 gies for the adoption of Industry 4.0, which were mostly 474 to improve process efficiency and quality levels. It was 475 possible to identify that these companies had dedicated 476 cross-functional teams that met frequently, with clear objec-477 tives to be achieved. They had well-defined action plans and 478 KPI boards that communicated to stakeholders. Ideas and 479 lessons learned were shared among them and with the board 480 as part of the decision-making process. The manufacturing 481 staff often requested new ideas as a source for the devel-482 opment of action plans. Good practices were shared across 483 the company and implemented as standardized processes or 484 procedures. Problems were discussed openly with the support 485 of cross-functional representatives and external experts.

486
In contrast, the least mature companies were unable to 487 present a strategy for Industry 4.0 adoption. They showed 488 great interest and curiosity on the topic but lacked a clear 489 vision of the expected cause-effect relationship of its imple-490 mentation on the company's strategy. In addition, they were 491 not able to present a clear decision-making process. This 492 was mainly performed by the executive director but with no 493 clear criteria or requirements. Notably, there are no dedicated 494 teams, action plans, or KPIs for new initiatives. Industry 4.0 495 is often a theme studied by only one or two employees. 496 However, there were complaints about barriers such as lack 497 of trustful information, channels to share new ideas, and 498 available resources. Most of the times, initiatives are only 499 good ideas that never come to be entirely implemented.

500
Thus, it is suggested that ''strategy & governance'' is an 501 important aggregate dimension for manufacturing companies 502 to achieve greater Industry 4.0 maturity levels, as it was 503 observed that it has positive effects on the following aggregate 504 dimensions: (4) Bottom-up approach, (5) Learn by doing and 505 (6) Knowledge sharing. The authors of this study also suggest 506 that the development of this aggregate dimension could be 507 achieved by nurturing the following IC factors: leadership 508 ability (HC4), internal cooperation and knowledge transfer 509 (SC1), management instruments (SC2), and IT and explicit 510 knowledge (SC3).

512
The fourth aggregate dimension was distilled, once again, 513 from the social subsystem dimension, as it was observed 514 that initiatives to collect, analyze, and implement new ideas, 515 mostly related to manufacturing process improvement, were 516 normally taken in companies at higher maturity levels. 517 According to the interviewees, employees were encouraged 518 to share their ideas and were rewarded when these ideas were 519 successfully implemented. These ideas are often aggregated 520 into the company's action plan to implement Industry 4.0, 521 which is connected through the governance and leaders of 522 the interviewed companies. These initiatives are considered 523 pilots, so the results are measured to verify the causes and 524   Consequently, it is suggested that ''learn by doing'' is an 594 important aggregate dimension for manufacturing companies 595 to achieve greater Industry 4.0 maturity levels, as it was 596 observed that it has positive effects on the following aggregate 597 dimensions: (6) Knowledge sharing and (8) Go and see. The 598 authors of this study also suggest that the development of 599 this aggregate dimension could be achieved by nurturing 600 the following IC factors: internal cooperation and knowl-601 edge transfer (SC1), management instruments (SC2), prod-602 uct innovation (SC4), process optimization and innovation 603 (SC5), customer relationships (RC1), supplier relationships 604 (RC2), and relationships with cooperation partners (RC5).

606
The sixth aggregate dimension was distilled from the envi-607 ronmental subsystem as an internal factor. According to the 608 interviewees, companies with higher Industry 4.0 maturity 609 levels have well-established knowledge processes and sys-610 tems that support employees in sharing their learning across 611 departments. Additionally, those companies presented flatter 612 hierarchies, ''war rooms'' for initiatives, with KPI boards and 613 updated information. In addition, working stations are placed 614 without separation, promoting an open culture where peo-615 ple integrate to exchange ideas and solve problems quickly. 616 As one representative said, ''nobody does anything alone.'' 617 Thus, knowledge and decision-making processes are dis-618 tributed in the company with the support of their governance 619 and leaders.

620
Companies with lower maturity levels presented more ver-621 tical hierarchical structures, with knowledge and decisions 622 concentrated on fewer individuals. Companies often do not 623 have a process for registering and sharing information that 624 could be useful in improving their business and manufactur-625 ing processes. As knowledge is not shared across the com-626 pany, only a few key persons are able to connect with external 627 partners such as suppliers, customers, and RTOs which could 628 provide new insights to improve the manufacturing process. 629 Thus, it is suggested that ''knowledge sharing'' is an 630 important aggregate dimension for manufacturing companies 631 in order to achieve greater Industry 4.0 maturity levels, as it 632 was observed that it has positive effects on the following 633 aggregate dimensions: (4) Bottom-up approach and (5) Learn 634 by doing. The authors of this study also suggest that the 635 development of this aggregate dimension could be achieved 636 by nurturing the following IC factors: internal cooperation 637 and knowledge transfer (SC1), IT and explicit knowledge 638 (SC3), corporate culture (SC6), social competence (HC2), 639 and leadership ability (HC4). companies, with companies located in the same industrial 703 district, sometimes even competitors. They are able to create 704 communities of practices, visit each other and meet often 705 to share common pains, learn from each other's pilots and 706 share their good and bad experiences with technology suppli-707 ers. These transformation networks are useful for exploring 708 new possibilities connected with the bottom-up approach and 709 employee empowerment. It was also observed that shared 710 learning made innovation pilots more efficient and improved 711 their outcomes.

712
However, companies at lower maturity levels have poor or 713 no connections with customers, suppliers, and other partners. 714 They are usually isolated from the communities of companies 715 that learn from each other. Consequently, they do not have 716 access to reliable information from suppliers, and do not 717 collaborate with customers. This makes it even harder for 718 employees to suggest new ideas because they have never seen 719 them at work before. In this sense, they are less empowered 720 to support their companies.

721
It is thus suggested that ''go and see'' is an important 722 aggregate dimension for manufacturing companies to achieve 723 greater Industry 4.0 maturity levels, as it has shown positive 724 effects on the following aggregate dimensions: (4) Bottom-725 up approach, (6) Knowledge sharing, (5) Learn by doing, 726 and (1) Empowered employees. The authors of this study 727 also suggest that the development of this aggregate dimension 728 could be achieved by nurturing the following IC factors: 729 customer relationships (RC1), supplier relationships (RC2), 730 public relationships (RC3), and relationships to cooperation 731 partners (RC5).

733
Once this research was able to identify the aggregate dimen-734 sions distilled from the semi-structured interviews, observing 735 how they evolved from lower to higher levels of Industry 4.0 736 implementation, and how they influenced each other, it was 737 possible to develop a conceptual framework representing 738 these dynamics. The main goal of this concept development 739 is to illustrate the importance of such hidden dynamic fac-740 tors to support manufacturing companies in developing their 741 own action plans for adopting new technologies and also to 742 nurturing their intangible assets.

743
The figure of a wheel was suggested to account for the fact 744 that it was not possible to identify where a company should 745 start, much like in ''the chicken or the egg'' dilemma. This 746 proposal suggests that the aggregate dimension (7) Productiv-747 ity and quality tools as groundwork should be a priority, so it 748 is placed at the beginning of the framework. In the central part 749 of the wheel, appears the aggregate dimension (2) Engaged 750 leaders, as it has a positive impact on three other dimensions  for Industry 4.0 implementation, as information is highly 791 valuable in future value creation. This study also sheds light 792 on the importance of generating experiences and lessons 793 learned within a company [14]. The researchers observed that 794 some companies employed small projects, using cost-benefit 795 analysis in their companies, learning quickly from mistakes, 796 and testing new approaches to develop and offer effective 797 solutions. In this sense, concrete information about costs and 798 potential was obtained from the pilot projects. In addition, 799 it was possible to highlight the role of lean manufacturing 800 [14], which benefits companies not only in terms of orga-801 nizational agility but also in fostering the development of a 802 smooth data flow based on interconnected systems. There-803 fore, it can be said that SC is the backbone of companies at 804 higher Industry 4.0 maturity levels [27]. This observation is 805 in line with previous studies that emphasize the importance 806 of the work organization and technical subsystems [12], [13], 807 [14] based on a socio-technical perspective [30] as ground-808 work for the Industry 4.0 adoption process.

809
Another important aspect is that relational capital fac-810 tors make a critical contribution for companies at higher 811 Industry 4.0 maturity levels. The aggregate dimension (8) 812 ''go and see'' highlighted the importance of connecting with 813 customers and suppliers, maintaining a collaborative relation-814 ship with them, and enabling firms to expand their horizons 815 and absorptive capacity [7]. This fundamentally revolution-816 izes the way organizations interact with their customers and 817 suppliers. Connecting with the end customers during all 818 stages of the value-added process offers companies the oppor-819 tunity to develop new, strongly service-oriented business 820 models [14]. Additionally, close collaboration between uni-  companies, converting HC into SC, which is the backbone of 876 companies at higher Industry 4.0 maturity levels. Moreover, 877 it was observed that RC factors play a key role in accelerating 878 the adoption of Industry 4.0.

879
From the sociotechnical perspective, the observed dynam-880 ics suggested that the social subsystem plays a key role 881 in developing the work organization subsystem dimension, 882 accelerated by environmental subsystem factors. Finally, 883 technical subsystem factors, such as lean manufactur-884 ing, were found to be an important groundwork for the 885 Industry 4.0 adoption process. 886 Overall, this research suggests that, by nurturing the IC 887 factors related to the aggregate dimensions, a company may 888 achieve greater Industry 4.0 maturity levels and thus become 889 a learning, agile company capable of continuous and dynamic 890 adaptation to a changing environment.

892
The results of this study have several implications. First, 893 in terms of public policies for small companies, SMEs corre-894 spond to 82.6% of the companies at the lowest maturity level 895 within the scope of this research. Therefore, public policies 896 should be developed to encourage the training of SME leaders 897 in IC management methods.  As only eight of the 353 companies in our initial scope were 912 analyzed in-depth, this research presents limited empirical 913 evidence. In addition, the data analyzed are related to one 914 industry sector only. An additional limitation is the fact that 915 only one executive from each company was interviewed. 916 To broaden this view, future research could analyze data 917 from a larger number of manufacturing companies in differ-918 ent industrial segments. Besides, future studies should con-919 sider interviewing more experts from the same company in 920 order to achieve a more thorough picture of the dynamics of 921 sociotechnical factors. Additionally, this study is focused on 922 Brazilian companies. Since Industry 4.0 and IC management 923 also play an important role in many other economies, an inter-924 national perspective could add interesting perspectives to this 925 stream of work.

926
Another aspect to be explored is that some aggregate 927 dimensions revealed by this study could present different 928 dynamics in SMEs as compared to large companies [44]. 929