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Rapid scaling amidst resource constraints is crucial for established firms and startups in today’s business landscape. Despite its increasing popularity and research interest, little is understood about dynamic capabilities in the context of growth hacking. This study explores how growth hacking activities contribute to developing dynamic capabilities by employing a flexible pattern matching approach based on 29 qualitative interviews with growth hacking experts. By filling the gap in understanding dynamic capabilities in the context of growth hacking, the research enriches growth hacking’s theoretical foundations and provides practical insights. The results emphasize effectively managing capability dimensions dualities, distinguishing between startup and corporate challenges, and prioritizing rapid experimentation with big data. The study also examines artificial intelligence’s (AI) potential for automating growth hacking processes, while highlighting data privacy risks. This paper suggests future research avenues for further exploring the interplay of dynamic capabilities and growth hacking.
The has been an upsurge in the significance of sustainability in the business landscape, leading corporations to adopt strategies that extend beyond implementing social responsibility initiatives. While start-ups and social entrepreneurs have excelled in integrating sustainability into their business models, balancing financial goals with the growing demand for sustainability has been far more challenging for large corporations. This study considers the potential of corporate entrepreneurship to foster sustainability within established companies. Sustainable corporate entrepreneurship (SCE) allows companies to leverage innovation for sustainability as a value-creating opportunity rather than a restrictive constraint. This study addresses a critical gap in the literature—the lack of a comprehensive framework for SCE––through a meticulous, systematic literature review of 95 recent publications. Our proposed SCE framework has three dimensions: focus, approach, and evaluation. We provide insights to deepen understanding and guide future research in this evolving field. Specifically, we introduce a model that illustrates how SCE can be cultivated as a dynamic capability for generating value through sustainability-focused innovation. This model captures individual and organisational factors and encompasses factors that enable and limit SCE.
Artificial intelligence (AI) emerges as a promising technology to address burgeoning challenges resulting from shifting demographics, coupled with a shortage of qualified personnel. Thus, the adoption of AI creates especially interest within the talent acquisition (TA) domain to realize anticipated efficiency gains. However, evidence suggests that AI adoption may foster the emergence of harmful forms of practices (HFP) within TA practices. Despite the importance, respective empirical studies collecting data to generate insights remain sparse. Thus, the aim of this study is to investigate HFP and underlying drivers through a mixed-method approach. At the first stage, we conducted in-depth interviews with 42 TA experts. The resulting insights informed the development of the 'Adoption of AI in TA: Framework on Negative Consequences.' This model suggests that a confluence of technological, individual, and organizational factors can result in the emergence of HFP post-AI adoption. Such potential HFP include biased decision-making, data privacy violations, and efficiency reduction. Then, we validated our qualitative findings and confirmed our hypotheses by employing a quantitative, survey-based approach with 303 valid study participants. By shedding light on potential HFP through AI adoption in TA and respective catalysts, our research empowers both information technology and TA professionals to proactively engage in mitigation strategies. In this vein, they may successfully navigate the complex landscape of AI adoption. Hence, this study adds to research on effective AI adoption in TA.
Artificial intelligence (AI) is increasingly being recognized as a critical tool when it comes to addressing the most pressing challenges facing modern industries, including the pursuit of sustainability. The use of AI is aiding businesses in navigating corporate sustainability challenges, but existing research lacks a comprehensive exploration of how corporations leverage AI to boost their sustainability. By exploiting an inductive concept-development approach and incorporating data from 24 companies, this study provides valuable insights into the role that AI plays in shaping organizational sustainability strategies, identifying operational enablement and technical capacity as key drivers of AI adoption for corporate sustainability. These drivers are incorporated into the technology, organization, and environment (TOE) framework alongside the strategic steps and capabilities necessary for organizations to effectively adopt and implement AI in the development of their sustainability strategies. Ultimately, this study proposes an integrative model for sustainability-oriented AI adoption that emphasizes the importance of aligning AI initiatives with organizations’ sustainability objectives in order to maintain a competitive advantage and drive progress. Correspondingly, it underscores the need for robust data management, system integration, and continual performance monitoring to reduce resistance to AI adoption allowing for the potential of AI to be fully harnessed in pursuit of sustainability. Furthermore, this study offers practical guidance by exploring the direct and indirect use cases of AI in corporate sustainability. The study concludes by highlighting potential avenues for future research in this evolving field.
The concept of coopetition - simultaneous collaboration and competition between organizations to achieve mutually beneficial outcomes - plays a pivotal role in shaping business performance, particularly during periods of rapid technological advancements. This is especially evident the manufacturing sector, where innovation and competitive dynamics intersect with economic and social forces. The current academic discourse predominantly focuses on the qualitative identification and analysis of coopetition attributes, leaving a significant gap for large-scale quantitative studies to enable empirical assessment. This study aims to examine the significance of three groups of coopetition attributes for coopetition performance classified into two strategic (dynamics, paradoxicality), six relational (asymmetry, complexity, coopetition intensity, mutual dependence, strength, tensions), and five behavioral attributes (competition intensity, conflict, formality, investments, trust). Using data from 1216 manufacturing firms in Poland and employing a generalized Covariance based Structural Equation Model (CB-SEM), this study offers nuanced insights to the global discourse at the intersection of technological change and social dynamics. The results indicate that the strategic attribute paradoxicality, the relational attribute strength, and most of the behavioral attributes (trust, competition intensity, investments, formality) positively impact coopetition performance. Additionally, a significant negative impact of the strategic attribute dynamics was demonstrated, while no significant influence was identified for the remaining relational attributes (asymmetry, tensions) as well as the behavioral attribute conflict. Diverging from prior qualitative approaches, this study offers data-driven insights for decision-makers navigating societal and technological change, highlighting which attributes should be stimulated to enhance coopetition performance while minimizing the level of dynamics within coopetition strategies.
Adopting AI-based solutions is now widely regarded as an essential consideration in organisations’ innovation strategies. For healthcare institutions, such solutions are an especially promising means to address societal and organisational challenges, including rising demand combined with shortages of qualified staff. The technology may enhance the efficiency of, for example, detecting diseases and planning treatments, which are time-consuming when executed manually. However, empirical research related to how AI can be effectively adopted in healthcare to harness these opportunities remains scarce. To address this gap, we conduct an exploratory multiple case study comprising 13 cases in the radiotherapy domain. Taking over an adoption theory perspective, we uncover that organisational, environmental, technological and individual factors are decisive for effective adoption of AI and contribute to the emergence of efficiency gains and standardisation. Our analysis reveals that organisational factors such as pursuing a dedicated innovation strategy within the radiotherapy department as well as a holistic AI implementation strategy are most crucial. In determining and relating the identified relevant factors, we contribute to adoption theory and AI-enabled value creation in healthcare. Further, we advise managers of healthcare institutions on how to effectively adopt AI to overcome challenges at organisational and societal levels.
This paper investigates the emerging potential of metaverse technology and the diverse opportunities it presents for companies across industries. Although the metaverse remains in its nascent stages, its swift evolution has introduced a broad spectrum of use cases that hold significant promise for businesses. However, despite the evident potential, there remains a limited understanding of how metaverse technology can be effectively applied to benefit business operations and strategy. To address this gap, this study employs a scoping review methodology, systematically collecting and analyzing data from academic literature, publicly available sources, and company websites. The comprehensive review identified 101 distinct use cases of metaverse technology, which were subsequently categorized into three primary application fields: developing new product and service offerings, enhancing customer experience, and optimizing internal business processes. These findings not only provide a compelling rationale for companies contemplating the adoption of metaverse technology but also represent the first extensive exploration of its applications across diverse fields and industries. The study offers valuable insights that are crucial for both academic researchers and business practitioners who are keen to understand and leverage the transformative potential of the metaverse. By mapping out the current landscape of metaverse applications, this paper contributes to a deeper understanding of how companies can harness this technology to drive innovation, improve operational efficiency, and create new value propositions in an increasingly immersive and interconnected world.
Purpose
This study aims to explore the potential of entrepreneurship through acquisition (ETA) in the underexplored sector of small and medium-sized web-based businesses, addressing the succession crisis in industrialized nations and offering insights into the digital ETA landscape.
Design/methodology/approach
The research uses a qualitative approach, conducting in-depth interviews with 19 established website owners from diverse backgrounds and industries. The study investigates their business models, selling motivations and characteristics to provide insights for potential buyers in the digital ETA space.
Findings
Web-based small and medium-sized enterprises (SMEs) present unique opportunities for ETA, characterized by lower initial investment, higher scalability and diverse revenue streams. Key considerations for buyers include understanding seller motivations, evaluating niche focus and assessing the impact of emerging technologies such as artificial intelligence on content creation and search engine optimization. The findings also highlight the importance of authenticity and user engagement in maintaining website value.
Practical implications
The findings offer valuable insights for entrepreneurs considering ETA in the digital space, highlighting critical factors for success, potential risks and mitigation strategies in acquiring web-based businesses.
Originality/value
This paper bridges a significant gap in ETA literature by focusing on web-based SMEs, which have previously been overlooked despite their growing importance in the digital economy. It provides a comprehensive analysis of relevant factors when evaluating web-based businesses in the context of ETA, particularly in light of technological advancements and changing online landscapes.
Organizational agility (OA), the ability of an organization to adapt to rapidly changing environments and reconfigure its structure and operations, has become a critical capability for achieving and sustaining competitive advantage. However, existing frameworks for OA often adopt narrow, industry-specific perspectives, neglecting the broader interplay of contextual factors, internal and external antecedents, and multidimensional capabilities. This study addresses this gap by conducting a systematic literature review (SLR) of 110 peer-reviewed articles from three leading academic databases. Guided by an inductive approach and the grounded theory methodology, this research identifies and categorizes the key antecedents of OA into four interconnected dimensions: contextual factors, fundamental attributes, vital enablers, and dynamic capabilities. The findings reconceptualize OA as a bundle of interrelated dynamic capabilities—encompassing macro-agility (e.g., strategic and partnering agility) and micro-agility (e.g., operational, innovation, and workforce agility)—rather than a singular construct. This multidimensional concept bridges theoretical gaps, integrating insights from contingency, agency and resource-based theories to explain the dynamic relationship between internal and external antecedents. The study offers a foundation for future research and provides actionable guidance for practitioners seeking to design agile organizations capable of thriving in dynamic capabilities.
Innovating beyond boundaries
(2025)
This article analyses how firms enhance their dynamic capabilities through open innovation activities. While previous research has acknowledged the potential of integrating dynamic capabilities and open innovation, existing studies are fragmented in that they neither build upon one another nor offer a comprehensive framework. Instead, they often focus on isolated aspects of dynamic capabilities, resulting in disparate, incoherent insights. This fragmentation hinders the development of actionable insights for organizations aiming to systematically enhance their innovation processes through open innovation. To address this issue, we conducted a systematic literature review to identify key dimensions that link open innovation activities to the sensing, seizing and transforming phases-the core components of dynamic capabilities. The resulting framework offers an integrative perspective that goes beyond fragmented research findings and provides a structured approach to operationalizing open innovation. The framework transitions open innovation from an abstract concept to a practical tool that can be systematically embedded into firms' innovation processes. Additionally, by situating dynamic capabilities within the context of innovation management, the framework expands their theoretical and practical utility. This study provides actionable insights for practitioners and establishes a consolidated foundation for future research, thus enhancing the theoretical and practical impacts of open innovation.