A couple of years ago, I published a blog post giving an overview of the academic work that I had published recently. That led up to very interesting conversations and collaborations. So, I thought that I should write a short update on what I have published in the last couple of years. Let’s start with the journal articles.
- Quinton, S., Canhoto, A.I., Pera, R., Budhathoki, T. & Molinillo, S. (2018). Conceptualising a digital orientation: antecedents supporting SME performance in the digital economy. Journal of Strategic Marketing, 26(5), 427-439. DOI: http://dx.doi.org/10.1080/0965254X.2016.1258004
Summary: Digital technologies have dramatically changed the organisation and marketing environments. Whether this presents an opportunity or a challenge for small and medium organisations depends on how these organisations approach it, strategically. Specifically, organisations that are guided by a combination of market, learning and entrepreneurial orientations are well-positioned to take advantage of the opportunities presented by digital technologies because they adopt attitudes and behaviours that support the generation and use of market insight, proactive innovation and openness to new ideas. We call this combination the digital orientation (DO), and present a set of propositions that facilitate its development. This paper creates value both through the conceptualisation of the DO and the outlining of the implications for strategic marketing management of understanding the strategic factors supporting or hindering the performance of small and medium enterprises in the digital economy.
Keywords: Digitalisation, SMEs, strategic orientation, strategic marketing, digital orientation
You can find this paper here.
- Merendino, A., Dibb, S., Meadows, M., Quinn, L., Wilson, D., Simkin, L. & Canhoto, A. I., (2018). Big Data, Big Decisions: The Impact of Big Data on Board Level Decision-Making. Journal of Business Research, 93(December), 67-78. DOI: https://doi.org/10.1016/j.jbusres.2018.08.029
Summary: Big Data (BD) has the potential to ‘disrupt’ the senior management of organisations, prompting directors to make decisions more rapidly and to shape their capabilities to address environmental changes. This paper explores whether, how and to what extent BD has disrupted the process of board level decision-making. Drawing upon both the knowledge-based view, and cognitive and dynamic capabilities, we undertook in-depth interviews with directors involved in high-level strategic decision-making. Our data reveal important findings in three areas. First, we find evidence of a shortfall in cognitive capabilities in relation to BD, and issues with cognitive biases and cognitive overload. Second, we reveal the challenges to board cohesion presented by BD. Finally, we show how BD impacts on responsibility/control within senior teams. This study points to areas for development at three levels of our analysis: individual directors, the board, and a broader view of the organisation with its external stakeholders.
- There is a shortfall in directors’ capabilities for dealing with Big Data.
- Board cohesion can be disrupted by Big Data, compromising the decision-making process.
- Boards need to develop cognitive capabilities and find new ways to make decisions in the Big Data era.
- Big Data provides firms with opportunities to enhance their adaptive capabilities.
- Boards need to work in new ways to meet the challenges that Big Data can present.
Keywords: Boards, Directors, Big data, Knowledge-based view, Capabilities, Decision making
- Canhoto, A. I. & Clear, F. (in press). Artificial Intelligence and Machine Learning as business tools: factors influencing value creation and value destruction. Business Horizons, 63(1)
Summary: Artificial intelligence (AI) and machine learning (ML) may save money and improve the efficiency of business processes, but these technologies can also destroy business value, sometimes with grave consequences. The inability to identify and manage that risk can lead some managers to delay the adoption of these technologies and thus prevent them from realizing their potential. This article proposes a new framework by which to map the components of an AI solution and to identify and manage the value-destruction potential of AI and ML for businesses. We show how the defining characteristics of AI and ML can threaten the integrity of the AI system’s inputs, processes, and outcomes. We then draw from the concepts of value-creation content and value-creation process to show how these risks may hinder value creation or even result in value destruction. Finally, we illustrate the application of our framework with an example of the deployment of an AI-powered chatbot in customer service, and we discuss how to remedy the problems that arise.
Keywords: Artificial intelligence, Machine learning, Value creation, Value destruction, Decision making, Technology adoption, Enterprise value, chatbot
You can find this paper here.
I also contributed two articles to the website, The Conversation, which aims to support a better understanding of current affairs and complex issues by sourcing articles from university and research institute experts.
- Canhoto, A.I. (2019) ‘Facebook ten year challenge: how our need to belong trumps our distrust of social media’, The Conversation, published 6th February 2019
- Canhoto, A.I. (2017) ‘What Jawbone’s demise can teach the fitness wearable market’, The Conversation [here], published 13th July 2017
So, this is what I have been working on. Do reach out if you want to learn more about these articles, or to discuss opportunities to work together.