How do incumbent energy firms realise the potential for value creation from the adoption of smart meters? A study of organisational affordances, organisational capabilities, and generative mechanisms in the UK energy sector

Big data technologies are advanced technologies that enable data to be collected in real-time at large volume and at low cost. Anecdotal evidence suggests that insights derived from big data have the potential to transform business strategies and business models and thereby improve marketing, product and service development, human resources, operations, and other core business functions. As such, there has been significant academic and practitioner interest in studying big data and value creation in organisations. However, much of the previous research has focused on studying the relationship between big data resources and investments and their impact on firm performance, and therefore have overlooked the processes and mechanisms through which firms realise the value creation potential from big data technologies. Lack of knowledge and understanding on how organisations realise the value creation potential may explain why some organisations still fail to reach their strategic goals despite investing substantial resources into big data technologies. Against this backdrop, this thesis aims to address this research gap by seeking to understand how organisations realise the value creation potential from adopting a specific big data technology (i.e., smart meters) in the UK energy sector. To do so, I collect qualitative data (interviews, company documents, news articles, governments reports, and publicly available documents) in two case study organisations: BlueHouse and GreenWorks (anonymised names). Using affordance theory lens, I provide empirically grounded insights into the opportunities for value creation that smart meters provide (organisational affordances), explain how these value creation opportunities are realised (organisational capabilities and actualisation enablers), and explain what constrains these value creation opportunities from being realised (generative mechanisms). My findings extend affordance theory by empirically examining the role of organisational capabilities and generative mechanisms in the affordance actualisation process. They also provide meaningful insights on the process of realising the value creation potential from the adoption of a new technology within incumbent firms

Realising Value from Big Data Technology Adoption: Understanding the Role of Organisational Capabilities in the Affordance Actualization Process

The adoption of big data technologies presents organisations with many value creation opportunities that can transform and improve their business. Much of the research today focuses on big data value creation (what value big data technologies offer), whereas limited research focuses on big data value realisation (how big data value is realized). We aim to fill this research gap by addressing the following research question: how do organisations effectively realize value from the adoption of a new big data technology? We do so by adopting an affordance theory lens and empirically examine the adoption of smart meters (a big data technology) in the UK energy sector. We introduce the concept of actualization enablers, and our findings provide empirically grounded insights into the role of organisational capabilities and actualization enablers in the big data value realization process (affordance actualization). Furthermore, our findings provide important and relevant theoretical and managerial implications

Unveiling the (biased?) nature of mystery shopping in the tourism service sector

Mystery shopping is the practice of using trained shoppers to anonymously evaluate customer service, operations, employee integrity, merchandising, and product quality. This paper contributes with new insights on the role of mystery shoppers and the potential biases that can characterize their incognito reviews of services. The study is set in the context of tourism services, and uses an interpretative phenomenological approach. Prior studies raised issues about the reliability and validity of the mystery shopping technique, but failed to address this problem from the perspective of the mystery shoppers themselves. In this exploratory paper we address this lacuna, and offer a series of insights for both theory and practice. First, we develop a phenomenological definition of the mystery shopping experience. Second, we describe and classify seven distinct biases recognized by mystery shoppers during their work. We conclude with implications for theory, practice and future research

Realising Value from Big Data Technology Adoption: Understanding the Role of Organisational Capabilities in the Affordance Actualization Process

The adoption of big data technologies presents organisations with many value creation opportunities that can transform and improve their business. Much of the research today focuses on big data value creation (what value big data technologies offer), whereas limited research focuses on big data value realisation (how big data value is realized).We aim to fill this research gap by addressing the following research question: how do organisations effectively realize value from the adoption of a new big data technology? We do so by adopting an affordance theory lens and empirically examine the adoption of smart meters (a big data technology) in the UK energy sector. We introduce the concept of actualization enablers, and our findings provide empirically grounded insights into the role of organisational capabilities and actualization enablers in the big data value realization process (affordance actualization). Furthermore, our findings provide important and relevant theoretical and managerial implications