Ferran Giones

Abstract

Entrepreneurial ecosystem (EE) research has contributed to reshaping entrepreneurial policy and practice. Despite significant translational efforts, the gap between theory and actionable policy seems to be widening. This paper adopts a collaborative approach and critically reflects on the alignment of EE research with practical policy needs, structured around an interactive round-robin brainstorming with 58 EE scholars (i.e., 12 authors and 46 additional experts). We examine policy adoption in the context of EE, discussing the challenges and evolution of research methods, data, and theory. We propose a future policy-oriented research agenda, validated and prioritized by European policymakers, to ensure that EE research effectively informs entrepreneurship policy.

Abstract

The role of incumbent firms in sustainability transitions is gaining more attention, with rapidly rising evidence of their proactive role in the change. Nevertheless, debates continue to focus on their defensive and resisting role. Studies that review the existing knowledge on incumbents' interaction with sustainability transitions are lacking. Therefore, this research applies a systematic literature review to introduce a synthesised approach to differentiate between incumbents' proactive and defensive strategies. Further, it examines these strategies more closely and proposes a level-based typology that includes organisational and management, technology development, industry and markets, and institutional. It argues that this classification has implications for scholarship, policymaking and management and highlights avoiding the sectoral bias in empirical evidence on proactive and defensive strategies and how addressing the four-level strategies by which incumbents interact with sustainability transitions contributes to creating policies and strategies that enforce an incumbent-led transition.

Abstract

In the context of open innovation, effectively integrating internal and external collaborative networks to leverage relevant knowledge is crucial for enhancing innovation capabilities. Current research has largely overlooked the potential non-linear effects of knowledge relatedness (similarity and complementarity) in external collaboration networks on firm innovation capability, particularly the risk of innovation suppression caused by excessive relatedness. Moreover, systematic investigation is still lacking regarding how internal inventor collaboration networks moderate this relationship. Using a sample of 189 publicly listed firms and employing social network analysis along with negative binomial regression modeling, this study addresses two key questions: (1) Does knowledge relatedness in external collaboration networks nonlinearly affect firm innovation capability? (2) How does the structure of internal collaboration networks influence this relationship? The findings reveal an inverted U-shaped relationship between both knowledge similarity (the alignment of a firm's internal knowledge) and knowledge complementarity (differences between shared resources) and firm innovation capability. Moderate levels of knowledge similarity and complementarity are most conducive to enhancing innovation capability. Furthermore, transitivity within internal inventor collaboration networks strengthens the effect of knowledge relatedness on innovation, whereas network stability weakens it. These results extend the application of absorptive capacity theory in network innovation contexts and offer a theoretical basis for firms to optimize partner selection and improve internal collaboration mechanisms.

Abstract

The progression from Google's 2017 transformer architecture to OpenAI's ChatGPT in 2022 marks a pivotal development in artificial intelligence (AI). Innovations, such as self-attention mechanisms and parallelization, significantly advanced natural language processing, enabling powerful generative models like GPT-3. ChatGPT's introduction democratized conversational AI, fueling rapid adoption across diverse industries. This article discusses AI's far-reaching impact beyond the software sector, highlights advancements in generative AI efficiency and accessibility, explores emerging architectures like Agentic and Multimodal AI, addresses implications for the workforce, and outlines critical challenges requiring attention.

Abstract

Cognitive biases within Artificial Intelligence are a common phenomenon. Before this background, we asked ChatGPT what the cognitive biases of AI are. In this article, we critically reflect on the response we got from Generative AI, and discuss cognitive biases in general. We then focus on concrete implications for handling cognitive biases. Such as Algorithms and techniques that can help AI systems identify and reduce bias could be implemented, and standardized techniques to check AI systems for bias before implementation. We also highlight the importance of realizing procedures for ongoing observation and input to identify and rectify prejudices in AI systems once they are put into use. We conclude that solving such biases calls for an allencompassing strategy that incorporates experts from other fields and places an emphasis on moral issues in addition to technological fixes. By doing this, we can encourage the creation of AI technologies that are not just advanced but also ethical, equitable, and beneficial to society as a whole.

Abstract

Creating new manufacturing systems or changing existing ones are both time-consuming and cost-sensitive. Errors in system development not only lead to financial losses and setbacks in market competition but also generate wasteful operations that are unsustainable. Digital twin technology offers a solution by replicating the behavior of complex systems in a virtual environment. This approach reduces the resources required for system development and enables the creation of a more efficient system in a shorter timeframe. This paper sheds light on the wasteful aspects of system development and introduces a digital twin-based agile system development life cycle (DT-Sustain).

Abstract

Sustainability and Industry 4.0 have been emerging topics in recent years, in theory as well as in practice. Related technological topics like 5G technology, blockchain, artificial intelligence and digital twins among others, are gaining importance. In addition, these themes are becoming increasingly merged with a discussion on I4.0 from societal and organizational perspectives. As a background to this paper, we discuss recent research in this area as covered in this Special Issue. We identify accepted submissions covering four conceptual themes and three methodological themes in the SI. Finally, we outline opportunities for future research: these include human interaction with I4.0 technology-enabled workspaces as well as societal aspects of I4.0 in relation to sustainability efforts. Last, but not least, interaction of I4.0 with other disciplines, such as sustainable manufacturing, reliability, maintenance and disaster management are proposed.

Abstract

Despite extensive research on academic entrepreneurship and entrepreneurial universities, this special issue challenges conventional beliefs by examining intrapreneurship in academia. It aims to investigate how faculty and staff can adopt entrepreneurial behaviors and cultivate an entrepreneurial approach within their roles as researchers and educators, in diverse academic contexts. The 11 papers included in this issue span various domains of intrapreneurial universities, broadening the original concept beyond initial expectations set forth in the call for papers. Exploring a spectrum of intrapreneurial initiatives, this issue seeks to enhance understanding and broaden perspectives on intrapreneurial behaviors within universities through various research approaches and methodologies. Based on the contributions received, we reflect on theoretical and practical implications and delineate future directions for academic intrapreneurship research.

Abstract

OVERVIEW: The artificial intelligence (AI) revolution in new product development (NPD) has reached a critical juncture, demanding decisive action from business leaders. Our comprehensive study of key AI applications in NPD reveals a startling lack of adoption across industries, particularly in the United States. Despite the potential benefits, businesses also demonstrate weak intentions to adopt AI and low readiness regarding AI integration into NPD processes. Despite the low adoption rate, the study’s results offer a compelling picture of AI’s potential, including substantial positive impacts of AI use in key areas like product design, prototyping, testing, digital twin simulations, market analysis, and new product ideation. Benefits include accelerated development and markedly improved decision-making.

Abstract

Open innovation requires the correct diagnosis of the situation, a differentiated value proposal, and a coherent, consistent action plan. In at least the first phases of this related funnel, open innovation can profit tremendously from artificial intelligence (AI) applications. How? Today, numerous sources of unstructured and scattered information, which may provide strategic insights, are accessible and can be automatically and systematically scanned and analyzed by AI algorithms. For example, the main sources of a company's strategic information are the evolving scientific research on its core competencies; the emergence of synergistic startups; the company's expansion decisions, new product launches, patents, and research and development investments; and its economic and financial results. While open innovation is subject to human cognitive biases, AI applications help overcome these biases and use metadata far beyond human respective ecosystems. This chapter explores the possibilities and limits of AI-enabled open innovation.

Abstract

Moments of crisis such as pandemics, hyperinflation, or natural disasters cause societies, governments, companies, and individuals to reflect on their priorities and essential needs. However, there is no concept or theory that links human needs to the consumption of goods and services. With this in mind, we introduce the product essentiality concept and a method to measure the essentiality level of a group of products. We used a survey questionnaire and quantitative methodology to illustrate the concept and propose that it can be reasonably approximated by a measure of perceived essentiality. Our analysis examined the influence of location, gender, and family income on the perceived essentiality of general goods and services. For this, a sample of Business and Management students in Brazil and the UK classified 81 products as ‘essential’ or ‘superfluous’. Our findings and analyses show that applying the essentiality concept and its measurement can be consistent and useful for reflecting on what is essential and what is not. This study provides preliminary insights on product portfolio essentiality measurements suggesting it is significantly affected by location rather than gender and income. The results can help organisations to rethink their product portfolios, designs, and assist sustainable development policies.

Abstract

The incompatibility between diverse responsible principles of science and technology (S&T) and multi-stakeholders' heterogeneous value assessments underscores the importance of coordinating normative principles of responsible research and innovation (RRI). In this context, this study adopts an ambidexterity lens to address this issue, conceptualizing two constructs—“generalized responsibility” and “specialized responsibility” of S&T (GRST and SRST)—to illustrate the trade-offs. It explores the antecedents of GRST and SRST from an agency perspective. Drawing from a dataset of 19,707 poll responses, the study employs a fractional logit regression model to examine the relationships between three types of agency (iterational agency, strategic agency, and ethical agency) and GRST and SRST. The results reveal a positive relationship between iterational agency and SRST, and between strategic agency and GRST, as well as U-shaped effects of iterational agency on GRST, strategic agency on SRST, and ethical agency on both GRST and SRST. Moreover, ethical agency is found to be more important for SRST than for GRST. The study offers theoretical and policy implications for a critical discussion about responsible innovation.

Abstract

Continuous innovation is the lifeblood of a competitive economy. Furthermore, and arguably, the existence of institutions of governance of quality can be a catalyst for emerging economies to transition up the universal innovation value chain. In this context, we investigate temporal causal interactions among institutional quality, innovation, and economic growth for developing countries (DCs) spanning the period of 2005–2020. Employing a vector error-correction model (VECM), we find that for each case and specification (49 instances), there is evidence of the long-run causality from institutional quality and innovation to economic growth. Stated another way, in the long run, institutional quality and innovation Granger-cause economic growth. However, the short-run causality results differ depending on the specific measures of innovation and institutional quality. The strongest short-run conclusion is support for the feedback hypothesis for economic growth and innovation where there is a strong endogenous relationship between innovation, institutional governance, and economic growth. The empirical analysis shows over 70\% of our observations support that economic growth and innovation jointly determine each other in the short run. The results suggest that DCs should develop and pursue long-term growth strategies that simultaneously develop innovation and improve institutional governance.

Abstract

The automotive industry is undergoing a profound transformation characterized by the transition from hardware-centric to software-driven vehicles. This results in a variety of challenges, such as the increasing complexity of components, shortened development cycles, and evolving regulatory requirements that need to be met. In this context, our article explores the impact of UNECE regulations R.155 and R.156 on the technical prototyping phase in the development of mechatronic systems. Furthermore, we use the findings as an objective and examine the implications for the current landscape of prototyping research. Using a comprehensive case study in the German automotive industry with four OEMs, we investigate the current state of prototyping in the German automotive industry. Our analysis shows that although previous research suggests prototyping processes, they reach their limits in complex systems and cannot cope with the challenges of the industry. At the center of the conclusions is the need to develop a prototyping framework that includes a taxonomy of projects and forms the basis for a testing strategy to shorten time-to-market. As part of this, we propose the introduction of the novel term “phygital prototype” to bridge the gap between physical and virtual prototypes. Furthermore, we argue that product compliance should not only be integrated methodically but also propose concrete procedural steps within the prototyping framework.

Abstract

This research aims to consider, in the context of smart objects, the interplay of motivated consumer innovativeness (MCI), satisfaction and word-of-mouth (WOM). Following earlier behavioural research through three phases of attitudes (cognition, affection and conation), the study proposes that functional, hedonic, and social MCI (cognition) are positively related to satisfaction (affection), thus positively influencing WOM engagement (conation). In addition, it is shown that functional and hedonic MCI moderate the relationship between social MCI and satisfaction. Two quantitative studies across two smart object categories (1,129 users of wearables and 511 users of smart home objects) highlight that both functional and hedonic MCI positively relate to satisfaction and WOM. Though the effect of social MCI on satisfaction is non-significant for smart home objects and very low for wearables, our findings confirmed that social MCI has an indirect impact on satisfaction through functional and hedonic MCI in both product categories.

Abstract

Crisis highlights conflicts but also helps disparate organisations rally around common objectives through forming ecosystemic relationships. To improve future crisis response, we study the influence of crisis-driven transitions on innovation in ecosystems. We illustrate the study with the dynamics of hydrogen innovation at Enel. Here, innovation caters to multiple value propositions; therefore, we define interecosystemic innovation as an innovation that addresses the value propositions of more than one ecosystem. The unexpected disruption caused by the energy crisis focuses attention on a single value proposition, thus fomenting the dynamic, temporal sequencing of interecosystemic innovation. This increases activity in the ecosystem core as well as interaction with the ecosystem periphery, allowing more rapid innovation iterations throughout the ecosystem. When operating in the intercept of ecosystems, firms need to consider the multiple value propositions of ecosystem participants to identify and mitigate tensions that may impede innovation.

Abstract

Overview Artificial intelligence (AI) is transforming all aspects of business, including new product development (NPD). Early adopters of AI for NPD are reaping substantial rewards, witnessing remarkable reductions in development timelines, and experiencing a more rapid pace of innovation. But what about the more typical firm? This article presents the preliminary results of a study of US and Central European companies, shedding light on the current state of AI implementation across 13 key AI applications in NPD. We found that companies studied have not yet fully embraced AI across any of these applications; 75 percent have failed to adopt AI for a single application; and “intention to adopt” for all 13 applications is quite weak. European firms are only marginally ahead of US firms. We conclude with important messages for management and offer six recommendations firms can use in their efforts to integrate AI into NPD. A note of caution: Companies will need to act quickly in their AI adoption efforts; otherwise, they risk losing out.

Abstract

Digital platforms are changing economies and societies, challenging the fundamental institutions of democracy and requiring an understanding of the driving factors behind the development of such platforms. Therefore, we have investigated the impact of dominant platforms on standardization in innovation ecosystems on the level of technologies, firms, and societies. We have conducted a systematic review of the literature on standardization and ecosystems. We define ecosystem-based standardization as the development of a standard embodied in a dominant platform. Important innovation-related findings include that processes are embedded in the platform, allowing for complementary innovation using modular capabilities and, thus, requiring the traditional view of the relationship between product and process innovation to be revisited. Ecosystem-based standardization foments both technological and organizational modularity, which increases innovation speed as well as synergies within the ecosystem. However, the power asymmetry generated by ecosystem-based standardization favors value appropriation by platform sponsors, which has vast implications for the development of regulations and institutions.

Abstract

Traditionally, designers and engineers develop prototypes to visualize concepts and test features. People from other disciplines were less involved in this process. Nowadays, more interdisciplinary approaches are required to solve complex problems in new product development. The evidence showing the value of interdisciplinary approaches in prototyping practice is limited. This study designs a workshop to investigate the values and impacts of both the mono-disciplinary approaches and interdisciplinary approaches in prototyping practice. Technical skills are essential, but soft skills, e.g. communication and process management, can enhance significantly the prototype performance. Fixation effects are observed in both mono-disciplinary and interdisciplinary groups.

Abstract

Technological evolution in the field of robotics is emerging with major breakthroughs in recent years. This was especially fostered by revolutionary new software applications leading to humanoid robots. Humanoids are being envisioned for manufacturing applications to form human-robot teams. But their implication in manufacturing practices especially for industrial safety standards and lean manufacturing practices have been minimally addressed. Humanoids will also be competing with conventional robotic arms and effective methods to assess their return on investment are needed. To study the next generation of industrial automation, we used the case context of the Tesla humanoid robot. The company has recently unveiled its project on an intelligent humanoid robot named Optimus to achieve an increased level of manufacturing automation. This article proposes a framework to integrate humanoids for manufacturing automation and also presents the significance of safety standards of human-robot collaboration. A case of lean assembly cell for the manufacturing of an open-source medical ventilator was used for human-humanoid automation. Simulation results indicate that humanoids can increase the level of manufacturing automation. Managerial and research implications are presented.

Abstract

Artificial Intelligence (AI) is an emerging technological field with immense transformative potential. Within this context, we discuss the diverse ways AI is transforming innovation. We introduce a conceptual framework in which we argue AI plays the following two roles: originator and facilitator of innovation. Additionally, we discuss different applications and implications for innovation theory and practice using a reflection on the traditional innovation process and the front end of innovation perspective. For this, we use the perspectives of AI as technology push, AI as market pull, AI to advance steps in the innovation funnel as well as AI as a contributor to new product development. Finally, we discuss future directions for research in these fields.

Abstract

Artificial intelligence (AI) technologies are engaged in a harsh battle for market dominance. This article examines the emergence of a dominant design in terms of technology, service, and business model innovation. We conduct a theoretical synthesis of the literature on industrial organization, technology management, network economics, operations management, and strategic management—with the implications of each theory related to the dominant-design battle in AI. The findings indicate a dominant design for AI will be based on innovation concerning business models as much as on technology, and that the dominant business model will include AI as a service.

Abstract

The disruptive impact of digital technologies opens the opportunity to redefine the innovation ecosystems across (and between) several industries. To respond to this challenge, several initiatives were funded all over Germany. The Research Campus ARENA2036 at the University of Stuttgart oversees the platform for research and innovation on the topic of mobility and production of the future. This article describes the creation of ARENA2036, its organizing mechanisms, and its function as a catalyst for collaborative innovation. The article ends with a summary of the lessons learned in its first years of operation and an outlook on the future challenges.

Abstract

There is no doubt that the Covid pandemic had a lasting effect on people all over the world. It also gave rise to technological innovation as never before. Then how did these technologies change our lives during and beyond the pandemic? This article provides an overview of some of the key technological changes and of the situation in 2022. Our analysis is based on technologies directly related to the treatment of the virus, as well as on pandemic-born innovations influencing business and beyond. A final conceptual framework considers implications for the theory and practice of technological innovation. Specifically, we identify crisis innovation, defined as innovation carried out in response to a crisis, as a potential emerging line for future research efforts.

Abstract

The role of open or closed innovation (CI) strategies regarding the innovation or rather entrepreneurial success is not solved yet. Therefore, this simulation study examines by means of a multi-agent system the effects of open innovation (OI) on the entrepreneurial success of SMEs under differently parameterised market conditions. The simulation study shows that different market conditions and the characteristics of human resource allocation of a company have a relevant influence on the success of an innovation strategy. The experiments show that OI can mainly take advantage of more human resources, whereas CI lags behind OI in the financial aspect but exceeds OI in terms of market share. Furthermore, the simulation revealed that concrete company situations and market conditions have different effects on the examined innovation strategies. These findings help to stimulate further, even empirical, research efforts.

Abstract

Industry 4.0 is an important contributor to industrial innovation and sustainability. Nevertheless, few studies empirically analyse how it acts as a binding force of both business practices. This study examines 1501 sustainability reports using a mixed human-artificial intelligence method based on Python's text mining libraries. This method takes advantage of AI's capabilities to extract information from large samples of data and of human critical thinking to find patterns in those data. Specifically, the method is used to evaluate the adoption of Industry 4.0 technologies, analyse how they are deployed worldwide, and investigate their sustainability outcomes. In terms of overall frequency, robots and cybersecurity are the most often reported technologies. Broken down by the firm's region, Asian firms have the highest rate of adoption, while African firms are lagging. Regarding the themes, Industry 4.0 is mainly adopted to improve production processes and customer experience. A small percentage of firms, particularly in Europe and North America, utilize Industry 4.0 to reduce the environmental footprint of their operations. Furthermore, results indicate that Industry 4.0 and sustainability are following two routes. Some firms have massively adopted Industry 4.0 to increase operational efficiency and reaped environmental gains as an indirect consequence of improved operations. Others have chosen to balance the adoption of technologies aimed to increase productivity with innovations whose explicit aim is the reduction of their operations' environmental footprint, such as additive manufacturing. Eastern firms tend to follow the first route while western firms the second. African and South American firms are still at a very early stage in their Industry 4.0 and sustainability journey. At the global level, Industry 4.0 is still far from being utilized as a catalyst to develop sustainability-driven business models.

Abstract

The pandemic challenged industries and entire social systems. Hence, investigating overarching innovation ecosystems in this context can uncover the intriguing effects of innovation and technological change. Based on an inductive case study of a water ecosystem in Catalonia, Spain, with eleven interviews and a follow-up focus group, we observe how an idle innovation ecosystem was crucial to rapid technological change. This finding demonstrates that common innovation objectives and urgency born from a crisis can activate seemingly idle ecosystems—a novel concept in the literature—and suggests that society benefits from the development of ecosystems even when there is no initial joint value proposition. This ecosystem exaptation, i.e., the alignment of an existing ecosystem to a new value proposition, extends the concept of technological exaptation. Thus, business model innovation is a result of, and not an antecedent to, the emergence of an innovation ecosystem.

Abstract

Overview: The extent of knowledge available to society may no longer be limited by human cognition or by refining algorithms. Instead, the interaction of the two may limit knowledge transfer and creation. We examine two behavioral paradoxes: Polanyi’s paradox, which has existed since 1966, and the Trust paradox, which we propose. We study four technology innovations—printing, digitalization, the Internet, and artificial intelligence (AI)—and assess how these paradoxes limit the use of knowledge created by each innovation. We found that while technology has largely overcome Polanyi’s paradox of limiting the transfer of tacit knowledge, the Trust paradox may limit the application of AI-generated knowledge. We identify five relevant drivers of trust—reliability, transparency, association, reciprocity, and accountability—and outline how each impacts and creates challenges for the application of AI.

Abstract

The growing dynamics of innovation and productivity are challenges that are met by companies with the constant development of new technologies and business models-the logic with which they create and capture value. Especially in the face of the grand challenge of climate change, looking for energy efficient solutions offers opportunities not only for big companies in metropolitan areas, but also for small and medium sized companies in rural areas. This study therefore investigates similarities and differences of SMEs in an energy intensive industry that are situated in a specific, geographic border region regarding dependencies between networks, energy efficiency, and success. These three dimensions are analyzed in a qualitative study leading to implications for energy efficient solutions. This study contributes to existing research on sustainable collaborative business models by suggesting the inclusion of cross border networking and circular economy aspects.

Abstract

Digitalization is transforming the industrial landscape. Smarter products, data-based services, and new business models promise to reshape the whole manufacturing industry. However, below the visible excitement, unexpected tensions and challenges make the digital transformation an excruciating journey for industrial companies. In this article, we decipher the digital transformation strategy choices of leading industrial firms in a highly innovative country. Using their insights, we identify four dominant tensions that managers need to sort out. We provide guiding principles to select a digital transformation strategy that has the adequate configuration to overcome each of the identified tensions.

Abstract

Certain technologies have the potential to spawn an entrepreneurial ecosystem, but this potential is not always realized. Some of these technologies that could enable prosperous and sustainable ecosystems struggle at the threshold of ecosystem emergence. In this paper, we use an in-depth case study of an emergent entrepreneurial ecosystem based on an enabling technology—synthetic biology—to identify the structural, societal, and ethical barriers to ecosystem growth. The structural barriers mainly relate to the lack of an ecosystem framework to manage intellectual property in complex interactions. The societal barriers concern the clock speed conflict between parts of the quintuple helix entrepreneurial ecosystem, and the ethical barriers arise from the widespread impact of enabling technologies in combination with the diffusion of ethical responsibility throughout the ecosystem. We also discuss both the theoretical and managerial implications of these barriers.

Abstract

The race against time to attain the Sustainable Development Goals (SDGs) intensifies, with inequality, poor living conditions, and biodiversity threats still prevalent. Achieving the SDGs is constrained by limited resources that require frugal solutions that are affordable, easy-to-use, ecologically sustainable, and socially inclusive. The role of infrastructure companies developing technologies with a frugal orientation that focus on the 17 SDGs must be at the core of efforts, because sustainable infrastructure is critical to the SGDs. This paper examines how such company-efforts foster the SDGs through the lens of frugal innovation. An exploratory multiple case study methodology was used with a 3-step and 4-dimensional evaluation approach to determine what technologies are fostering the SDGs, and their frugal characteristics. The results show that alternative resource and energy innovations are at the core of how infrastructure companies are promoting sustainability and fostering the SDGs. Most cases cluster around ecological contributions (mainly climate and energy), with sustainability and cost-effectiveness being the common characteristics. Implications for theory and practice are discussed, as well implications for policy-making.

Abstract

Digitalization is transforming the industrial landscape. Smarter products, data-based services, and new business models promise to reshape the whole manufacturing industry. But just below the visible excitement lurk unexpected tensions and challenges that can make digital transformation an excruciating journey for industrial companies. In this article, we decipher the digital transformation strategy choices of leading industrial firms in a highly innovative country. We then identify four dominant tensions that managers need to sort out. We also provide guiding principles for selecting a digital transformation strategy capable of overcoming each of the identified tensions.

Abstract

For better or worse, digital technologies are reshaping everything, from customer behaviors and expectations to organizational and manufacturing systems, business models, markets, and ultimately society. To understand this overarching transformation, this paper extends the previous literature which has focused mostly on the organizational level by developing a multi-level research agenda for digital transformation (DT). In this regard, we propose an extended definition of DT as ?a socioeconomic change across individuals, organizations, ecosystems, and societies that are shaped by the adoption and utilization of digital technologies.? We suggest four lenses to interpret the DT phenomenon: individuals (utilizing and adopting digital technologies), organizations (strategizing and coordinating both internal and external transformation), ecosystems (harnessing digital technologies in governance and co-producing value propositions), and geopolitical frameworks (regulating the environments in which individuals and organizations are embedded). Based on these lenses, we build a multi-level research agenda at the intersection between the bright and dark sides of DT and introduce the PIAI framework, which captures a process of perception, interpretation, and action that ultimately leads to possible impact. The PIAI framework identifies a critical research agenda consisting of a non-exhaustive list of topics that can assist researchers to deepen their understanding of the DT phenomenon and provide guidance to managers and policymakers when making strategic decisions that seek to shape and guide the DT.

Abstract

Global warming is no longer a trend, but reality, which calls for the development of new technologies. In this paper, we thus identify antecedents of enabling technologies and study the patterns of emergence of new fields of eco-innovation. For this, we suggest a conceptual framework focusing on environmental technologies, specifically on their emergence as enabling technologies in innovation ecosystems. We test this framework using data of 136,059 citations to 13,510 patents of climate change mitigation technologies. Complex and complementary technologies tend to be more enabling for subsequent innovation, and this effect is amplified for environmental technologies that constitute dominant designs. Dominant designs generated through a collaborative process, on the other hand, rarely become enabling technologies. We also contribute to climate action by allowing governmental bodies and other investors to direct funding to those innovations that are most likely to make a lasting impact on global warming. In addition, managers and policy makers can foment the antecedents that are most important to incite the development of climate change mitigation technologies.

Abstract

To date, one of the most prominent methods to integrate users into the innovation process is the lead user method. However, due to its high resource intensity, it is less used than its potential would allow. In times of the internet and especially social media, this is changing since methods like netnography allow to efficiently identify potential lead users. Hence, based on a case study in the aviation industry, targeted screening and pyramiding are combined to identify lead users. Three users with sufficient characteristics to be lead users were included based on their degree-centrality and relevant contribution on Twitter. This study proposes the combination of these methods and Twitter as a suitable approach for lead user identification.

Abstract

Given the rapid popularity of smart wearable products, users' continuance intentions are increasingly important. Research concerning the continuance intentions to adopt smart wearable products has received some attention from scholars, but previous studies were more “technology-driven” rather than “consumer-driven” and largely neglected how different configurations (specific combinations of variables) affect users' intentions to continue adopting smart wearable products. This research, which is based on the means-end chain theory, tests the factors affecting the continuance intentions to adopt smart wearable products. Through an analysis of the survey results of 249 smartwatch and fitness wristband users by Mplus and fsQCA, the findings reveal that face consciousness was a strong predictor of users’ perceived value. Three dimensions of social capital had a different positive effect on perceived value. Social, utilitarian, and hedonic value positively affected continuance intention. Furthermore, different configurations of individual characteristics can explain the impact of the continued adoption of smart wearable products.

Abstract

Creating technologically focused entrepreneurs is a crucial endeavor worldwide, especially with the exponential growth of artificial intelligence (AI) innovation. This research explores meta-organizations that enable new business models in the retail domain by acting as a powerful mechanism to support entrepreneurs in extracting value from data. This study investigates how meta-organizations engage users and empower tech entrepreneurs to create shared value by developing social innovation. This research involves an in-depth and longitudinal unique case study of a meta-organization operating in Italy, Germany, and Finland. Results indicate that the flexible structure of meta-organizations can effectively guide stakeholders of different mindsets to offer support to high-tech startups. AI-based platforms are a reliable alternative to tackle critical social issues in order to improve economic growth and increase people's performance in a stressful, competitive environment, such as the retail sector. The findings affirm that AI-based innovation orchestrated by meta-organizations can enable new business models by creating shared value for society. Seven critical success factors with implications for theory and practice are discussed, and a new model for AI-driven entrepreneurship is proposed.

Abstract

For better or worse, digital technologies are reshaping everything, from customer behaviors and expectations to organizational and manufacturing systems, business models, markets, and ultimately society. To understand this overarching transformation, this paper extends the previous literature which has focused mostly on the organizational level by developing a multi-level research agenda for digital transformation (DT). In this regard, we propose an extended definition of DT as “a socioeconomic change across individuals, organizations, ecosystems, and societies that are shaped by the adoption and utilization of digital technologies.” We suggest four lenses to interpret the DT phenomenon: individuals (utilizing and adopting digital technologies), organizations (strategizing and coordinating both internal and external transformation), ecosystems (harnessing digital technologies in governance and co-producing value propositions), and geopolitical frameworks (regulating the environments in which individuals and organizations are embedded). Based on these lenses, we build a multi-level research agenda at the intersection between the bright and dark sides of DT and introduce the PIAI framework, which captures a process of perception, interpretation, and action that ultimately leads to possible impact. The PIAI framework identifies a critical research agenda consisting of a non-exhaustive list of topics that can assist researchers to deepen their understanding of the DT phenomenon and provide guidance to managers and policymakers when making strategic decisions that seek to shape and guide the DT.

Abstract

To provide further knowledge and technology transfer to society, universities are exploring new collaborative models. These new models are regarded as promising alternatives to the patent-centric linear model. However, their implementation requires revising the roles of the actors in the technology transfer process and their relationships. While collaborative models could indeed be an attractive option for universities, there is limited evidence on how these collaboration processes could be effectively introduced. We use a longitudinal embedded multiple case study to explore the contribution of knowledge interactions between scientists and students in the preliminary steps of the technology transfer process. We investigate the learning dynamics between the focal actor, i.e., the scientist, and the students in a university setting to decipher how the introduction of such collaborative processes can contribute to knowledge and technology transfer. Our results suggest that students enrolled in an educational program can contribute to the scientist’s interest and engagement in technology transfer. However, we find out that the extent of the students’ contribution depends on the shared consensus over the technology function and the openness of the scientist to reconsider the technology’s meaning. We contribute to the ongoing exploration of alternative models for technology transfer and the identification of additional roles that students can take in entrepreneurial university ecosystems.

Abstract

Digital means of creating and transferring knowledge have been thought to reduce the importance of firm location. Still, there is evidence that the urbanisation of entrepreneurship and innovation is accelerating in the digital era. We review the theory that explains how and why entrepreneurial activity moves towards city centers. Schumpeterian dynamics may affect urban entrepreneurial ecosystems more than others, and cities are thus more susceptible to external shocks. We therefore expect urban entrepreneurial activity to exhibit rapid but discontinuous growth. With data from 88 entrepreneurial ecosystems over 15 years, a panel regression analysis not only finds support for the urbanisation of entrepreneurial activity but also for how and when it happens. Urban entrepreneurial ecosystems appear to better support entrepreneurship under the current circumstances. Possible explanations and implications include the rise of digital platforms upon which business-model innovations prosper.

Abstract

The number of women entrepreneurs has increased significantly over the past years. However, literature suggests that women from science, technology, engineering, and mathematics (STEM) fields are inadequately represented in this growing trend. Meanwhile, the circumstances which cause this underrepresentation have not yet been sufficiently analysed. To help fill this gap, this paper focuses on women's entrepreneurship in specific educational and country contexts, acknowledging that relations between these factors play a crucial role in entrepreneurship. By means of an explorative approach, 21 interviews with seven STEM educated women entrepreneurs from Denmark, Latvia and Turkey have been conducted and analysed with a qualitative content analysis. The results show the main motivations, challenges, and support sources for the women entrepreneurs, and provide important advice for future women entrepreneurs as well as for policy makers to increase the number of STEM educated women on the national level.

Abstract

The synonymic use of sustainable innovation types obstructs the impact of increasingly disperse research on sustainable innovation, environmental innovation, eco-innovation, and green innovation. To identify the meaning and contributions of each innovation type over time, we apply co-word analysis as a bibliometric technique to 1,985 papers, analysing the evolution of motor, emergent and basic themes for each type. For environmental innovation, the focus has shifted from environmental regulations and policies to patents and inventions with an environmental impact, while in sustainable innovations the societal impact of technology adoption has become a driver. Green innovation increasingly concerns environmental technology and its management, whereas eco-innovation studies aspects related to efficiency and decision making. Clear distinctions among sustainable innovation types will increase the impact of this expanding body of research and make it more available to managers and policymakers.