Document Type : Research Paper
Authors
1 Associate Professor, Technology management Department Allameh Tabataba’i University, Tehran, Iran
2 PhD Student of Technology management Allameh Tabataba’i UniversityTehran, Iran Corresponding Author : Sohrab-aghazade@atu.ac.ir
3 Associate Professor, Technology management Department Allameh Tabatabai’ University, Tehran, Iran
4 Assistant Professor, Allameh Tabataba’i University, Tehran, Iran
Abstract
Abstract
The reduction of profit margins and the disappearance of past competitive advantages have pushed companies in Petrochemical industries toward innovation by utilizing digital capabilities. This necessitates the establishment of a strategic alignment between digital capabilities and innovation strategies and decisions. This research aims to examine the dimensions of alignment between digital capability variables and innovation strategies and create a framework for its assessment. Initially, by reviewing the background of studies, a framework for assessing each of the variables was developed. Subsequently, a questionnaire for confirmatory structural analysis of the identified concepts and dimensions was formulated. This questionnaire was completed by 99 experts in innovation management, digital technologies in the industry, and academia. As a result, it was determined that to assess the level of alignment between digital capabilities and innovation strategies, creating digital value and digital innovation processes for innovation strategies, digital innovation infrastructure and digital innovation capabilities for digital capabilities, and complementarity, balance, and coordination for alignment were considered as assessment dimensions of the variables.
Introduction
Today, the advantages of the past in the petrochemical industry are diminishing, and the competitive landscape is changing. It can be noted that one of the main challenges encompassing the petrochemical industry today is enhancing competitiveness and reducing operational costs, which require innovation in the use of new technologies (O. V. Zhdaneev, V. Korenev, and A. S. Lyadov, 2020).
Most organizations in this industry use structures and organizational procedures that are not well-suited for utilizing innovative capabilities, including digital capabilities (Alexey Shinkevich, Naira Barsegyan, Vladimir Petrov, and Tatyana Klimenko, 2021). On the other hand, organizations are striving to create complementarity between their different capabilities to strengthen potential innovation capacity (Rogier van de Wetering, Patrick Mikalef, 2017).
Therefore, one of the crucial questions for companies in the petrochemical industry can be how to assess the alignment between digital capabilities and innovation strategy. Consequently, the goal of this research is to identify appropriate dimensions and components for assessing the alignment of digital capabilities and innovation strategy in the petrochemical industry. To achieve this, the relevant concepts related to the main variables are identified and examined, and based on this, the dimensions and components under these variables will be confirmed through a validation process to create an assessment tool.
Literature Review
In the examination of digital capabilities in the petrochemical industry, it can be noted that new processes and patterns are emerging due to adaptation to new technologies, (Amankwah-Amoah, J., Khan, Z., Wood, G., & Knight, G., 2021). Studies conducted on dynamic capabilities (Loureiro, R., Ferreira, J. J., & Simoes, J., 2021) claim that the proper combination of resources and capabilities allows organizations to gain a competitive advantage and improve their performance. (Torres, R., Sidorova, A., & Jones, M. C, 2018). From automating data movement to leveraging processes, all of these have a significant impact on creating added value and generating income (Oztemel, 2018). Based on this, to assess the digital capability variable, one can consider the effective use of digital innovation resources, the management of digital innovation networks, the capacity for absorbing and accepting digital innovation, predicting trends and technologies, managing digital innovation risks, access, transparency, and information security, advanced analysis, and artificial intelligence, as primary components.
Pisano introduces three key questions as the pillars of innovation strategy: The first question is how the organization's innovation creates value for potential customers. The second is how the company gains a share of the value it creates due to its innovation. The third question returns to the type of innovations that enable the company to create and gain value, and what resources each innovation requires (Pisano, 2015). The role and position of digital technologies in addressing these key questions seem crucial. Since digital technologies have significantly influenced technical and social changes for individuals and societies, including organizations, they have caused products, services, processes, and business models to have a more substantial impact (Ciriello RF, Richter A, Schwabe G, 2018).
The concept of alignment implies the existing collaboration between different organizational units based on environmental needs. Organizations with greater alignment perform better in various performance standards, and an aligned organization has internalized directions (Labovitz, G. H., & Rosansky, V., 1997). Growth and profitability are ultimately the results of alignment between employees, customers, strategies, and processes (Labovitz, G. H., & Rosansky, V., 1997). It is necessary for organizations to prepare for changes by creating structures and processes that can easily be adjusted and realigned (Galbraith, 2002). Alignment should exist at all levels of the organization (individuals, projects, systems, and the company). In recent studies, digital platforms and the ecosystem around the company have been added to the scope (Coltman, T., P. Tallon, R. Sharma, and M. Queiroz, 2015).
Methodology
This research was conducted with an applied approach using quantitative methods and confirmatory factor analysis. The main question in this study relates to the components and dimensions of assessing the alignment between two variables: digital capability and innovation strategy. Therefore, it was necessary to identify and categorize concepts, indicators, and main dimensions of each of the three variables (alignment, digital capability, and innovation strategy) based on previous studies, and this formed the basis for analysis in the confirmatory factor analysis. Based on the identified concepts and indicators for the variables, a questionnaire was developed. A total of 120 individuals were identified. A purposive sampling method was used to collect their opinions, and questionnaires were distributed. In the end, 110 responses were received, of which 99 were usable. The reliability of the questionnaire was calculated for each of the variables, and all of them had values above 0.7 (as reported in the findings). Then, using the smart PLS software and the confirmatory method, the sub-structures of each of the variables were modeled.
Conclusion
Based on a review of the literature and relevant concepts and topics related to the research question, a comprehensive understanding was developed. Previous alignment models in organizations have mostly focused on information technology and high-level business strategies.
Regarding the assessment of the innovation strategy variable, it's important to note that, given the decreasing profit margins and the increasing operational costs of companies, a shift toward value-oriented strategies (economic, social, etc.) is becoming more prominent. The realization of value can be achieved through customizing products, improving industrial processes, automating decision-making, and increasing the speed of decision-making in innovation. On the other hand, digital technology has brought fundamental changes to innovation management processes, requiring companies to be attentive to new tools and approaches when formulating innovation strategies. Artificial intelligence aids in identifying new opportunities, while big data analysis helps organizations make decisions based on their past records and experiences.
Furthermore, as companies in the petrochemical industry need to create digital capabilities for success in the field of digital innovation, some of these capabilities will be focused on changing historical business routines. In this context, businesses strive to continuously evaluate the returns on their digital projects and optimize resource allocation. Additionally, the enhancement of digital literacy, thinking, and human capital competencies, often referred to as digital talent, is essential.
In the context of digital capability and innovation strategy, there are three main dimensions. The first is coordination. If the path to digital innovation is pursued in a fragmented and uncoordinated manner within the organization, it is unlikely to enhance organizational performance and alignment. Therefore, organizational goals and needs in the digital innovation and digital capability domains should be coordinated, and the organization should be able to establish new processes to create dynamism in the problem-solution and digital innovation processes. Moreover, stronger attention and balancing are required, as unbalanced attention to digital capability or innovation strategy can disrupt alignment and equilibrium between organizational capabilities. This indicates the importance of flexibility and transparency regarding resource allocation. The illustration of model is showed in figure 1.
Figure 1. Dimensions of alignment of digital capability and innovation strategy
Keywords: Digital Capabilities, Innovation Strategy, Alignment, Digital Innovation.
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Main Subjects
Adrian Yeow, Christina Soh, Rina Hansen. (2017). Aligning with new digital strategy: A dynamic capabilities approach. Journal of Strategic Information Systems.
Alexey Shinkevich, Naira Barsegyan, Vladimir Petrov and Tatyana Klimenko. (2021). Transformation of the management model of a petrochemical enterprise in the contex of industry 4.0 challenges. 1st International Conference on Environmental Sustainability Management and Green Technologies. Kazan.
Amankwah-Amoah, J., Khan, Z., Wood, G., & Knight, G. (2021). COVID-19 and digitalization: the great acceleration. Journal of business research, 602-611.
Anmar Kamalaldin, David Sjodin, Dusana Hullova, Vinit Parida. (2021). Configuring ecosystem strategies for digitally enabled process innovation: A framework for equipment suppliers in the process industries. Technovation.
Baker, J. and H. Singh. (2019). The roots of misalignment: Insights on strategy implementation from a system dynamics perspective. Journal of Strategic Information Systems.
Bertot JC, Estevez E, Janowski T. (2016). Digital Public Service Innovation. 9th International Conference on Theory and Practice of Electronic Governance, (ص. 113-122). New york.
Chan, Y. E. and B. H. Reich. (2007). IT alignment: What have we Learned? Journal of Information Technology.
Chan, Yolande, Rashmi Krishnamurthy, Ali Ghawe. (2020). Information Technology allignment and innovation. Boston: the essence of knowledge.
Ciriello RF, Richter A, Schwabe G. (2018). Digital Innovation. Business & Information systems engineering, 60, 563-569.
Coltman, T., P. Tallon, R. Sharma, and M. Queiroz. (2015). Strategic IT alignment: Twenty-five years on. journal of information technology, 91-100.
Cooper, C. L. (2014). Wiley Encyclopedia of Management. Wiley.
Daniel Ellstrom, Johan Holtstrom, Emma Berg and Cecilia Josefsson. (2). Dynamic capabilities for digital transformation. Journal of Strategy and management, 272-286.
Dürr, S., Wagner, H.T., Weitzel, T. and Beimborn, D. (2017). Navigating digital innovation: The complementary effect of organizational and knowledge recombination. International Conference on Wirtschaftsinformatik.
Galbraith, J. R. (2002). Designing organizations: an executive guide to strategy, structure and process. San Francisco: Jossey-Bass.
Gerow, J. E., J. B. Thatcher, and V. Grover. (2015). Six types of IT-business strategic alignment: An investigation of the constructs and their measurement. European Journal of Information Systems., 465-491.
Huang, J.C., Henfridsson, O., Liu, M.J. and Newell, S.,. (2017). Growing on steroids: Rapidly scaling the user base of digital ventures through digital innovation. MIS Quarterly, 301-314.
Hukal, P. and Henfridsson, O. (2017). Digital innovation: A definition and integrated perspective. The Routledge Companion to Management Information Systems,.
Kappelman, L., V. Johnson, R. Torres. (2018). A study of information systems issues, practices, and leadership in Europe. European Journal of Information systems.
Khin, S., & Ho, T. C. (2019). Digital technology, digital capability and organizational performance:A mediating role of digital innovation. International Journal of Innovation science.
Kim, H. (2015). Acceptability engineering: The study of user acceptance of innovative technologies. Journal of Applied Research and Technology,, 230-237.
Ksenia Onufrey, Anna Bergek. (2021). Transformation in a mature industry: The role of business and innovation strategies. Technovation.
Labovitz, G. H., & Rosansky, V. (1997). The power o f alignment: How great companies stay centered and accomplish extraordinary things. Ney york: Wiley.
Loureiro, R., Ferreira, J. J., & Simoes, J. (2021). Approaches to measuring dynamic capabilities: Theoretical insights and the research agenda. Journal of Engineering and Technology management.
Nambisan, S., Lyytinen, K., Majchrzak, A. and Song, M. (2017). digital innovation management: Reinventing innovation management research in a digital world. MIS Quarterly, 223-238.
- V. Zhdaneev, V.Korenev, and A. S. Lyadov. (2020). Opportunities and Challenges to Deploy Industry 4.0 Technologies in Russian Oil Refining and petrochemical industries. Russian Journal of applied chemistry, 1926-1930.
Olascoaga, E. (2006). DYNAMIC STRATEGIC ALIGNMENT: An integrated method. Pepperdine University.
Oztemel, E. (2018). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 127-182.
Pisano. (2015). You need an innovation strategy. Harvard Business Review, 44-54.
Qing Wu, Dawei Zhang. (2018). Digital Transformation Of Refining& Chemical Enterprises Under The Contemporary Situation From Digital To Smart. The International Journal of Engineering and Science, 23-19.
Reinmoeller, P. (2010). Dynamic contexts for innovation strategy: Utilizing customer. Design Management Journal, 37-50.
Rogier van de Wetering, Patrick Mikalef. (2017). managing firms innovation capabilities through strategically aligning combinative IT and dynamic capabilities. Information Systems. Boston.
Saldanha, T.J., Mithas, S. and Krishnan, M.S. (2017). Leveraging customer involvement for fueling innovation: The role of relational and analytical information processing capabilities. MIS Quarterly, 367-396.
Skog DA, Wimelius H, Sandberg J. (2018). Digital disruption. Business & Information system engineering, 431-437.
T larger, J.Frishammar. (2010). Equipment supplier/user collaboration in the process industries. in search of enhanced operating performance, 698-720.
Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. information management, 822-839.
Walsham. (2017). ICT4D research: Reflections on history and future agenda. information technology for development, 18-41.
Wang, C. L. (2007). Dynamic capabilities: A review and research agenda. International Journal of management reviews, 31-51.
Watson, R., Lind, M. and Haraldson, S. (2017). Physical and Digital Innovation in Shipping: Seeding, Standardizing, and Sequencing. 50th Hawaii International Conference on System Sciences.
Yeow, A. (2018). Aligning with new digital strategy: A dynamic capabilities approach. Journal of Strategic Information Systems.
Zhan Shi, Yongping Xie, Wei Xue. (2020). Smart factory in Industry 4.0. System reasearch and behavioral Science, 1-11.
Zhou, X., Cai, Z., Tan,K. H., Zhang, L., Du, J., & Song,. (2021). technological innovation and structural change for economic development in China as an emerging market. Technological Forecasting and Social Change.