@article {1422,
	title = {Call for Papers: Distributed Ledger Technologies for Smart Digital Economies},
	journal = {Technology Innovation Management Review},
	volume = {11},
	year = {2021},
	month = {02/2021},
	pages = {1-1},
	publisher = {Talent First Network},
	chapter = {1},
	address = {Ottawa},
	keywords = {artificial intelligence, blockchain, cybersecurity, digital economy, distributed ledger technology, smartification},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1422},
	url = {timreview.ca/article/1422}
}
@article {1471,
	title = {Can Artificial Intelligence be a Critical Success Factor of Construction Projects? Practitioner perspectives},
	journal = {Technology Innovation Management Review},
	volume = {11},
	year = {2021},
	month = {12/2021},
	pages = {17-32},
	publisher = {Talent First Network},
	chapter = {17},
	address = {Ottawa},
	abstract = {The construction sector has not been altogether successful in adopting automated systems. Related research on artificial intelligence has mainly been confined to the development of software models for a specific subset of construction work. This study aims to identify whether artificial intelligence is a potential critical success factor for construction project success. Data were collected through semi-structured interviews and analyzed using content analysis. The interviewees were selected on the basis of convenience and included highly experienced project managers from the global community with expertise in project management working on large construction projects. Our research shows that senior project managers perceive artificial intelligence as different from information technology and advanced project management software. Major drawbacks of artificial intelligence were found to be (i) lack of soft skills, (ii) lack of intelligence to interpret things in various ways like human beings, and (iii) lack of human relationship capabilities, including the ways people manage projects. The interviewees believe that artificial intelligence is still years away from becoming self-aware. This study improves the understanding of artificial intelligence as a success factor for construction projects and provides future directions for research in this field.},
	keywords = {artificial intelligence, Construction Projects, Critical Success Factors, Project Success},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1471},
	url = {timreview.ca/article/1471},
	author = {Virender Kumar and Amrendra Pandey and Rahul Singh}
}
@article {1449,
	title = {Distributed Ledger Technologies and Social Machines: How to {\textquotedblleft}smartify{\textquotedblright} the economy with blockchain-based digital extension services?},
	journal = {Technology Innovation Management Review},
	volume = {11},
	year = {2021},
	month = {06/2021},
	pages = {42-57},
	publisher = {Talent First Network},
	chapter = {42},
	address = {Ottawa},
	abstract = {This paper examines the broad impact of digitalization on economic development. More specifically, it addresses the computer science-derived notion of "social machines", along with the invention of distributed ledger technologies (DLTs) (or blockchain), as potential signposts on the pathway to "smart(er) digital economies". The paper investigates blockchain-based ecosystems as examples of social machines that assist in economic "smartification" and development. It looks at distributed ledger-based communities (DLCs) that provide examples of functioning social machines for a variety of business and personal network communications purposes. It then analyses the scaleup of DLT-based social machines by comparison with "extension services", largely in education and agriculture, which are currently undergoing processes of digitalization. Overall, this conceptual study examines the general horizons and potential impact of blockchain and social machines on the provision of online products and services, across a range of sectors and industries. The paper offers interpretative assistance to managers, entrepreneurs, technology experts, and academics with lingering questions about blockchain in and for business and economic development.},
	keywords = {artificial intelligence, blockchain, digital economy, digital platform, distributed ledger technology, economic development, extension services, extension thinking, innovation diffusion, Internet of Things, ledger community, smartification, social machines, web science},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1449},
	url = {timreview.ca/article/1449},
	author = {Gregory Sandstrom}
}
@article {1438,
	title = {Reinvigorating the Discourse on Human-Centered Artificial Intelligence in Educational Technologies},
	journal = {Technology Innovation Management Review},
	volume = {11},
	year = {2021},
	month = {05/2021},
	pages = {5-16},
	publisher = {Talent First Network},
	chapter = {5},
	address = {Ottawa},
	abstract = {The increasing relevance of artificial intelligence (AI) applications in various domains has led to high expectations of benefits, ranging from precision, efficiency, and optimization to the completion of routine or time-consuming tasks. Particularly in the field of education, AI applications promise immense innovation potential. A central focus in this field is on analyzing and evaluating learner characteristics to derive learning profiles and create individualized learning environments. The development and implementation of such AI-driven approaches are related to learners{\textquoteright} data, and thus involves several privacies, ethics, and morality challenges. In this paper, we introduce the concept of human-centered AI, and consider how an AI system can be developed in line with human values without posing risks to humanity. Because the education market is in the early stages of incorporating AI into educational tools, we believe that this is the right time to raise awareness about the use of principles that foster human-centered values and help in building responsible, ethical, and value-oriented AI.},
	keywords = {artificial intelligence, design for value approach., educational technology, human-centered AI, intelligent tutoring systems},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1438},
	url = {timreview.ca/article/1438},
	author = {Andr{\'e} Renz and Gergana Vladova}
}
@article {1348,
	title = {Correlation between Entrepreneurial Orientation and Implementation of AI in Human Resources Management},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {04/2020},
	pages = {72-79},
	publisher = {Talent First Network},
	chapter = {72},
	address = {Ottawa},
	abstract = {This paper develops the concept of adopting artificial intelligence (AI) in human resources management (HRM) through a research questionnaire and reports the results of a study designed to investigate the perception of adopting and introducing AI in HRM processes. In addition, it investigates the correlation between entrepreneurship orientation (EO) and AI in HRM processes. A survey was conducted with a sample of 310 firm members in the HR Section Romande, as well as a literature review on the adoption of new technologies. The results indicate a perceived positive value of introducing AI in HRM and a correlation between the level of a company{\textquoteright}s EO and the introduction of AI in HRM. This means that the more a company is entrepreneurially oriented, the more it tends to implement or include already implemented AI projects and tools in HRM processes. The perceived value of AI in HRM was evaluated by comparing answers to research questions involving the introduction of AI in HRM tools, and expectations of widely implementing AI in the next five years. The main barrier of adopting AI in HRM appeared to be a lack of skills and training. In addition, potential features of implementing AI in HRM were identified as potential steps toward introducing AI as a new technology. Questions regarding the evaluation of EO were based on a research Colvin Slevin (1989). It is important for SMEs to invest in information technology to set the basis for further development. Owing to intensified competitive pressures and the necessity of entering global markets, SMEs are incrementally employing Information Technology (IT) to create substantial benefits. Most prior research has focused more on IT adoption in large organizations, yet when regarding the limited resources of SMEs, the IT adoption process is considerably different. (Ghobakhloo, Sabouri, Hong and Zulkifli, 2011).},
	keywords = {artificial intelligence, entrepreneurial orientation, Human Resource Management},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1348},
	url = {timreview.ca/article/1348},
	author = {Rico Baldegger and Maurizio Caon and Kreshnik Sadiku}
}
@article {1298,
	title = {Editorial: Insights (January 2020)},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {01/2020},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {AI, artificial intelligence, B2B sales, big data, business-to-business sales, data-based value, digital solutions, ecosystem, ecosystems, Ethics, Gujarat State, Indian IT industry, innovation, IT clusters, Knowledge Innovation clusters, Networks Analysis, regional development, Roboethics, Smart robot, strategy, Systematic literature review, technology, value capture, value creation, value sales},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1298},
	url = {timreview.ca/article/1298},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1404,
	title = {Editorial: Insights (November 2020)},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {11/2020},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {AI innovation and maturity, and diaspora entrepreneurs., artificial intelligence, confidential information, criminal law, digitally enhanced teamwork, economic espionage, entrepreneurship, health technology, immigrants, Innovation management, living labs, migration, Multidisciplinarity, situated practice, small and medium-sized enterprises, stakeholder participation, sustainability, trade secrets, transnationals},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1404},
	url = {timreview.ca/article/1404},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1340,
	title = {The Effect of Machine Learning on Knowledge-Intensive R\&D in the Technology Industry},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {03/2020},
	pages = {88-98},
	publisher = {Talent First Network},
	chapter = {88},
	address = {Ottawa},
	abstract = {The impact of such current state-of-the-art technology as machine learning (ML) on organizational knowledge integration is indisputable. This paper synergizes investigations of knowledge integration and ML in technologically advanced and innovative companies, in order to elucidate the value of these approaches to organizational performance. The analyses are based on the premise that, to fully benefit from the latest technological advances, entity interpretation is essential to fully define what has been learned. Findings yielded by a single case study involving one technological firm indicate that tacit and explicit knowledge integration can occur simultaneously using ML, when a data analysis method is applied to transcribe spoken words. Although the main contribution of this study stems from the greater understanding of the applicability of machine learning in organizational contexts, general recommendations for use of this analytical method to facilitate integration of tacit and explicit knowledge are also provided.},
	keywords = {artificial intelligence, explicit knowledge, knowledge integration, ML, tacit knowledge, technological firm},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1340},
	url = {timreview.ca/article/1340},
	author = {Daniel Viberg and Mohammad H. Eslami}
}
@article {1312,
	title = {An Ethical Framework for Smart Robots},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {01/2020},
	pages = {35-44},
	publisher = {Talent First Network},
	chapter = {35},
	address = {Ottawa},
	abstract = {This article focuses on {\textquotedblleft}roboethics{\textquotedblright} in the age of growing adoption of smart robots, which can now be seen as a new robotic {\textquotedblleft}species{\textquotedblright}. As autonomous AI systems, they can collaborate with humans and are capable of learning from their operating environment, experiences, and human behaviour feedback in human-machine interaction. This enables smart robots to improve their performance and capabilities. This conceptual article reviews key perspectives to roboethics, as well as establishes a framework to illustrate its main ideas and features. Building on previous literature, roboethics has four major types of implications for smart robots: 1) smart robots as amoral and passive tools, 2) smart robots as recipients of ethical behavior in society, 3) smart robots as moral and active agents, and 4) smart robots as ethical impact-makers in society. The study contributes to current literature by suggesting that there are two underlying ethical and moral dimensions behind these perspectives, namely the {\textquotedblleft}ethical agency of smart robots{\textquotedblright} and {\textquotedblleft}object of moral judgment{\textquotedblright}, as well as what this could look like as smart robots become more widespread in society. The article concludes by suggesting how scientists and smart robot designers can benefit from a framework, discussing the limitations of the present study, and proposing avenues for future research.},
	keywords = {AI, artificial intelligence, Ethics, Roboethics, Smart robot},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1312},
	url = {timreview.ca/article/1312},
	author = {Mika Westerlund}
}
@article {1399,
	title = {Integrated AI and Innovation Management: The Beginning of a Beautiful Friendship},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {11/2020},
	pages = {5-18},
	publisher = {Talent First Network},
	chapter = {5},
	address = {Ottawa},
	abstract = {There is a growing consensus around the transformative and innovative power of Artificial Intelligence (AI) technology. AI will transform which products are launched and how new business models will be developed to support them. Despite this, little research exists today that systematically explores how AI will change and support various aspects of innovation management. To address this question, this article proposes a holistic, multi-dimensional AI maturity model that describes the essential conditions and capabilities necessary to integrate AI into current systems, and guides organisations on their journey to AI maturity. It explores how various elements of the innovation management system can be enabled by AI at different maturity stages. Two key experimentation stages are identified, 1) an initial stage that focuses on optimisation and incremental innovation, and 2) a higher maturity stage where AI becomes an enabler of radical innovation. We conclude that AI technologies can be applied to democratise and distribute innovation across organisations.},
	keywords = {AI innovation, AI maturity, artificial intelligence, IMS ISO 56002, Innovation management, maturity model},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1399},
	url = {timreview.ca/article/1399},
	author = {Nina Bozic Yams and Valerie Richardson and Galina Esther Shubina and Sandor Albrecht and Daniel Gillblad}
}
@article {1290,
	title = {The 3S Process: A Framework for Teaching AI Strategy in Business Education},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {12/2019},
	pages = {36-42},
	publisher = {Talent First Network},
	chapter = {36},
	address = {Ottawa},
	abstract = {A gap has emerged in teaching artificial intelligence (AI) in business education, where a style of curriculum based on strategy is missing. This article presents a new framework, the 3S Process, as a method for teaching leaders how to strategically adopt AI within their organizations. At a high-level, the 3S Process consists of three stages (Story, Strategy, and Solution), which are described in detail in the article. Stage 1: Story in the process is inspired by the Harvard Case Method to provide context for a problem. Stage 2: Strategy uses Design Thinking to produce candidate solutions. The substage of Empathy in Design Thinking plays a crucial role to reduce bias in designing AI. Virtualization technology is a tool for students to experience hands-on learning in prototype development. Stage 3: Solution is where students advocate for their conceptual AI solution in the context of the case study. AI is a type of complex system; therefore, students should consider feedback loops and the potential for unintended biases to enter a deployed solution. The presentation of the 3S Process in this article is conceptual. Further empirical studies, including evaluations of the 3S Process in classroom settings, will be considered in the future.},
	keywords = {3S Process, artificial intelligence, Business Education, design thinking, Harvard Case Method},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1290},
	url = {timreview.ca/article/1290},
	author = {Navneet Bhalla}
}
@article {1287,
	title = {Artificial Intelligence for Innovation in Austria},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {12/2019},
	pages = {5-15},
	publisher = {Talent First Network},
	chapter = {5},
	address = {Ottawa},
	abstract = {It has been claimed that Artificial Intelligence (AI) carries enormous potential for service and product innovation. Policy makers world-wide nowadays aim to foster environments conducive for AI-based innovation. This paper addresses the current lack of empirical data for evidence-based innovation policies and the management of AI-based innovation. It focuses on \&ldquo;AI and innovation management\&rdquo; in addressing the question whether innovation that is based on new AI technology requires a management approach different from other forms of IT innovation. We present results from a study of Austrian companies on the degree of use and implementation of AI, and on challenges related to AI-based innovation management. This study used a keyword-list approach to define \&ldquo;Artificial Intelligence\&rdquo; and to find AI-based innovation projects in research databases. These projects facilitated the identification of experts from organisations developing AI-based innovation. In total, eleven experts were interviewed about their AI-based innovation activities. The results show that AI is a very fast emerging technology that is being applied in many sectors. A broad range of innovative solutions are being developed and some have already reached the market. Specific AI business models are, however, less clear and still developing. Companies are facing multiple challenges from regulation to human resources and data collection. Managing AI-based innovation will be particularly difficult for smaller enterprises, where problems are often more pronounced than in larger industries. Explicit challenges for managing AI-based innovations include the necessary attention to managing expectations and ensuring historic metadata expertise essential for many AI-based solutions. Policies to support AI-based innovation therefore should focus on human aspects. This includes increasing the availability of AI experts, but also concerns the development of new job profiles, such as experts in AI training. AI innovators also require clear AI regulation and research investments in key challenges, such as explainable AI.},
	keywords = {AI, AI innovation management, artificial intelligence, Austria, innovation, SME},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1287},
	url = {timreview.ca/article/1287},
	author = {Erich Prem}
}
@article {1291,
	title = {Connected Health Innovation:  Data Access Challenges in the Interface of AI Companies and Hospitals},
	volume = {9},
	year = {2019},
	month = {12/2019},
	pages = {43-55},
	publisher = {Talent First Network},
	chapter = {43},
	address = {Ottawa},
	abstract = {The purpose of this paper is to explore the challenges and potential solutions regarding data access for innovation in the realm of connected health. Theoretically, our study combines insights from data management and innovation network orchestration studies, taking thereby a new approach into issues that have emerged in these research streams. Empirically, we study these issues in the context of a development endeavor involving an AI-driven surgery journey solution in collaboration with hospitals and companies. Our study indicates that the challenges and solutions in data access can be categorised according to the level where they emerge: individual, organisational, and institutional. Depending on the level, the challenges require solutions to be searched from different categories. While solutions are generally still scarce, organizational level solutions seem The purpose of this paper is to explore the challenges and potential solutions regarding data access for innovation in the realm of connected health. Theoretically, our study combines insights from data management and innovation network orchestration studies, taking thereby a new approach into issues that have emerged in these research streams. Empirically, we study these issues in the context of a development endeavor involving an AI-driven surgery journey solution in collaboration with hospitals and companies. Our study indicates that the challenges and solutions in data access can be categorised according to the level where they emerge: individual, organisational, and institutional. Depending on the level, the challenges require solutions to be searched from different categories. While solutions are generally still scarce, organizational level solutions seem to hold wide-ranging potential in addressing many challenges. By discussing these dynamics, this paper provides new knowledge for academics and practitioners on the challenges and solutions for data access and management in networked contexts. The greatest challenges among healthcare providers and health technology companies lay on uncertainties and interpretations concerning regulation, data strategy, and guidelines. Creating guidelines for data use and access in a hospital can be a first step to creating connected health innovations in collaboration with AI companies. For their part, these companies need to put effort into gaining in-depth knowledge and understanding of the processes and standards in healthcare context. Our paper is one of the first to combine data management and innovation network orchestration literatures, and to provide empirical evidence on data access related issues in this setting.to hold wide-ranging potential in addressing many challenges. By discussing these dynamics, this paper provides new knowledge for academics and practitioners on the challenges and solutions for data access and management in networked contexts. The greatest challenges among healthcare providers and health technology companies lay on uncertainties and interpretations concerning regulation, data strategy, and guidelines. Creating guidelines for data use and access in a hospital can be a first step to creating connected health innovations in collaboration with AI companies. For their part, these companies need to put effort into gaining in-depth knowledge and understanding of the processes and standards in healthcare context. Our paper is one of the first to combine data management and innovation network orchestration literatures, and to provide empirical evidence on data access related issues in this setting.},
	keywords = {artificial intelligence, connected health, Data access, data management, governance, information mobility, innovation, orchestration, patient- centered},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1291},
	url = {timreview.ca/article/1291},
	author = {Laura Kemppainen and Minna Pikkarainen and Pia Hurmelinna-Laukkanen and Jarmo Reponen}
}
@article {1278,
	title = {Editorial: Insights (November 2019)},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {11/2019},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {artificial intelligence, competitive advantage, cybersecurity, deep learning, Deepfake, design rules, digitalization, entrepreneurial ecosystems, entrepreneurial university, entrepreneurship, entrepreneurship education, fake news, innovation, international entrepreneurship, leadership, Learning Capabilities, marketing, motivation, new venture teams, quadruple helix, sanctions, SMEs, teamwork, triple helix, university business incubation},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1278},
	url = {timreview.ca/article/1278},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1282,
	title = {The Emergence of Deepfake Technology: A Review},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {11/2019},
	pages = {40-53},
	publisher = {Talent First Network},
	chapter = {40},
	address = {Ottawa},
	abstract = {Novel digital technologies make it increasingly difficult to distinguish between real and fake media. One of the most recent developments contributing to the problem is the emergence of deepfakes which are hyper-realistic videos that apply artificial intelligence (AI) to depict someone say and do things that never happened. Coupled with the reach and speed of social media, convincing deepfakes can quickly reach millions of people and have negative impacts on our society. While scholarly research on the topic is sparse, this study analyzes 84 publicly available online news articles to examine what deepfakes are and who produces them, what the benefits and threats of deepfake technology are, what examples of deepfakes there are, and how to combat deepfakes. The results suggest that while deepfakes are a significant threat to our society, political system and business, they can be combatted via legislation and regulation, corporate policies and voluntary action, education and training, as well as the development of technology for deepfake detection, content authentication, and deepfake prevention. The study provides a comprehensive review of deepfakes and provides cybersecurity and AI entrepreneurs with business opportunities in fighting against media forgeries and fake news.},
	keywords = {artificial intelligence, cybersecurity, deep learning, Deepfake, fake news},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1282},
	url = {timreview.ca/article/1282},
	author = {Mika Westerlund}
}
@article {1139,
	title = {Convergent Innovation in Food through Big Data and Artificial Intelligence for Societal-Scale Inclusive Growth},
	journal = {Technology Innovation Management Review},
	volume = {8},
	year = {2018},
	month = {02/2018},
	pages = {49-65},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {Inclusive innovation has not yet reached societal scale due to a well-entrenched divide between wealth creation and social equity. Taking food as the initial test bed, we have proposed the convergent innovation model to address such challenges still facing 21st century society by bridging sectors and disciplines around an integrated goal on both sides of the social-economic divide for innovations that target wealth creation with an upfront consideration of its externalities. The convergent innovation model is empowered by two key enablers that integrate an advanced digital infrastructure with leading scientific knowledge on the drivers of human behaviour in varying contexts. This article discusses the structure, methods, and development of an artificial intelligence platform to support convergent innovation. Insights are gathered on consumer sentiment and behavioural drivers through the analysis of user-generated content on social media platforms. Empirical results show that user discussions related to marketing, consequences, and occasions are positive. Further regression modelling finds that economic consequences are a strong predictor of consumer global sentiment, but are also sensitive to both the actual price and economic awareness. This finding has important implications for inclusive growth and further emphasizes the need for affordable and accessible foods, as well as for consumer education. Challenges and opportunities inspired by the research results are discussed to inform the design, marketing, and delivery of convergent innovation products and services, while also contributing to dimensions of inclusion and economic performance for equitable health and wealth.},
	keywords = {artificial intelligence, convergent innovation, food, social media, user-generated content},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1139},
	url = {http://timreview.ca/article/1139},
	author = {Laurette Dub{\'e} and Pan Du and Cameron McRae and Neha Sharma and Srinivasan Jayaraman and Jian-Yun Nie}
}
@article {1185,
	title = {Impact of Business Intelligence Solutions on Export Performance of Software Firms in Emerging Economies},
	journal = {Technology Innovation Management Review},
	volume = {8},
	year = {2018},
	month = {09/2018},
	pages = {39-49},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {The article is written with the aim of understanding how well software firms in emerging economies perform when exporting their goods. Focusing on Paraguay as a representative context, a multiple-case-study research design was adopted using different sources of evidence, including 15 in-depth interviews with founders, shareholders, and CEOs. The data were analyzed using grounded theory in order to develop patterns and categories, and to understand differences and regularities. The revised Uppsala internationalization process model was used as a theoretical framework. This article highlights the experts{\textquoteright} views of the impact of business intelligence on the export performance of software firms in Paraguay. Although only a few of the interviewees currently use business intelligence solutions to support international strategic decision-making processes, most of them reveal a desire to use them because they expect it will have a positive impact on export performance and international competitiveness. The main factors for selecting a business intelligence solution are transparency of cost and benefits, excellent client service, and an attractive pricing model. The study results apply to all stakeholders who support the impact of business intelligence systems on the export performance of software firms in emerging economies. The article fulfils an identified need and call for research to study the use and impact of business intelligence on the way an emerging country{\textquoteright}s exportation of goods actually performs, and the ability of its software firms to globalize successfully.},
	keywords = {artificial intelligence, business intelligence, emerging markets, global marketing, international business, international entrepreneurship, international management, machine learning, Paraguay, software industry},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1185},
	url = {https://timreview.ca/article/1185},
	author = {Michael Neubert and Augustinus Van der Krogt}
}
@article {1158,
	title = {The Impact of Digitalization on the Speed of Internationalization of Lean Global Startups},
	journal = {Technology Innovation Management Review},
	volume = {8},
	year = {2018},
	month = {05/2018},
	pages = {44-54},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {Lean global startups need to internationalize early and fast. The digitalization of new foreign market development helps them to more efficiently identify new market opportunities in global markets. With this approach, they are saving resources while developing the most attractive markets. This article examines how lean global startups develop new foreign markets more rapidly due to digitalization. Thus, the aim is to understand the impact of digitalization on speed of internationalization of lean global startups. The study addresses a gap in the scholarly literature and a practical need to evaluate new foreign markets and business opportunities more quickly and more regularly and to understand what helps lean global startups react more quickly to opportunities and threats with respect to changing market attractiveness. Furthermore, it outlines why and how digitalization is important throughout the internationalization process. The research followed a multiple case-study design using different sources of evidence, including 73 interviews with senior managers of lean global startups. The findings reveal that digitalization allows lean global startups to increase decision-making efficiency and to optimize strategies and processes for evaluating international markets. The findings suggest that lean global startups can benefit from the use of digital technologies by applying a more efficient foreign market development process with regular reviews and a reduced workflow, by faster mediation between local market realities and strategic goals, by analyzing all foreign markets instead of just a sample of them, and by optimizing decision-making processes including the ability to make long-term, strategic decisions due to better market information. },
	keywords = {artificial intelligence, big data analytics, digitalization, global marketing, international business, international business development, international entrepreneurship, international management, lean global startup, machine learning},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1158},
	url = {http://timreview.ca/article/1158},
	author = {Michael Neubert}
}
@article {1082,
	title = {Using Artificial Intelligence and Web Media Data to Evaluate the Growth Potential of Companies in Emerging Industry Sectors},
	journal = {Technology Innovation Management Review},
	volume = {7},
	year = {2017},
	month = {06/2017},
	pages = {25-37},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {In this article, we describe our efforts to adapt and validate a web search and analytics tool {\textendash} the Gnowit Cognitive Insight Engine {\textendash} to evaluate the growth and competitive potential of new technology startups and existing firms in the newly emerging precision medicine sector. The results are based on two different search ontologies and two different samples of firms. The first sample includes established drug companies operating in the precision medicine field and was used to estimate the relationship between the firms{\textquoteright} innovativeness and the extent of online discussions focusing on their potential growth. The second sample includes new technology firms in the same sector. The firms in the second sample were used as test cases to determine whether their growth-related web search scores would relate to the degree of their innovativeness. The second part of the study applied the same methodology to the real-time monitoring of the firms{\textquoteright} competitive actions. In our findings, we see that our methodology reveals a moderate degree of correlation between the Insight Engine{\textquoteright}s algorithmically computed relevance scores and independent measures of innovation potential. The existence of such correlations invites future work in attempting to analyze company growth potential using techniques founded in web content scraping, natural language processing, and machine learning.},
	keywords = {analytics, artificial intelligence, business intelligence, entrepreneurship, online textual data, precision medicine sector, startup growth potential},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1082},
	url = {http://timreview.ca/article/1082},
	author = {Andrew Droll and Shahzad Khan and Ehsanullah Ekhlas and Stoyan Tanev}
}
