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Pilipczuk, O. Transformation of Business Process Manager Profession. Encyclopedia. Available online: https://encyclopedia.pub/entry/17999 (accessed on 16 November 2024).
Pilipczuk O. Transformation of Business Process Manager Profession. Encyclopedia. Available at: https://encyclopedia.pub/entry/17999. Accessed November 16, 2024.
Pilipczuk, Olga. "Transformation of Business Process Manager Profession" Encyclopedia, https://encyclopedia.pub/entry/17999 (accessed November 16, 2024).
Pilipczuk, O. (2022, January 10). Transformation of Business Process Manager Profession. In Encyclopedia. https://encyclopedia.pub/entry/17999
Pilipczuk, Olga. "Transformation of Business Process Manager Profession." Encyclopedia. Web. 10 January, 2022.
Transformation of Business Process Manager Profession
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The increasing role of emerging technologies, such as big data, the Internet of Things, artificial intelligence (AI), cognitive technologies, cloud computing, and mobile technologies, is essential to the business process manager profession’s sustainable development.  Nevertheless, these technologies could involve new challenges in labor markets.

business process management labor market digital technologies sustainable development

1. Introduction

Even before the COVID-19 pandemic, it has been argued that careers have been changing; they are becoming more complex and unpredictable. Most of the contemporary scientific papers studying careers emphasize their changing nature [1]. On the other hand, the COVID-19 pandemic is increasing the importance of the regulation of and stabilization in today’s labor markets.
Currently, the global economy is in freefall, millions of people have lost their jobs, livelihoods have been undermined, primary healthcare in most countries is in a critical condition, and mental health and domestic abuse are at crisis levels [2]. Sustainable careers have a significant influence on labor markets.
The grand challenges that humanity faces—poverty, inequality, hunger, conflict, climate change, deforestation, and pandemics, among others—hinder sustainable development [3]. Georg Scherer and Christian Voegtlin state that fundamental changes in behavior, as well as in the modes and processes of production and business, are occurring more generally.
Moreover, Joel Baum and Heather Haveman argued that “the digital revolution has expanded the capacity of businesses to disperse their activities geographically and to design and deliver goods and services in novel ways”. Consequently, these changes have influenced organizational strategies, structures, and processes [4].
This inspired the author to set the question of whether these changes are actually visible in the labor market. In other words, the purpose of this research was to discover the advances in business process management that were affected by emerging technologies.
The impact of digital technologies on organizations is one of the trending topics in careers research [5]. The impact of emerging technologies on organizations and professional work has been significant and often brings about new challenges. It has been proven that digitized processes can change incrementally over time [6].
As a result, managers are charged with new tasks and responsibilities and exert intensified managerial control. The monitoring and analysis of new tasks and the competencies associated with them are of great importance to current sustainable and smart organizations.
According to Jan Mendling, Brian Pentland, and Jan Recker, much research on digital innovation and process management has been conducted by different communities [7]. The authors argue that a synthesis is required to connect these separate streams of research.
In [8], the authors argue that the recent emergence of technologies such as machine learning, robotic process automation, and the blockchain will reduce the influence of human factors on business process management.
The research that has expanded the knowledge of professional role identity by showing the value of an in-depth analysis of the content indicates that the missing link between the interpretation of technology and institutional logics is a guiding principle for professions [9].
Finally, a report on the BPM Institute from Forrester Research highlights the importance of improving BPM skills [10]. The company argued that the lack of sufficient business process skills continues to hamper the progress and dynamics of enterprise-wide business process management initiatives, leading to continued over-reliance on professional BPM software vendor services and system integrator resources [10]. They also underlined the current presence of a skills gap and argued that this fact has delayed improvements in business processes across enterprises.
To address the abovementioned gaps, this study aimed to answer the research question of how the business process manager profession in Poland is being affected by the “iBPM” concept and related technologies.
Taking into consideration the suggestions made in the work of Brock, Leblebici, and Muzio [11], the research was built upon an analysis of scientific and organizational responses.

2. Carriers’ Development

The literature review concentrated on the identification of the tendencies and dimensions of the impact of emerging technologies on the business process manager profession.
At the beginning, the perspective of sustainable carries skills model creation was studied. In “Handbook of Career Theory”, authors define the career from different perspectives, referring to Becker, Doeringer, and Piore [12]. From their suggestion, from an economic perspective, a career should be treated as a response to market forces. Therefore, the research presented in this paper was based on the abovementioned perspective.
Drawing on the degrowth literature in sustainable careers, several papers are concentrated on sustainable careers analysis. The paper by De Vos et al. (2020) “aims to move the research field on sustainable careers forward by building conceptual clarity about what a sustainable career means and delineating what distinguishes sustainable from non-sustainable careers, thereby providing key indicators of a sustainable career” [13]. In the work of Ellen Kossek and Ariane Ollier-Malaterre (2020), the authors focus their work on the implementation of sustainable reduced load work and shed light on key issues [14].

3. Sustainable BPM

The concept of sustainability can be found not only in sustainable carriers, but also in ecological economics, sociology, and political ecology. In their work [15], the authors identify key principles relevant to processes of organizing for a more just and environmentally sustainable future [15]. Consequently, one of the most important directions of change are green initiatives towards sustainability development, such as green bpm, green finance, green cities, green information systems [16][17][18][19][20][21], etc. According to von Brocke, Seidel, and Recker (2012), green BPM is the pathway to sustainable enterprise [20]. Green Business Process Management focuses on the ecological impact of business processes and related technological development [17][18]. Currently, it is an emerging field, and different approaches exist to realize it. It is also associated with sustainable BPM.
In the paper by Couckuyt and Van Looy, the authors describe the literature analysis that revealed the connection between Green BPM and the sustainability development concept [22]. Their results describe Green BPM as an approach for environmentally sustainable organizations.
Other research treated sustainability in BPM as a more extended concept [23][24][25][26][27]. Therefore, based on Seidels et al.’s work (2010), the authors propose to extend the “devil’s quadrangle” with the factor “sustainability” [20].
Similarly, Schormann et al. state that previous research on sustainable BPM and green BPM seeks to consider ecological concerns in addition to economic obligations [28]. Social sustainability is mostly neglected in scientific research. "This deficiency hinders businesses from being guided on how to systematically consider social aspects such as fair and healthy working conditions. Accordingly, this study makes use of a process pattern-based approach to provide proven, general solutions for common problems referring to “social sustainability” [28]. Some authors viewed BPM as a tool for implementing the concept of sustainable development [29].
Another emerging direction is the direction of the concept which has been evaluated from intelligent organization to smart organization. The term “smart organization” is used for organizations that are knowledge-driven, technology-driven, internetworked, dynamically adaptive, learning, and agile [30]. A smart organization is also an organization that is safe, principle-driven, and value-focused. The term “smart organization” is closely related to the term “smart city”.
The relationship between professional associations, multinational corporations, international organizations (such as the EU, WTO, and OECD), and nation-states is in rapid transition [11]. Accordingly, the research results of the abovementioned organizations could be taken into consideration during the professions’ transformation analysis.
The development of networking and social media and the pandemic have had an impact on the way of working. The rise in remote working has resulted in the development of remote work skill models. The Workplaceless Remote Work Competency Model is a framework of essential competencies needed to succeed in remote work [31]. This model provides a holistic view of the competencies (attitudes, behaviors, knowledge, and skills) needed by distributed workers, team members, leaders, and executives. Change management, performance management, conflict management, team culture, communication management, remote leadership tools, stakeholder management, resource management, and innovation are all skills that a new remote leader should have [31].
A report by the McKinsey Global Institute highlights “how jobs based on human skills will be affected by AI and automation” [32]. The Accenture company, in its “Future Skills Pilot”, also states that artificial intelligence will force organizations to create more job pathways [33]. A million jobs may be changed by using machines by 2025. Due to these changes [33], one million new roles may emerge by 2025. It also highlighted the importance of eliminating bias in human work. Accenture also emphasizes the role of cross-industry collaboration and fostering culture change.
In the paper by Tarafdar, Beath, and Ross (2017), the authors highlight the importance of using cognitive technologies and provide an overview of enterprise cognitive computing applications [34]. They specifically identify opportunities for developing these applications and describe implementation challenges [34]. Their findings are based on a study of 51 application initiatives across a broad range of industries in different continents.
The OECD skills report focuses on other issues. It has been mentioned that high cognitive skills, social and emotional skills, and technological skills will be crucial for the next decade [35]. According to the OECD report, the greatest demand will be for computers and electronics knowledge areas, decision-making and judgment skills, systems evaluation, and system analysis. It presents the shortages (e.g., unsatisfied demand in the labor market for the analyzed dimension) [34].
Moreover, according to the OECD ranking, it is hard to find employees in Poland with the following competences related to managerial positions [35]:
  • Manufacturing and production: Understanding of the principles and facts relating to the manufacture, processing, storage, and distribution of manufactured and agricultural goods.
  • System Skills: Systems evaluation, systems analysis, judgment and decision-making developed capacities used to understand, monitor, and improve socio-technical systems.
  • Complex problem solving: The ability to solve novel, ill-defined problems in complex, real-world situations.
  • Knowledge of the practical application of engineering science and technology. This includes applying principles, techniques, procedures, and equipment to the design and production of various goods and services (mostly in computers and electronics).
  • Knowledge of principles and facts related to business administration and accounting, human and material resource management in organizations, sales and marketing, economics, and office information and organizing systems—was in excess.
The analysis of common tendencies allowed to highlight the main drivers for BPM transformation: sustainable carriers and development, green initiatives, increasing amounts of remote work and networking, demand for intelligent technologies, cognitive and emotional skills, and direction toward decision making rather than routine operations.

4. Changes in Business Process Management Concept

The BPM discipline continues to improve its value due to digital transformation [36]. However, most organizations have started or at least planned digital transformation initiatives [36]. The process of digital transformation is significantly influenced by internal embeddedness [37].
Kirchmer (2021) and Javidroozi et al. (2020) describe the challenges and factors associated with business process changes [38][39]. The study by Javidroozi et al. (2020) proposes a conceptual framework for addressing BPC challenges and their success factors, as well as supporting solution providers to develop solutions for effective and efficient BPC [39]. The authors also argue that “enterprise systems integration is necessary for today’s business environment to access real-time data and quickly respond to fluctuating market demand” [39]. According to Kirchmer (2021) and Binci, Belisari, and Appolloni, RPA, low code, change management, AI, stakeholder management, and digital governance technologies are currently in demand [38][40].
Furthermore, last year, agile methodology became popular. Experts demonstrated that in order to improve business processes, the values and principles of agile methods such as Scrum and various agile practices such as Kanban should be applied [41].
Moreover, emerging technologies implemented in BPM projects affect the results of BPM improvement. These technologies are smart production systems, big data analytics, cyber-physical systems, and the Internet of Things (IoT) [42]. In the paper by Battisti et al. (2020), the authors describe the role of integration between big data, risk management, and BPM and study the impact of this relationship on risk management efficiency and business process optimization [43].
Software solutions simplify the implementation of BPM and shift the responsibilities from people to technology [44]. Robotic process automation is helpful in improving enterprise efficiency and reducing costs [45]. Experts also argue that more research on the use of AI in organizations should be conducted. They also highlight that “a substantial change is required in how AI research is currently conducted in order to develop meaningful theory and to provide practitioners with sound advice” [46].
According to Leotta et al. [47] IoT can provide many opportunities for improving BPM initiatives. In particular, the IoT supports reducing the need to manually signify the completion of manual tasks by using sensor data. It also helps to acquire more accurate data, to reduce errors, and increase efficiency gains [48]. On the other hand, “it still involves challenges that require enhancements and extensions of the current state-of-the-art in BPM” [47].
Another emerging trend is the blockchain technology—“a shared ledger for parties collaborating on a process” [49]. The blockchain technology also significantly affects the human factor in BPM [50].
A growing trend toward partnership and network development of a “network society” was observed. Interdependence and horizontal relations have grown in importance due to the influence of information technologies [51]. Moreover, networking skills become a meaningful factor for career success. Social technologies have an impact on work planning and collaboration in BPM [51][52][53][54][55]. The research also noticed the effectiveness of cognitive technologies’ application to social networks and building cognitive social structures [56]. They can also help to improve the managers’ effectiveness in their leadership roles [57][58]. Scientists argue that the next step in networking concept development is processual communication networks [59].
It should be noted that there are several differences between men’s and women’s networks for career success. Meredith Woehler et al. in 2021 [60] proposed “guidance to organizations aiming to address inequality resulting from gender differences in network creation and utilization”.
Last year, a significant number of works on low-code and even zero-code technologies appeared [61], owing to more advanced technology analysis.
Analyzing the determinants from the management perspective, it was noticed that many authors proved that BPM is closely related to project management. Moreover, currently, boundaryless career theory has been the dominant career perspective in project management research [62].
BPM is also related to knowledge management [63]. Knowledge-intensive business processes are crucial for knowledge creation and have become a popular topic of scientific research [64]. Thus, in the paper [63], the authors propose a theoretical framework including a holistic model of BPM reversed knowledge pyramid [63]. It has also been confirmed that “knowledge-intensive processes require another approach to their ongoing improvement” [65]. Knowledge-intensive processes can be supported by process-based knowledge management systems [66]. The research on knowledge-intensive processes involves the BPM evolution toward an intelligent BPM concept.
BPM is also related to change management. In the work of Binci, Belisari, and Appolloni (2020), the authors outlined the perspective of a combination of BPM and change management [40]. The changes in BPM systems technology were caused by the changes in the nature of business processes, from routine processes to cognitive-intensive processes [67]. The core processes are still the same, but the changes in the business environment and emerging technologies have changed them significantly, in particular their functionality and complexity.
These changes lead to replacing workers doing routine and methodical tasks. Intelligent BPM systems support workers with high problem-solving skills, leadership, emotional intelligence, empathy, and creativity skills. Intelligent BPM systems offer solutions for human collaboration, such as integration with social media, mobile-enabled process tasks, deep analytics, and real-time decision management [68].
The BPM systems evolve from the simple form to advanced, complex systems. However, only a few papers on cognitive BPM systems have been published [67][69][70][71][72]. Mostly, these are conceptual works published by IBM managers. Thus, in the work of Hull and Nezhad, the components of the cognitive BPM (cBPM) concept are described [69]. Nezhad and Akkiraju (2015) also mentioned the pursuit of cognitive process management [70].
One of the core advantages of the application of intelligent technologies to BPM is that they enable change management inside their organization by enabling processes to improve themselves without human intervention [71].
Moreover, research suggests that the adoption of cognitive technologies in BPM will improve performance [72], especially machine learning (ML) algorithms [49]. Evermann et al. (2017) argue that these cognitive technologies can be used to generate views and processes customized for an end user [49].
Moreover, predicting business process behavior has become possible due to natural language processing [73]. For example, in the paper [73], the authors describe an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process [48].
Currently, intelligent BPM software leads the world market. Nevertheless, the era of cognitive business process management has been initiated. Cognitive BPM means cognitive decision support, cognitive process learning, cognitive interaction with processes and cognitive process enablement, and cognitive issues in BPM visualizations.
Several research studies concentrated on complex analysis of the determinants influencing the BPM concept transformation were conducted. Thus, Szelgowski and Lupeikiene (2020) define the current core capabilities of BPM as: real-time business analytics, content interaction management, human interaction management, business rule management, social-media, case management in dynamic processes, business pressure, changes in social culture, real-time decision making, and new technologies such as: low-code applications, mobility, cloud computing, or predictive analytics, process mining, social collaboration, robotic process automation, Blockchain, IoT, or ML/AI [74][75].
All the above-mentioned determinants have an impact on skills models and BPM certification program structure. The certification programs ought to represent the current demand in labor markets.

5. Certification Programs Analysis

The competence models are the basis for certification programs. Currently, there are several certification services, such as: ABPMP Certified Business Process Professional (CBPP), Business Process Management Certification from BPM Institute, Business Process Management Certification from AIIM, Business Process Management Certification from Bizagi, and Object Management Group (OMG) BPM Certification. For example, The ABPMP BPM Competency Model consider the knowledge, skills, competencies, and experience levels for a practitioner in Business Process Management. It provides a developmental path that aligns knowledge, skills, and competencies with the ABPMP BPM Certification Levels.
Most certification programs define the “business process leader” or “business process professional” status as the most coveted.
Some certification programs have already been supplemented with new certificates in emerging technologies skills as a result of BPM system transformation. Thus, the Dbiz institute offers certification with analytics and big data, statistics, OpEX tools, change management, agile methodology, data management, data visualization, date governance, DMN, RPA, Lean, and Six Sigma skills.

6. BPM Concept Development in Poland

It has been noticed for years that BPM concept implementation in Polish companies is problematic enough. In the paper [76], the authors present the findings of a process approach in Polish companies in 2007. They also describe consequential difficulties with the process management. Enterprises encounter consequential difficulties with process identification and process management [76]. As basic difficulties in process management were defined functional organization structure, and the problems in information flow between organizational divisions.
The authors also highlighted the fact that, in the majority of firms, employees actively participate in process realization, and they have the possibility of notifying improvements [76]. Polish firms are aware of the need to use tools for the measurement of process effectiveness.
Similarly, another problem identified was determining the level of process maturity in the surveyed municipal office [77]. The research results show that 178 (78.8%) of municipal offices did not undertake any projects related to the implementation of process management or took only selective action, not using comprehensive projects at any level of process maturity [77]. The undertakings most frequently implemented by municipalities are the identification of main processes, their optimization, and their description in the form of process maps or graphical diagrams. This procedure was performed by 26.1% of all surveyed municipia.
The author of work [78] defines, among others, the following project barriers in strategic management processes in Polish enterprises: information noises or lack of information and lack of qualified employees.
In paper [79], the authors present the results of the empirical procedure carried out in 2017 on a random sample of 350 organizations in Poland, answering questions regarding the desired role of an employee as a leader.
The empirical research was conducted in order to analyze the current state of the Polish labor market and the demand for BPM managers.

References

  1. Tracey, L. Professional employees and professional managers: Conflicting logics, hybridity, and restratification. J. Prof. Organ. 2020, 7, 101–115.
  2. Banerjee, S.; Jermier, J.; Peredo, A.; Perey, R.; Reichel, A. Theoretical perspectives on organizations and organizing in a post-growth era. Organization 2021, 28, 337–357.
  3. Scherer, A.; Voegtlin, C. Corporate governance for responsible innovation: Approaches to corporate governance and their implications for sustainable development. AMP 2020, 34, 182–208.
  4. Baum, J.; Haveman, H. Editors’ comments: The future of organizational theory. AMR 2020, 45, 268–272.
  5. Akkermans, J.; Kubasch, S. Trending topics in careers: A review and future research agenda. Career Dev. Int. 2017, 22, 586–627.
  6. Pentland, B.; Liu, P.; Kremser, W.; Hærem, T. The dynamics of drift in digitized processes. Mis Q. 2020, 44, 19–47.
  7. Mendling, J.; Pentland, B.; Recker, J. Building a complementary agenda for business process management and digital innovation. Eur. J. Inf. Syst. 2020, 29, 208–219.
  8. Mendling, J.; Decker, G.; Hull, R.; Reijers, H.A.; Weber, I. How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? Commun. Assoc. Inf. Syst. 2018, 43, 19.
  9. Goto, M. Collective professional role identity in the age of artificial intelligence. J. Prof. Organ. 2021, 8, 86–107.
  10. About Certification. Available online: https://www.bpminstitute.org/certification/about (accessed on 25 May 2021).
  11. Brock, D.; Leblebici, H.; Muzio, D. Understanding professionals and their workplaces: The mission of the journal of professions and organization. J. Prof. Organ. 2014, 1, 1–15.
  12. Artur, M.; Hall, D.; Lawrence, B. Generating the New Directions in Carrier Theory: The Case for Transdisciplinary Approach; Arthur, M.B., Hall, D.T., Lawrence, B.S., Eds.; Cambridge University Press: Cambridge, UK, 1989.
  13. De Vos, A.; Beatrice, I.J.M.; van der Heijden, A.J. Sustainable careers: Towards a conceptual model. J. Vocat. Behav. 2020, 117, 103196.
  14. Kossek, E.; Ollier-Malaterre, A. Desperately seeking sustainable careers: Redesigning professional jobs for the collaborative crafting of reduced-load work. J. Vocat. Behav. 2020, 117, 103315.
  15. Thornbush, M. Becoming smart. In Sustainable Urbanism in Digital Transitions: From Low Carbon to Smart Sustainable Cities; Sustainable Urbanism in Digital Transitions; Thornbush, M., Golubchikov, O., Eds.; Springer: Berlin/Heidelberg, Germany, 2020; pp. 35–47.
  16. Serhiy, L.; Pimonenko, T.; Bilan, Y.; Štreimikienė, D.; Mentel, G. Assessment of green investments’ impact on sustainable development: Linking gross domestic product per capita, greenhouse gas emissions and renewable energy. Energies 2019, 12, 3891.
  17. Couckuyt, D.; van Looy, A. An empirical study on Green BPM adoption: Contextual factors and performance. J. Softw. Evol. Process 2020, 33, e2299.
  18. Couckuyt, D.; van Looy, A. A systematic review of green business process management. Bus. Process Manag. J. 2020, 2, 421–446.
  19. Maciel, J. The core capabilities of green business process management—A literature review. In Proceedings of the International Conference on Wirtschatsinformatik, St. Gallen, Switzerland, 12–15 February 2017; University of Liechtenstein: Vaduz, Liechtenstein, 2017; pp. 1526–1537.
  20. Vom Brocke, J.; Seidel, S.; Recker, J. Green Business Process Management: Towards the Sustainable Enterprise; Springer: Berlin/Heidelberg, Germany, 2012.
  21. Corrocher, N.; Malerba, F.; Morrison, A. Technological regimes, patent growth, and catching-up in green technologies. Ind. Corp. Chang. 2021, 30, 1084–1107.
  22. Couckuyt, D.; van Looy, A. Green BPM as a business-oriented discipline: A systematic mapping study and research agenda. Sustainability 2019, 11, 4200.
  23. Seidel, S.; vom Brocke, J.; Recker, J. Call for action: Investigating the role of business process management in green IS. In Proceedings of the SIGGreen 2010 Workshop: An Introduction. Sprouts: Working Papers on Information Systems; Hasan, H., Dwyer, C., Eds.; Case Western Reserve University, Weatherhead School of Management: Cleveland, OH, USA, 2011; pp. 1–6.
  24. Levina, O. Exploring the Role of Business Process Management in Sustainability Initiatives. In Proceedings of the MCIS 2015 Proceedings, Samos, Greece, 2–5 October 2015; Available online: http://aisel.aisnet.org/mcis2015/35 (accessed on 5 September 2021).
  25. Lisovsky, A. Sustainable Development and Business Process Management, Strategic decisions and risk management. Strateg. Decis. Risk Manag. 2019, 10, 228–237.
  26. Opitz, N.; Krüp, H.; Kolbe, L.M. Environmentally sustainable business process management—Developing a green bpm readiness model. In Proceedings of the PACIS 2014: The 18th Pacific Asia Conference on Information Systems, Chengdu, China, 24–28 June 2014.
  27. Sokphea, Y.; Yoon, C.K. Sustainable business process management model for construction companies. In Proceedings of the 28th International Symposium on Automation and Robotics in Construction (ISARC 2011), Seoul, Korea, 29 June–2 July 2011; pp. 430–435.
  28. Stolze, C.; Semmler, G.; Tomas, O. Sustainability in business process management research—A literature review. In Proceedings of the Eighteenth Americas Conference on Information Systems, Seattle, WA, USA, 9–12 August 2012.
  29. Schoormann, T.; Kutzner, K.; Pape, S.; Knackstedt, R. Elevating social sustainability in business processes: A pattern-based approach. In Proceedings of the International Conference on Information Systems (ICIS 2019), Munich, Germany, 15–18 December 2019.
  30. Filos, E.; Banahan, E. Towards the smart organization: An emerging organizational paradigm and the contribution of the European RTD programs. J. Intell. Manuf. 2001, 12, 101–119.
  31. The Remote Work Competency Model—Creating Success at Every Stage of Remote Work. Available online: https://www.workplaceless.com/blog/remote-work-competency-model (accessed on 11 May 2021).
  32. The Future of Work after COVID-19. Available online: https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-after-covid-19 (accessed on 4 May 2021).
  33. Future Skills Pilot. Available online: https://www.accenture.com/tw-en/case-studies/consulting/future-skills-pilot-report (accessed on 5 April 2021).
  34. Tarafdar, M.; Beath, C.; Ross, J. Enterprise cognitive computing applications: Opportunities and challenges. It Prof. 2017, 19, 21–27.
  35. Skills for Jobs. Available online: https://www.oecd.org/els/emp/Skills-for-jobs-brochure-2018.pdf (accessed on 5 May 2021).
  36. Kirchmer, F. Value-Driven Business Process Management: The Value-Switch for Lasting Competitive Advantage, 1st ed.; McGraw Hill: New York, NY, USA, 2012; Available online: https://www.celonis.com/process-mining-core/ (accessed on 4 June 2021).
  37. Ekman, P.; Thilenius, P.; Thompson, S.; Whitaker, J. Digital transformation of global business processes: The role of dual embeddedness. Bus. Process Manag. J. 2020, 26, 570–592.
  38. Kirchmer, M. Business Process Management in a Digital World—Trends and Predictions. Available online: https://www.dbizinstitute.org/resources/articles/business-process-management-digital-world-trends-and-predictions (accessed on 4 June 2021).
  39. Javidroozi, V.; Shah, H.; Feldman, G. A framework for addressing the challenges of business process change during enterprise systems integration. Bus. Process Manag. J. 2020, 26, 463–488.
  40. Binci, D.; Belisari, S.; Appolloni, A. BPM and change management: An ambidextrous perspective. Bus. Process Manag. J. 2020, 26, 1–23.
  41. Schmitt, A.; Hörner, S. Systematic literature review—Improving business processes by implementing agile. Bus. Process Manag. J. 2021. ahead of print.
  42. Queiroz, M.; Fosso Wamba, S.; Machado, M.; Telles, R. Smart production systems drivers for business process management improvement: An integrative framework. Bus. Process Manag. J. 2020, 26, 1075–1092.
  43. Battisti, E.; Shams, S.; Sakka, G.; Miglietta, N. Big data and risk management in business processes: Implications for corporate real estate. Bus. Process Manag. J. 2020, 26, 1141–1155.
  44. Oncioiu, I.; Căpuşneanu, S.; Topor, D.I.; Ifrim, A.M.; Silvestru, R.C.; Toader, M.I. Improving business processes in a construction project and increasing performance by using target costing. Sage Open 2021, 11, 2158244021997808.
  45. Santos, F.; Pereira, R.; Vasconcelos, J. Toward robotic process automation implementation: An end-to-end perspective. Bus. Process Manag. J. 2020, 2, 405–420.
  46. Raisch, S.; Krakowski, S. Artificial intelligence and management: The automation-augmentation paradox. Acad. Manag. Rev. 2021, 46, 192–210.
  47. Leotta, F.; Marrella, A.; Mecella, M. IoT for BPMers. Challenges, case studies and successful applications. In Business Process Management. Lecture Notes in Computer Science; Hildebrandt, T., van Dongen, B., Röglinger, M., Mendling, J., Eds.; Springer: Cham, Switzerland, 2019; Volume 11675.
  48. Janiesch, C.; Koschmider, A.; Mecella, M.; Weber, B.; Burattin, A.; Di Ciccio, C.; Gal, A.; Kannengiesser, U.; Mannhardt, F.; Mendling, J.; et al. The Internet-of-Things Meets Business Process Management: Mutual Benefits and Challenges, CoRR. 2017. Available online: dbis.eprints.uni-ulm.de (accessed on 12 September 2021).
  49. Evermann, J.; Rehse, J.-R.; Fettke, P. Predicting process behavior using deep learning. Decis. Support Syst. 2017, 100, 129–140.
  50. Cimiterra, M.; Krafft, J.; Nesta, L. Blockchain as Schumpeter Mark 1 or Mark 2? An empirical analysis of blockchain job offers in France and Germany. Ind. Corp. Chang. 2021, dtab009.
  51. Gritzalis, D.; Stavrou, V.; Kandias, M.; Stergiopoulos, G. Insider threat: Enhancing BPM through social media. In Proceedings of the 6th International Conference on New Technologies, Mobility and Security (NTMS), Dubai, United Arab Emirates, 30 March–2 April 2014; pp. 1–6.
  52. Swenson, K. Social BPM: Work, Planning and Collaboration under the Impact of Social Technology; Future Strategies Inc: Lighthouse Point, FL, USA, 2012.
  53. Brambilla, M.; Fraternali, P.; Vaca, C. A model-driven approach to social BPM applications. In Social BPM; Future Strategies Inc: Lighthouse Point, FL, USA, 2011; pp. 95–112.
  54. Erol, S.; Granitzer, M.; Happ, S.; Jantunen, S.; Jennings, B.; Johannesson, P.; Koschmider, A.; Nurcan, S.; Rossi, D.; Schmidt, R. Combining BPM and social software: Contradiction or chance? J. Softw. Maint. Evol. Res. Pract. 2010, 22, 449–476.
  55. Schmidt, R.; Nurcan, S. BPM and social software. In Business Process Management Workshops. BPM 2008. Lecture Notes in Business Information Processing; Ardagna, D., Mecella, M., Yang, J., Eds.; Springer: Berlin/Heidelberg, Germany, 2009; Volume 17.
  56. Brands, R. Cognitive social structures in social network research: A review. J. Organ. Behav. 2013, 34, 82–103.
  57. Cullen-Lester, K.; Maupin, C.; Carter, D. Incorporating social networks into leadership development: A conceptual model and evaluation of research and practice. Leadersh. Q. 2017, 28, 130–152.
  58. Cullen-Lester, K.L.; Woehler, M.L.; Willburn, P. Network-based leadership development: A guiding framework and resources for management educators. J. Manag. Educ. 2016, 40, 321–358.
  59. Pilny, A.; Dobosh, M.; Yahja, A.; Poole, M.S.; Campbell, A.; Ruge-Jones, L.; Proulx, J. Team coordination in uncertain environments: The role of processual communication networks. Hum. Commun. Res. 2020, 46, 385–411.
  60. Woehler, M.; Cullen-Lester, K.; Porter, C.; Frear, K. Whether, how, and why networks influence men’s and women’s career success: Review and research agenda. J. Manag. 2021, 47, 207–236.
  61. Waszkowski, R. Low-code platform for automating business processes in manufacturing. Ifac-Pap. 2019, 52, 376–381.
  62. Akkermans, J.; Keegan, A.; Huemann, M.; Ringhofer, C. Crafting project managers’ careers: Integrating the fields of careers and project management. Proj. Manag. J. 2020, 51, 135–153.
  63. Marjanovic, O.; Freeze, R. Knowledge intensive business processes: Theoretical foundations and research challenges. In Proceedings of the 44th Hawaii International Conference on System Sciences, Kauai, HI, USA, 4–7 January 2011; pp. 1–10.
  64. Little, T.; Deokar, A. Understanding knowledge creation in the context of knowledge-intensive business processes. J. Knowl. Manag. 2016, 20, 858–879.
  65. Marjanovic, O.; Freeze, R. Knowledge-intensive business process: Deriving a sustainable competitive advantage through business process management and knowledge management integration. Knowl. Process Manag. 2012, 19, 180–188.
  66. Sarnikar, S.; Deokar, A.V. A design approach for process-based knowledge management systems. J. Knowl. Manag. 2017, 21, 693–717.
  67. Pilipczuk, O.; Cariowa, G. Business process modelling with “cognitive” EPC diagram. In Advances in Soft and Hard Computing, ACS 2018: Advances in Intelligent Systems and Computing; Pejaś, J., El Fray, I., Hyla, T., Kacprzyk, J., Eds.; Springer: Cham, Switzerland, 2019; Volume 889, pp. 220–228.
  68. Intelligent Business Process Management Suites (iBPMS) Reviews and Ratings. Available online: https://www.gartner.com/reviews/market/intelligent-business-process-management-suites (accessed on 4 May 2021).
  69. Hull, R.; Nezhad, H. Rethinking BPM in a cognitive world: Transforming how we learn and perform business processes. In Proceedings of the Business Process Management, 14th International Conference, BPM, Rio de Janeiro, Brazil, 18–22 September 2016; pp. 3–19.
  70. Nezhad, M.; Akkiraju, R. Towards cognitive BPM as the next generation BPM platform for analytics-driven business processes. Lect. Notes Bus. Inf. Process. 2015, 202, 158–164.
  71. Zebec, A. Cognitive BPM: Business Process Automation and Innovation with Artificial Intelligence. Available online: http://ceur-ws.org/Vol-2420/paperDC1.pdf (accessed on 5 September 2021).
  72. Slominski, A.; Muthusamy, V. BPM for the masses: Empowering participants of cognitive business processes. In Proceedings of the Business Process Management Workshops, BPM 2017, Barcelona, Spain, 10–15 September 2017; Teniente, E., Weidlich, M., Eds.; Springer: Cham, Switzerland, 2018; Volume 308.
  73. Wilson, H.; Alter, A.; Sachdev, S. Business Processes Are Learning to Hack Themselves; Harvard Business Review: Brighton, MA, USA, 2016; Available online: https://hbr.org/2016/06/business-processes-are-learning-to-hack-themselves (accessed on 5 October 2021).
  74. Szelągowski, M.; Lupeikiene, A. Business process management systems: Evolution and development trends. Informatica 2020, 31, 579–595.
  75. Szelągowski, M. The knowledge and process dimensions. Vine J. Inf. Knowl. Manag. Syst. 2021, 51, 271–287.
  76. Kuchta, D.; Ryńca, R. Podejście procesowe w świetle badań polskich przedsiębiorstw. Bad. Oper. I Decyz. 2007, 2, 71–81.
  77. Flieger, M. Zarządzanie Procesowe w Urzędach Gmin. Model Adaptacji Kryteriów Dojrzałości Procesowej; Adam Mickiewicz University, Prawo: Poznan, Poland, 2016; p. 176.
  78. Cyfert, S. Doskonalenie procesów w polskich przedsiębiorstwach, Management Forum 2020—Nowoczesne koncepcje i metody zarządzania strategicznego. In Nowoczesne Koncepcje i Metody Zarządzania Strategicznego; Płoszajski, P., Bełz, G., Eds.; SGH: Warsaw, Poland, 2006.
  79. Czubasiewicz, H.; Grajewski, P.; Sliż, P. Rola pracownika w organizacji zorientowanej procesowo. J. Manag. Financ. 2018, 16, 57–66.
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