نوع مقاله : مقاله پژوهشی

نویسندگان

• بهمن خداپناه ¹
• سید علی حسینی ²
• مجتبی بابایی هزه جان ³

¹ استادیار، گروه مدیریت بازرگانی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران نویسنده مسئول: khodapanah@uma.ac.ir

² استادیار گروه جهانگردی، دانشکده مدیریت و حسابداری دانشگاه علامه طباطبائی، تهران ،ایران

³ دانشجوی دکتری مدیریت دولتی گرایش توسعه و تطبیقی، گروه مدیریت دولتی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران

چکیده

خاستگاه تغییرات فناورانه مدرن، زمینه را برای درک تحولات فناورانه، بررسی تاثیر فناوری‌های دیجیتال جدید، و بررسی پدیده اختلال دیجیتال در صنایع و مشاغل فراهم می‌کند. آنچه قابل توجه است نقش داده‌ها در تحولات فناورانه و در نتیجه تخریب خلاقی است که تحول دیجیتال و مدل‌ها و استراتژی‌های کسب‌وکار جدید، نوآوری و قابلیت‌ها در سطوح جهانی، ملی، شرکتی و محلی را در منجر می‌شود. هدف اصلی پژوهش حاضر طراحی چارچوبی برای توسعه تخریب خلاق داده محور است. روش تحقیق، به‌صورت کیفی با رویکرد داده‌بنیاد و نظریه اشتراوس و کوربین و رهیافت نظام مند انجام گرفت؛ جامعه آماری تحقیق شامل کسانی که دانش نظری در رابطه با تئوری های کارآفرینی به ویژه تخریب خلاق و کسانی که تجربه کافی در حوزه کسب و کارهای داده محور داشته باشند. برای تحلیل داده‌های کیفی، مراحل کدگذاری باز، محوری و انتخابی را طی کرده و در نهایت الگوی پارادایمی گراندد تئوری در بر دارنده 5 بعد اصلی و 21 بعد فرعی شامل عوامل علی(فناوری، شخصییتی و رفتاری، چارچوب نهادی) عوامل زمینه ساز(داده‌های رفتاری،داده‌های متنی، داده‌های روانشناختی، اطلاعات دموگرافیک، داده‌های جغرافیایی، میل به تخریب)، عوامل مداخله گر(فناوری سازمانی، درجه‌ای که ارزش جدید خلق می‌شود، اثربخشی و مدیریت هزینه)، راهبردها(راهبرد توسعه خلاقیت، راهبرد مبتنی بر ساختار، راهبرد بازتعریف مدل کسب و کار، راهبرد حس کردن و شکل دادن، راهبرد شناسایی و توقیف، راهبرد تغییر شکل و پیکربندی مجدد) و پیامدها( فناورانه، اجتماعی- اقتصادی) شکل گرفت.

کلیدواژه‌ها

• تخریب خلاق
• تغییرات فناورانه
• اقتصاد داده محور

موضوعات

• مدیریت داده، اطلاعات و دانش در حوزه کسب‌وکار هوشمند

عنوان مقاله [English]

Designing a framework for the development of data-driven creative destruction

نویسندگان [English]

• bahman khodapanah ¹
• Seyyed Ali Hosseini ²
• Mojtaba Babaeihezejan ³

¹ Assistant Professor, Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardebil , Ardabil, Iran Corresponding Author: khodapanah@uma.ac.ir

² Assistant Professor, Department of Tourism Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran

³ Ph.D. Candidate, Department of Governmental Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran

چکیده [English]

The origins of modern technological change provide the necessary context for understanding today's technological developments, examining the impact of new digital technologies, and examining the phenomenon of digital disruption in emerging industries and businesses. Time will tell how new technologies transform industries and institutions. But what is significant is the role of data in technological developments and creative destruction that causes digital transformation and new business models, business strategies, innovation and capabilities at the global, national, corporate and local levels. The main purpose of the current research; Design is a framework for developing data-driven creative destruction. The research method was conducted qualitatively with the grounded theory approach and Strauss and Corbin theory and systematic approach. The statistical population of the research includes those who have theoretical knowledge in relation to entrepreneurship theories, especially creative destruction, as well as those who have sufficient experience in the field of data-driven businesses. In order to analyze the qualitative data, open, central and selective coding steps were carried out and finally, the paradigm model of grounded theory was based on the comprising five main dimensions. and 21 sub-dimensions including causal factors (technology, personality and behavior, institutional framework) underlying factors (data behavioral, textual data, psychological data, demographic information, geographical data, destructive intent), intervening factors (organizational technology, the degree to which new value is created, effectiveness and cost management), strategies (creative development strategy, strategy Based on the structure, the strategy of redefining the business model, the strategy of sensing and shaping, the strategy of identification and seizure, the strategy of transformation and reconfiguration) and consequences (technological, socio-economic) were formed.

Introduction

Increasing globalization, e-commerce, and cross-border information sharing have led to the need for most companies worldwide to be digitally active. The key driver of creative destruction in the modern economy is data, and data is the backbone of emerging industries such as artificial intelligence, machine learning, and the Internet of Things. However, the current "data economy" is centralized and decentralized. Currently, it is very difficult for businesses to access and use the data they need to innovate and grow. Two decades ago, the popularity of the Internet led to what we refer to here as the first digital destruction; File-sharing, and the reordering of content-based industries from music to film to news, etc., have led us to the second digital destruction, driven by the ability of streaming platforms to collect massive amounts of data combined with powerful computing about Consumer preferences and consumption patterns. The data collected by Companies like Netflix, Spotify, and Apple leverage consumer data to gain granular insights into preferences. This has led to the emergence of "data-driven creativity" in business marketing.
 A review of the research literature related to the phenomenon of creative destruction and data-driven economy shows that so far there is no research that has investigated the relationship between these two phenomena.
 We show how businesses use streaming data not only to organize and suggest content to consumers, but even to shape creative decisions. Therefore, the organization of this article will be as follows: in the second part, the theoretical foundations and background of the research will be examined; In the third part, the research method is determined, and in the fourth part, the research findings will be evaluated. Finally, in the fifth section; We will draw conclusions and make suggestions from a policy perspective.

Literature Review

 Creative destruction, coined by Austrian economist Joseph Schumpeter in 1942 in his work, Capitalism, Socialism and Democracy. It is an evolutionary process in capitalism that overturns the economic structure from within, continuously destroying the old structure and creating a new structure. Every business operates in this "permanent storm," where "every part of the business strategy takes on real importance." From this definition; It can be concluded that Schumpeter saw the market and competition as dynamic. One of the most important features of the theory of creative destruction is that it can be transferred from the analysis of economic institutions to political institutions. Schumpeter made this transition by revising - in a radical and subtle way - the neoclassical theory of decision making and the formation of supply and demand.

Methodology

This study employs a qualitative approach rooted in Strauss and Corbin’s grounded theory methodology. The participant pool comprises experts in entrepreneurial theory (particularly creative destruction) and practitioners in data-driven businesses. Data were collected via semi-structured interviews, with purposive and iterative sampling conducted until theoretical saturation. Coding—a "vital link" between data collection and interpretation (Charmaz, 2001; Saldaña, 2021)—followed Strauss and Corbin’s (1967) three-stage process: open, axial, and selective coding. Categories were organized into causal, contextual, intervening, strategic, and consequential factors.

Results

The most important step in the process of analyzing the data obtained from the interviews is coding. A code, in qualitative research, means a short word or phrase that symbolically and succinctly represents a salient and comprehensive feature of an element of data. Charmaz (2001) describes coding as the "vital link" between data collection and the interpretation of their meanings (Saldana, 2021). In the grounded theory approach, the process of data analysis based on the theory of Strauss and Corbin (1967) includes three stages of coding (open, central, selective) and six categories, including the determination and identification of causal, central, intervening, contextual or background factors. strategies and finally consequences.

Discussion

In this study; the grounded theory paradigm model has five main dimensions and 21 sub-dimensions, including causal factors, background factors, intervening factors, strategies, and consequences were formed.

Conclusion

In the data economy, huge amounts of data are growing rapidly through various sources, including social media, sensors, and other digital technologies. These data are often used to improve society by improving the efficiency and effectiveness of various systems such as transportation and healthcare. However, the collection and use of data can raise concerns about privacy, security, and other social issues that may negatively impact society. In order to assess the nature and scope of these impacts on society, it is important to consider factors such as the parties' access to this information and the ways in which it is used. Gaining a clear understanding of the social implications of the data economy is critical to ensuring the responsible and ethical use of data.
Legal enablers are laws, regulations and other legal frameworks that enable the development and growth of the data economy while guaranteeing the rights of all. These enablers can include various legal frameworks such as data protection laws that ensure the privacy and security of personal data and laws that govern the collection, use and sharing of data. Legal enablers are essential to provide a stable and predictable legal environment in which companies and individuals can operate and innovate in the data economy. They can also help protect the rights and interests of individuals and ensure that the data economy is fair and transparent.
Keywords: Creative Destruction, Technological Changes, Data-Driven Economy.
 
 

کلیدواژه‌ها [English]

• Creative Destruction
• Technological Changes
• Data-driven Economy