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AI Organizational Learning Through Corporate Venture Capital Using CVC As a Tool for Artificial Intelligence Learning in France and Japan

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AI Organizational Learning Through Corporate Venture Capital Using CVC As a Tool for Artificial Intelligence Learning in France and Japan HEC MONTRÉAL École affiliée à l’Université de Montréal AI Organizational Learning through Corporate Venture Capital Using CVC as a tool for Artificial Intelligence learning in France and Japan Par Guillaume Charron Sciences de la gestion (Option stratégie) Mémoire présenté en vue de l’obtention du grade de maîtrise ès sciences en gestion (M. Sc.) Juin 2020 © Guillaume Charron, 2020 Résumé Le corporate venture capital (« CVC »), ou capital-risque d’entreprise, est une structure corporative d’investissement ayant pris de l’importance dans les dernières années (Brigl et al., 2018). Les entreprises choisissent d’établir un programme de CVC afin d’atteindre une série d’objectifs stratégiques et financiers (Basu, Wadhwa et Kotha, 2016; Maula, 2007). L’amélioration des connaissances est l’un des objectifs stratégiques qu’elles peuvent poursuivre: les programmes de CVC peuvent constituer pour les firmes des sources de savoir externe (Dushnitsky et Lenox, 2005b). En effet, au travers de son activité de CVC, une entreprise gère des prises de participations minoritaires dans de jeunes compagnies innovantes, telles des startups, et peut potentiellement apprendre de celles-ci. Cependant, la manière dont les activités de CVC contribuent aux apprentissages organisationnels d’une entreprise reste largement inconnue. Cette situation est particulièrement vraie lorsque des programmes de capital-risque investissent dans des startups ayant des savoirs complexes, ambigus. Cette recherche a pour objet de répondre à ces questionnements en étudiant le lien existant entre activités de CVC et apprentissages organisationnels. Elle le fait au travers d’une analyse de la contribution des structures de CVC à l’apprentissage de l’intelligence artificielle (IA), un ensemble de technologies réputées complexes, chez leurs compagnies mères. Cette recherche se base sur l’analyse de dix organisations ayant participé à des activités d’IA en France et au Japon, incluant sept programmes de CVC. Les résultats montrent que le CVC permet à une entreprise d’acquérir des savoirs généraux et commerciaux sur l’IA. Les activités de CVC ont permis aux entreprises mères à mieux reconnaître la valeur et l’attractivité de solutions d’IA, à assimiler plus rapidement des solutions d’IA et à traduire des opportunités d’IA en solutions commerciales. Cependant, ces programmes ne peuvent se substituer aux efforts de R&D d’une entreprise, ne permettant ni un transfert de savoir technologique ni une rétention de connaissances d’IA. Ils n’influencent pas par ailleurs directement la création de nouveaux savoirs d’IA. L’ambiguïté des technologies d’IA, quant à elle, n’a qu’un faible impact sur les activités de CVC. Mots-clés: CVC, capital-risque d’entreprise, apprentissages organisationnels, transfert de savoir interorganisationnel, capacité absorptive, sources de savoir externe, IA ii Abstract Corporate venture capital (“CVC”) is a corporate venturing structure that has grown in importance in recent years (Brigl et al., 2018). Organizations establish CVC programs to complete a series of strategic and financial objectives (Basu, Wadhwa et Kotha, 2016; Maula, 2007). Learning is one of such strategic objectives, as CVC programs can be used as external knowledge sources for companies (Dushnitsky et Lenox, 2005b). Through CVC programs, companies manage minority equity investments into young, innovative ventures firms such as start-ups. Using CVC, firms could potentially learn from their innovative partners. Yet, the way and extent to which CVC activities contribute to their companies’ organizational learning remain unclear. It is especially the case when CVC invest in start-ups exploiting intricate and ambiguous pieces of knowledge. This research attempts to answer these questions by studying in detail the relationship existing CVC and organizational learning. It does so by analyzing how CVC activities contributed to their parent companies’ artificial intelligence (“AI”) learning, an intricate and ambiguous set of technologies that has attracted considerable attention in recent years. This paper is based on ten case studies of companies engaged in AI activities in France and Japan, including seven CVC programs. Results show CVC programs enabled their parent companies to acquire general and commercial AI knowledge. Specifically, CVC activities contributed in making their parent companies gain experience, hence learn, in recognizing AI technological opportunities and attractiveness, assimilating AI solutions in their boundaries, and translating AI opportunities into commercial outputs. However, CVC programs cannot substitute internal R&D efforts. They do not transfer any technological AI knowledge to their parent companies, nor do they permit the retention of AI knowledge. Those units do not directly participate to the creation of AI knowledge. Finally, AI ambiguity only has a minor impact on the relation between CVC and AI learning. Key words: Corporate venture capital, organizational learning, inter-organizational knowledge transfer, absorptive capacity, external knowledge sources, artificial intelligence iii 論文概要 コーポレートベンチャーキャピタル（以下「 CVC 」と表記する）は、近年重要性を増して いる企業金融ベンチャー企業の一種である(Brigl et al., 2018)。企業は CVC プログラムを確立 して、一連の戦略的および財務的目標を達成する(Basu, Wadhwa et Kotha, 2016; Maula, 2007)。 企業学習は CVC の戦略的目標の一つだ。CVC プログラムは企業の外部知識源として使用で きる (Dushnitsky et Lenox, 2005b)。CVC のおかげで、企業はスタートアップのような若く、 革新的な起業に公正に投資することができる。CVC を通じて、企業は革新的なパートナー から学習できる潜在的な可能性がある。しかし、 CVC の活動が企業の学習にどのように貢 献するかについては、まだ不明だ。特に、CVC を通じて移転する知識の特徴が学習成果に どのような影響を及ぼすかについては、明確ではない。本論文は CVC と企業間学習との関 係を研究することでこれらの質問に答えようとする。そのために、ケーススタディを使用 して、CVC の活動が親企業の人工知能（ 以下「AI」と表記する ）の学習にどのように貢献 したかを分析する。AI は近年様々な注目が集めている、複雑で曖昧な一連の技術である。 本論文では、 CVC プログラム ７件を含む、フランスと日本における AI 事業を展開してい る企業の 10 件のケーススタディを紹介する。 分析結果によると、 CVC プログラムにより親企業は AI に関する一般的および商業的な知 識を得ることが出来た。具体的には、 CVC の活動は、親企業が AI の経験を積むために貢 献したことが明らかになった。特に、CVC プログラムにより親企業は AI の技術的な機会と 魅力を認識させ、 AI の使用事例を同化させ、技術機会を商業的な成果に変換することも貢 献した。ただし、 CVC プログラムは社内の研究開発に代わるものではないことも分析結果 に示されている。CVC プログラムは、技術的な AI 知識を親企業に移転したり、AI 知識の保 持を許可したりしない。CVC は AI 知識の作成に直接的に参加しない。最後に、AI の曖昧さ は、CVC と AI 学習の関係にわずかな影響しか与えない。 キーワード：コーポレートベンチャーキャピタル、企業学習、企業間学習における知識移 転のプロセス、企業の知職吸収能力、外部知識源、人工知能 iv Table of Contents Résumé ...........................................................................................................................................ii Table of Contents ............................................................................................................................v List of Tables ................................................................................................................................. vii List of Figures ................................................................................................................................ vii Remerciements - Acknowledgements .......................................................................................... viii Chapter 1 Introduction ............................................................................................................ 1 Chapter 2 Literature review ........................................................................................................ 5 2.1 Organizational Learning .................................................................................................. 5 2.1.1 Knowledge .............................................................................................................. 6 2.1.2 Learning in organizations ...................................................................................... 10 2.1.3 Organizational learning sub-processes .................................................................. 17 2.2 Corporate Venture Capital ............................................................................................ 24 2.2.1 External sources of knowledge .............................................................................. 24 2.2.2 Defining CVC ......................................................................................................... 31 2.3 Artificial Intelligence ..................................................................................................... 41 2.3.1 What Intelligence? ................................................................................................ 41 2.3.2 AI’s current impact ................................................................................................ 47 Literature review summary ...................................................................................................... 51 Chapter 3 Conceptual framework ............................................................................................. 52 3.1 Theoretical background ................................................................................................ 52 3.2 Research sub-questions ................................................................................................ 54 3.3 Conceptual framework model....................................................................................... 62 Chapter 4 Research Setting ....................................................................................................... 63 4.1 AI Context ..................................................................................................................... 63 4.2 CVC context .................................................................................................................. 66 Chapter 5 Methodology ...........................................................................................................
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