Discovering IoT implications in business and management: A computational thematic analysis
Introduction
Internet of Things (IoT) has flourished over the last decade as a new wave of digital transformation, which enables real-time sensing, collecting and sharing data. The unique features of IoT like ubiquity have enabled the possibility of developing advanced applications across many domains. The momentum IoT has generated makes it an ideal frontier for driving technological innovation (Siow et al., 2018), garnering significant attention from both practitioners and scholars. IoT is perceived as a disruptive innovation given its potentiality to truly reshape our world (Manyika et al., 2013). Pervasive applications of IoT are dramatically transforming many aspects of societies and economies such as healthcare (Pang et al., 2015; Tuan et al., 2019), transportation (Davidsson et al., 2016), logistic (Hopkins and Hawking, 2018), manufacturing (Birkel et al., 2019; Hasselblatt et al., 2018), and tourism (Byun et al., 2017; Gretzel et al., 2015). It is estimated that the IoT market size will reach $1.2 Trillion worldwide by 2022 (IDC, 2018). However, IoT's extensive publicity and promising future do not guarantee its widespread success, since many concerns and potential issues of gaining actual value of IoT are not yet fully known (Nicolescu et al., 2018). IoT mass adoption and actualizing its values depend not only on technological advances but more on understanding its business and managerial needs and challenges. Porter and Heppelmann (2014) maintain that we need to identify the dynamics of IoT technologies from business and management perspective to survive and gain competitive advantage during the technological transformations.
The diffusion trend of IoT leads to a call for studies to advance our understanding of research on managerial and entrepreneurial opportunities of this disruptive innovation (Clarysse et al., 2019). Despite exponentially expanding opportunities arising from IoT and ever-growing attention it attracts among scholars, practitioners, and the general public, a critical literature review indicates the lack of systematic and rigorous study on the business and management perspective of this technology. Mostly, the extant literature has taken a narrow view to discuss specific aspects of IoT business and management such as generating value from IoT data (Hajiheydari et al., 2019), concentrating on IoT applications in servitization (Rymaszewska et al., 2017), or providing a descriptive business model for IoT (Dijkman et al., 2015). This gap highlights the need for an integrative study that considers the current body of knowledge to connect the disciplinary perspective and insight around IoT studies with business and management identity.
There are several grounds that signify examining IoT from the business and management lens is both timely and essential. First, the ever-increasing growth of investment, the predicted market size (IDC, 2018), and the continuous introduction of pervasive applications (Forbes, 2019) necessitate understanding of IoT business implications. Further, calls continue for the ‘Managerial and Entrepreneurial Opportunities and Challenges of IoT’, principally based on the role of this disruptive technology in generating new venture opportunities, shifting the nature of competition, and eroding the traditional business models (Clarysse et al., 2019). Finally, due to growing expansion of IoT applications and related publications, researchers suggest quantitatively examining the related literature (Lu et al., 2018), to explore the hidden thematic structure of IoT research (Yoon et al., 2018), and IoT issues associated with managerial and organizational areas and theories (Mishra et al., 2016).
Previous studies have mainly focused on ‘general IoT research domain’. By applying either quantitative or qualitative methods, researchers attempted to examine the generic IoT knowledge field and objectively or subjectively analyse the literature. Co-word analysis (Kim and Kang, 2018; Yan et al., 2015), co-citation analysis (Ng et al., 2018), bibliometrics (Mishra et al., 2016), and scientometrics approaches (Erfanmanesh and Abrizah, 2018) are some of quantitative methods have been used to explore IoT research domain. On the other stream, qualitative and mainly literature review approaches have been followed to examine the IoT study domain (e.g., Atzori et al., 2010; Li et al., 2015; Siow et al., 2018; Lu et al., 2018). It thus appears that scholarly attempt with direct focus on uncovering the intellectual structure of IoT literature from the business and management perspective is largely disregarded. This study contributes to advancing the current discourse on IoT in particular considering business and management issues more holistically, by integrating, representing and synthesizing current knowledge through an innovative methodological approach.
The main goal of this systematic and rigorous research is to map and link the knowledge landscape of IoT in business and management domains. To this aim, the present study seeks to: (i) extract the inductive topical framework to portray the IoT research field in business and management, and more specifically for the highly focal domain of ‘business model’; (ii) analyse and explain the main business and management latent themes and sub-themes in the research field of IoT; and (iii) highlight the trend of business and management studies in the IoT field to detect novelty and emergence. To address these objectives, we analysed the corpus of IoT research in the business and management disciplines applying an explanatory sequential mixed-method approach. This study thereby provides three key contributions. First, it drives and presents phenomenon-based constructs and grounded conceptual relationships in the IoT literature on business and management. Second, we explore and discuss the related latent subjects of these constructs and their relationships, with special attention to the business model theme. Finally, we provide theoretical contribution by proposing research agenda for future study avenues in this context, based on the identified thematic map.
Section snippets
Research method
As quantitative and qualitative methodological approaches both have certain weaknesses (Gioia et al., 2013), researchers have called for new methods to examine organizational phenomena (Taras et al., 2009). Some propose combining them to take the advantages of both methods, addressing their limitations, and overcoming the trade-off between performing large-scale quantitative analytics and gaining in-depth qualitative insights (Creswell and Clark, 2011, p. 17; Schmiedel et al., 2018). Thereby,
Results
Fig. 2 presents the global view of the topic model on IoT business and management research area. This view visualizes the output of topic modelling, wherein circles represent topics in a two-dimensional plane. Areas of the circles are proportional to the relative prevalence of the topics in the corpus. The centres of circles are estimated by calculating the distance between topics and further projected onto a two dimensions space by using multidimensional scaling to reflect the inter-topic
Theoretical implication and future research
Our findings contribute to the literature on business and management of IoT in three ways. First, the findings of this study uncover and present a thematic map of IoT research streams in business and management domains. This study is a response to a call by Lu et al. (2018) that highlight a need for a more quantitative approach to drive and present the inductive classification framework for eliciting the latent structure of IoT extant literature. To map out a broad and rich picture of the
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