Service user perspectives on delivering social innovation : an implication of the internet of things for business

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Service User Perspectives on Delivering Social Innovation: An

Implication of the Internet of Things for Business

Amsterdam Business School

MSc. Business Administration

Track: Digital Business

Master Thesis

Author: Olga Maria Plessa

11817259 om.plessa@yahoo.com Supervisor: Dr. Somayeh Koohborfardhaghighi s.koohborfardhaghighi@uva.nl Second reader:

Prof. Dr. Peter van Baalen

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Statement of originality

This document is written by Olga-Maria Plessa, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Olga Maria Plessa – Amsterdam 22/06/2018

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ACKNOWLEDGEMENTS

I would like to take a second to thank all people who helped and supported me through the realization of this thesis. First of all I would like to express my sincere gratitude to my supervisor and guide to this journey Dr. Somayeh Koohborfardhaghighi for providing me with all the necessary tools that made me able to finish this research and the uncountable patience she showed in withstanding me. Then I would like to express my special gratitude to my family for supporting me throughout my time at University and for always being by my side and believing in me. I could not forget to thank my friends, or else the family I have chosen, for being the source of my encouragement and the pillar of everything I have ever needed. At the same time I would like to offer my gratitude to my boyfriend, for being present at all the difficult times and for inspiring me to do the best I can. Finally I would like to thank the University of Amsterdam for giving me the opportunity to conduct this research and for making this journey so unique.

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Abstract

Traditionally, business models have been referred to as the “architecture, design, pattern, plan, method, assumption, and statement” of businesses (Morris, Schindehutte, & Allen, 2005). While the potential of innovation and business models contribution to business revenue is undisputed, little is known about their exact role in the societal transition. Sociocultural concerns regarding innovation are increasing, and this study will look at these concerns through a promising technology, heavily associated with the everyday life: the Internet of Things. Unsurprisingly, IoT creates many opportunities and drives business growth by increasing the quality and speed of processes and the customer satisfaction. However, technology has no ethics, this means that it can serve both useful social purposes or be harmful to society (Brown, & Crump, 2013). The present study focuses on Stakeholder Canvas (Joyce & Paquin 2016) for delivering social innovation based on new IoT driven business models. With the help of an empirical study this research captures the service users‘ priorities in delivering social innovations the significance of different building blocks of the Social Stakeholder Canvas are estimated. Our experimental results show that three building blocks, which are mainly Social Impact (i.e., Privacy and Security), Social Benefits (i.e., Quality of Life), and Scale of Outreach (i.e., Adaptivity and Transparency), are the most influential constructs in delivering social innovation. Furthermore, The findings of this study can provide practitioners with guidelines and reasons to implement new IoT applications for delivering social innovations for the society.

Keywords: Internet of things – Social Value – Business model – Social Innovation – Stakeholder Model Canvas

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Table of Figures

Figure 1 - Stakeholder Model Canvas (Joyce & Paquin, 2016)_______________________________________ 30 Figure 2 - Conceptual Framework _____________________________________________________________________ 30 Figure 3 - Relative Importance of building blocks ____________________________________________________ 42 Figure 4 - Stakeholder model framework for IoT applications with a relative importance of specific types. ___________________________________________________________________________________________ 43

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Table of Tables

Table 1 - Overview of the literature review... 21

Table 2 - Definitions of the building blocks within the Stakeholder Model Canvas (Joyce& Paquin, 2016) ... 25

Table 3 - Descriptive Statistics of survey respondents ... 34

Table 4 - Correlation Matrix ... 38

Table 5 - Exploratory Factor Analysis ... 40

Table 6 - One sample t-test of building block ... 62

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1. Introduction

Business model describes the way the company creates, delivers and seizes value, or, more simply, how it will fulfill its purpose. The business model is essential for the business to outlive and grow, always being an integral part of a company. The business models started by being oriented towards output maximization (product-oriented), but traditional enterprises have altered into caring more about innovation and delivering services (Gebauer, Joncourt, & Sau, 2016). Formerly, financial goals have been the primary focus of such models, but business sustainability and shared values have been increasingly essential to business plans recently (Rouse, 2013).

The rise of technology, as we observe, cannot leave the business sector and everything it involves unaffected. Demil and Lecocq (2010) point in their article the two different uses of the business model concept: the first is the static approach, which refers to the importance of coherence between the core business model components and the second is the transformational approach which makes the business model the tool to create change through innovation. Technology and innovation have created a new way for companies to work and compete. Firms need to change, adapt and innovate their business models in order to seize value from technological innovation but it also works the other way around when new business models create renovation by starting to meet customers' concerns and desires (Hacklin, Björkdahl, & Wallin, 2017). According to Baden-Fuller & Haefliger (2013), the connection between business model and technology is two-way. As business model changes it enables and promotes innovation.

Even though there have been many definitions for business models, the majority of them include customer value creation as maybe the more obvious core element. Another core element, however, which is equally important but less apparent

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is interaction. By interaction, we mean that the business model construction is also externally oriented and highlights the relationships that the firm has or needs to have with the different actors in its value network (Nenonen, & Storbacka, 2010). With technological advancements, value is no longer perceived within firm boundaries created in a linear process; value creation is becoming more interactive, therefore, co-created between various constituencies (Järvi, & Pellinen, 2011). Those business actors are any individual, group or machine that interacts with the business (such as customers, partners, and suppliers). To improve value co-creation in a network, there is a need for growth of ecosystems and, subsequently, the number of applications and developers in the network and to become successful they merge their collaborators' interests with corporate knowledge and resources.

In a digital society, digital co-creation becomes a business standard by combining business expertise and technology and creating new value together with customers and network partners to shape a high-value future. Social Innovation requires the digitalization of customer co-creation activities and aims to realize that value co-creation possibilities are relatively higher as they go beyond geographic constraints (Funaki, 2017). While the potential of innovation and business models to contribute to business revenue is undisputed, little is known about their exact role in the societal transition. Sociocultural concerns regarding innovation are increasing, and this study will look at these concerns through a promising technology, heavily associated to the everyday life: the Internet of Things (IoT).

In the past few years’ mechanisms have been created to enable communication between people and things, which interact with each other to reach common goals. Eventually, this led to the creation of a worldwide network of interconnected physical objects equipped with sensors. This network, used as a web service to develop new

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applications or improve existing ones, is called Internet of Things (Glova, Sabol, & Vajda, 2014). IoT is included by the US National Intelligence Council in the list of six ‘‘Disruptive Civil Technologies" with popular demand and future opportunities like contributing to economic development arising (Li et al., 2015). In other words, we need to think to what extent does IoT impact society and how it can add to social value. Considering the above line of arguments we need to reflect on which social changes are of first priority from the users’ point of view and what is the role of IoT in their materialization.

Particular focus should be put on investigating social implications, intended or not, and facilitating the understanding of a subject as broad as the change in society. Even though there is already much literature on the IoT, there is enormous potential for social science research, given the way the IoT changes business practices and innovation, privacy, governance and the daily life at large (Oxford Internet Institute, 2013). The uncertainty surrounding the IoT’s future influence makes it significantly harder to question its profound impact on society and business. Nevertheless, it is undoubtedly a subject worth researching as its analysis can bring new insights regarding the direction that IoT could take towards social innovation.

The present study focuses on Stakeholder Model Canvas (Joyce & Paquin 2016) for delivering social innovation based on a new IoT driven business model. Therefore, the following research question will be addressed: How does a better understanding of service users’ priorities improve the contributions of IoT driven business model in delivering social innovation?

We aim to perform a proper literature review on the topic of social innovation and to identify the factors that are important from the service users’ perspectives. We identify relevant components for each building block of Social Stakeholder Canvas

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according to the literature review on the topic of IoT and social innovation. Later with the help of identified components we deliver a novel framework, which has the potential to guide new IoT driven business models in delivering social innovation. It can also provide practitioners with guidelines and reasons to implement new IoT applications for delivering social innovation in our society. Our proposed framework will be tested with real data captured from 590 responses of service users resulting in 327 observations. We perform exploratory factor analysis to test the framework’s structure and we capture the significance of the identified factors.

The results of this study unveil that some building blocks are significantly more important than others (i.e Social Impacts, Social Benefits, Scale of Outreach), derived from the importance of their components (i.e Privacy, Security, Quality of life, Adaptivity). Items such as Surveillance have negatively scored as they were defined as against the users values and while others such as Freedom vary depending on the gender. The research performed in this thesis has several implications. Our proposed framework has the potential to guide new IoT driven business models in delivering social innovation in line with what service users expect to receive. It expands IoT literature by looking into different kinds of social value created by its implementation as well as highlighting IoT’s benefits/drawbacks for society. It can also provide practitioners with guidelines and reasons to implement new IoT applications for delivering social innovations in our societies.

This thesis proceeds as following. In section 2 and 3, an overview the existing literature will be performed, and the conceptual framework of the research is presented. Description of the data and our research methodology are discussed in section 4. The obtained results of our experiments are delivered in section 5. Finally, I conclude this thesis in chapter 6 where a discussion over our findings is presented.

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2. Literature Review

In this section, relevant literature on the topics of IoT driven business models and social innovation are covered. This literature review section will be divided into three parts, which will point to the fundamental concepts in our study. Those fundamental concepts are specifications of business models based on the Internet of things, IoT and social innovation and social value creation through the IoT driven business models. Definitions of the above topics as well as past literature are allocated in different subsections.

2.1 Business Models based on the Internet of Things

Adopting Internet of Things (IoT) has been a significant worldwide trend for companies that will shape the future business. As Gartner published in December 2013 “The Internet of Things will include 26 billion units installed by 2020. IoT product and service suppliers will generate incremental revenue exceeding $300 billion, mostly in services, in 2020. It will result in $1.9 trillion in global economic value-add through sales into diverse end markets.” (Forecast: The Internet of Things Worldwide, 2013). Overall, connected products enable companies to provide better service at a lower cost and minimize response time (PTC Inc., 2017). In addition to that, IoT platforms are under pressure to generate financial returns for enterprises as Return on Investments (ROI) drives an essential outcome for businesses. Smart and interconnected items allow revolutionary technologies to open up the scope of new business models for capturing value. Therefore, the need for creation of business models, where IoT can adapt and create benefits for the company and the society has derived.

The role of business models is to provide a description of how a firm organises itself to create and distribute value in a profitable manner and to

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demonstrate how to do something so that the results will come out right (Baden-Fuller, Morgan, 2010). The rise of IoT provides the need of business models that can exploit the benefits of its application (Dijkman et al., 2015). As it generates new opportunities Ju, Kim & Ahn (2016) claim that it is indispensable for companies to identify the most critical factors of their business model to create value through IoT, providing this way better IoT service and value to their customers. Metallo et al., (2017) state that business modeling is a mechanism to connect firm technology and customer needs by enabling organisations to exploit the value potential set in new technologies and converting it into market outcomes. Furthermore, smaller and younger companies are more concentrated in a specific technological area (such as IoT) and tend to put more emphasis on developing partnerships, rather than building internal capabilities. Such orientation towards external interaction might lead, in capturing value from the continuous stipulation and exploitation of knowledge, information, resources, and abilities from the ecosystem partners (Metallo et al., 2017).

According to Glova, Sabol, & Vajda (2014), the business model for IoT can be an important element to unite the technical innovation with the economic perspective. The basic principles of such innovative mindset for designing IoT-oriented business models are the new nature of products, which should forecast user needs, and outspread product and service personalization (Metallo et al., 2017). Moreover, Westerlund, Leminen & Rajahonka (2014) argue that the change of focus from the IoT being primarily a technology platform to viewing it as a business ecosystem drives the evolution of business perspectives to the IoT. They explicitly explain that "the concept of business model, which is traditionally associated with a single organization's business model, could be replaced with the term ‘value design',

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which is better suited to ecosystems" (Westerlund, Leminen & Rajahonka, 2014). Finally, the article indicates that IoT's implementation challenges can be overcome by using a business model design tool that considers the holistic identity of the IoT.

In their article, Dijkman et al. (2015) chose to use the Business Model Canvas as a framework for the IoT applications because it is based on a meta-analysis of the framework. The Business Model Canvas, which was initially proposed by Alexander Osterwalder, is a template with nine business model building blocks, which can describe the activities of a company and how they can be changed in order to add value to the firm. This framework designs the business model as a template for the company and is frequently used in business environments, repeatedly cited in the literature. This study can serve as a guide on how the IoT applications could configure the business model.

Although some attempts have been made to explain the changes in the business models when applying the Internet of Things, the issue of social value has not been addressed yet.

2.2 IoT and social innovation

Increasing environmental pollution and sequentially global warming are now concerns of social, economic and political groups. While the natural resources are decreasing, concern grows about the deteriorating environment. Therefore, creating sustainable cities of the future becomes necessary and it requires the adoption of Internet of Things technologies through different applications. This will be achieved in new ways, in which things and objects will become more reliable, autonomous, resilient and smarter (Kyriazis, Varvarigou et al., 2013). In their paper Kyriazis, Varvarigou et al. present sustainable IoT applications. One example would be the intelligent heat and electricity which is an application allowing to reduce power on

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demand by communicating to the end users the energy consumption by real-time reporting. This would allow households to have control of their energy consumption by having regular and detailed information regarding their bills and thus reduce sufficiently their costs. IoT technology, through the corresponding sensors, will utilize information in order to adjust, predict and detect different situations avoiding behaviour that may have caused events such as fire. Furthermore, users will be immediately informed in both cases of unusual consumption and about how to optimize energy saving (Kyriazis, Varvarigou et al., 2013).

Innovation can have several meanings from a simple new way of doing things to a technological breakthrough. This means that it can incorporate any new way to generate value for an organization and for other stakeholders (i.e customers and suppliers). Therefore, innovation is directly linked to value creation (Polat, 2012). Social innovation can be seen through many views: The one highlights the product and process role for social purpose. The other is related to the entrepreneurial scope, where innovation plays a crucial role in helping in the development and the founding of social enterprises (Boons, & Lüdeke-Freund, 2013).

2.2.1 Corporate Social Responsibility through IoT

Being considered as an area of experimentation and innovation, social entrepreneurship (SE), can potentially contribute to entrepreneurship by providing new insights, as well as to the wider social sector. The combination between SE and corporate social responsibility (CSR) can assist discovering new types of collaborative value creation to help achieve sustainable development (Seelos, & Mair, 2005). Redesigning a business model is the essential method to improve its sustainability while creating social and environmental value. The core aim of sustainable business models is to overstep the creation exclusively of economic value

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and include different forms of value considering other types of stakeholders. (Bocken, Short et al., 2013). Innovation has been a popular topic when it comes to the business models literature, as a feature that can create competitive advantage and a tool that renovates industries. Even though technological innovation is mainly “jobs-to-be-done” and organizational innovation is mainly a form of introspection, social innovations are the ones offering solutions for various stakeholders (Boons, & Lüdeke-Freund, 2013).

A common characteristic of organisations that are victorious in progressing their business models to generate value on the cross of time to create is that they behave with an entrepreneurial mindset. The organisations that unveiled sustainable value creation have kept changing and innovating their business model through continuous experimentation and exploitation of new business opportunities (Achtenhagen, Melin, & Naldi, 2013). Socially oriented organisations and entrepreneurial companies are non-identical to the traditional nonprofit organization as they enact hybrid nonprofit and profitable activities (Dart, 2004). Many authors have argued about how social businesses are planned to efficiently combine both social and economic mission, concepts usually detained as conflicting (Wilson, & Post, 2013). The concurrent making of social and economic value complexes the demands on an organization. Wilson, & Post (2013) argue that the phenomenon of social businesses is linked to both concepts of CSR and SE. CSR appears when a company behaves purposively to increase social welfare. Despite the fact that supporters of CSR are suggesting firms to be thoughtful of all layers (economic, social and environmental), eventually only one layer usually is taken more into consideration, the economic one.

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2.2.2 Shared Value through IoT

According to Polat (2012), there is a new exploration flow that businesses should take into consideration and practice, which recommends the shared value and supports that it should be the target of any innovation. Following this, he states that innovation is currently the main strategy that helps companies survive and develop in the aggressive global market. Additionally, he entered the concept of co-innovation, where ideas from various sources are used in a different way to provide value for the stakeholders and thus experience network effects from value creation. This is assignable to the fact that key enablers of effective innovation are entities like culture, direction and strategic vision (Polat, 2012). The idea of shared value gives emphasis on linking social and financial progression, and it is believed to have the power and potential to release the next wave of global improvement. Two authors Porter and Kramer (2011) claim that shared value recognizes the deep societal needs and not only the economic needs. They argue that companies define value far too narrowly and don’t take enough into consideration long-term performance and as they say, “shared value will drive the next wave of innovation and productivity” as it will reconnect societies and business needs. This is done, according to both authors, when financial benefit also creates societal value by confronting challenging situations, and it is different from CSR (Corporate Social Responsibility) as it is essential and not supplementary to business activity. CSR decisions are driven by the values of stakeholder, while shared value starts from the idea that social issues can be directly in a company's economic interest. The idea of shared value reconstructs the boundaries of capitalism and unleashes different ways to serve contemporary needs, expand markets and improve efficiency. The overlap between those who seek shared value and the social innovators seems inevitable, since social innovation is shaped and

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affected as much from market failures as by social and environmental needs.

2.2.3 Value Co-creation through IoT

Technology touches the human life and creates new insights and possibilities for change. By bringing together stakeholders of an enterprise and combining them with the digital economy you can create new value opportunities, naming digital co-creation. This makes business more innovative, improving lives and delivering a brighter future. The digital platform of a company will extend the business to partners and developers and enable the company to interact globally with ease. Digital co-creation is the enabler to unlocking people's creativity and building new business models (Fujitsu, 2017). Value co-creation, on the other hand, contributes in the cooperation of different stakeholders to gain more benefits in different procedures. The concept of value co-creation expects organisations, besides generating value for themselves, to also create value to all stakeholders participating in co-creation procedures, as well as for the environment in which they function. Hence, co-creation enhances sustainable social development. Co-creation can guide institutes such as governance as well as development, and sustainability to a superior position, whilst developing wealth globally (Aquilani, Silvestri, & Ruggieri, 2016). Ramaswamy, (2009) examines in his paper that establishing a co-creation model, especially in traditional firms, requires people in managerial positions to accept the new mindset. An eligible co-creative company has to change the mindset and nature of the relationships between the management of the organization and the co-creators of this value, which are the employees, the customers and the other partners.

When becoming a co-creative organization there is a change in all relationships between the company and the co-creators of value (such as stakeholders, customers and employees). Even though several organisations call themselves

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customer-centric, very few of them literally put the customer at the core of the innovative operationalizations (Ramaswamy, 2009).

2.3 Social value creation through business model

As sustainability concerns are on the increase, firms start engaging in sustainability-oriented innovation. Sustainability necessitates progressing from the development of a product to a broader perspective that provides social wealth. Society nowadays expects enterprises to be socially responsible (Herrera, 2015). According to Bidmon, & Knab (2017) scholars have become increasingly interested in understanding societal transitions, which are large-scale and long-term changes of systems that fulfill societal functions and highlight the importance of business models for achieving systemic change. They even argue that "novel business models have a greater potential to achieve systemic change than technology" (Bidmon, & Knab, 2017). There is a need to investigate business models in order to get a better understanding of what drives the development these business models and how they could have a more human intention. Biloslavo, Bagnoli & Edgar (2017) claim that existing business frameworks exclude natural and social aspects and tend to neglect interrelations between economic and non-economic actors and need to incorporate the natural environment and future generations in the creation of value.

By adopting a holistic perspective, sustainable development requires that environmental, social and economical approach to be dealt with jointly and simultaneously (Rauter, Jonker, & Baumgartner, 2017). Sustainable business model archetypes are introduced to describe groupings of mechanisms and solutions that may contribute to building up the business model for sustainability. Bocken, Short et al. (2014) deliver a sustainable business model (SBM) with a “triple bottom line approach” (economic, environmental and social layer). They support that sustainable

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business models perform adequately in order to coordinate the various innovations with “system-level sustainability” (Bocken, Short et al., 2014). Upward & Jones introduced the novel SSBM framework, which has the outline of a business model, but relates to a business with intense sustainability. They define strongly sustainable businesses, as the ones that have a triple bottom line approach to create value, that would not harm the planet, but will only create social and financial wealth. In their paper, they used Osterwalder’s (2004) Business Model Ontology as a reference to identify the minimum required changes that could be referred to describe models of sustainable enterprises that include the possibility of “flourishing”. (Upward, & Jones, 2016). Bocken Short et al., (2013) conceived a value-mapping tool, which helps creating value delivery to maintain sustainability in business models. Its purpose is to motivate discussion and therefore the idea generation. The tool has a circular form, which evolved due to continuous discussions as well as a pilot to help identify the interpretation of value, promote equal consideration of all stakeholders, and investigate how interrelated are their interests.

Joyce, & Paquin (2016) introduce a tool to explore a sustainability-oriented business model, the Triple Layered Business Model Canvas (TLBM). TLBM complements the original Business Model Canvas by adding environmental and social layers, which interconnect between them "horizontally" (by exploring each value individually) and "vertically" (by integrating value creation across the layers). TLBM is meant to incorporate a holistic perspective of the entire business model and supports a more creative, sustainable development by consolidating environmental and social value creation to businesses.

The social layer of TLBM is developed on a stakeholder’s approach, which concerns the groups of individuals that can be influenced by the actions of a company

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(for example the community, the customer, the employees, etc.). Another view on stakeholders divides them as primary or secondary. Primary are those whose involvement is essential for business survival; for instance, employees, suppliers, customers, investors and shareholders. Secondary stakeholders are the ones not engaged in transactions with the main institution and are not crucial for its survival, such as the media, trade associations and non-governmental organizations (Maignan, Ferrell, & Ferrell, 2005). This was decided because the stakeholder perspective is broad and flexible and some of the more significant social impact factors have also been using the same angle.

Emphasis on social value creation has increased because first of all, it makes customers want to buy from these enterprises; secondly, employees prefer working for them, thirdly investors invest more in them and lastly entrepreneurs are eager to start them (Kuratko et al., 2017). Now that society expects from companies to be socially responsible, stakeholders are crucial for a firm and its innovation to be successful (Herrera, 2015).

Table 1 - Overview of the literature review

Author(s) Short summary IoT Business Model Social Value Value Co-Creation Baden-Fuller C.,

& Haefliger S. A detailed analysis on the impact of innovation to the performance with the use of business models and how the latter affect innovation X

Biloslavo, R., Bagnoli, C., &

Edgar, D.

An eco-critical approach to analysing the 20 most often cited

business model frameworks. X

Bidmon, C. M., & Knab, S. F.

A link between sustainable business model and a research on transition.

X

Brown, I., Crump, J., et al.

This report is based on the two-day seminar held in February 2013 at BCS to discuss the Societal Impact of the Internet of Things

X X

Bucherer, E., &

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Author(s) Short summary IoT Business

Model Social Value Value Co-Creation Demil, B., &

Lecocq, X. This paper describes the evolvement of business models as a tool that links necessary changes to essential components. X Funaki, K. This paper elaborates on Hitachi’s activities regarding innovations

and digitalization.

X

Gebauer, H., Joncourt, S., &

Saul, C.

The paper describes the reasons related to the products and sales that motivate companies to search for new ways to gain market share and differentiate their products.

X

Glova, J., Sabol, T., & Vajda, V.

This article elaborates on business models related to the Internet of Things, and Services

X X

Hacklin, F., Björkdahl, J., &

Wallin, M. W.

The paper tries to connect firm- and industry-level business models and investigates patterns of business model innovation between them.

X

Herrera, M. E.

B. The paper elaborates on corporate and social innovations that create value for the society and the corporations. X

Järvi, K., & Pellinen, A.

This article examines the methods through which mobile service productions generate value.

X X

Joyce, A., & Paquin, R. L.

The paper examines Nestle Nespresso business model through a triple layer business model canvas tool.

X

Ju, J., Kim, M. S., & Ahn, J. H.

The paper presents an analysis of IoT business model by examining existing literature and conducting interviews.

X X

Xie K., Wu Y., Xiao J., Hu Q.

According to several case studies, they present how big data can

create value for corporations and customers. X

Kuratko, D. F., McMullen, J. S.,

et al.

By introducing the social corporate entrepreneurship scale, the authors present how social value can create new opportunities and threats for companies.

X

Li, S., Xu, L. Da, & Zhao, S.

The paper indicates a thorough examination of IoT and presentation of current issues and gaps related with this subject.

X

Dijkman, R. M., Sprenkels, B., et

al.

The paper elaborates on business model frameworks related with IoT X X

Metallo, C., Agrifoglio, R., et

al.

The paper presents a study of the methods that companies that operate in the IoT sector are creating innovative business models.

X X

Morris, M., Schindehutte, M., & Allen, J.

The paper indicates a theoretical presentation of business models. The article proposes a sic component framework in order to depict a business model.

X

Nenonen, S., & Storbacka, K.

In this paper business models are explored as a broader approach of value co-creation. X Rauter, R., Jonker, J., & Baumgartner, R. J.

This research elaborates on the sustainable aspect of business models, its benefits and drivers.

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Model Social Value Value Co-Creation Westerlund, M.,

Leminen, S., & Rajahonka, M.

The authors examine business models related with IoT and the

difficulties that companies can face regarding those models. X X

Windrum, P., Schartinger, D.,

et al.

The authors try to connect in their paper the research fields of social

and service innovation. X

Maignan, I., Ferrell, O.C. Ferrell, L.

This research elaborates on the benefits and the methods of adopting

CSR in marketing segments. X

Achtenhagen, L., Melin, L., &

Naldi, L.

This paper identifies three important capabilities that enable to shape the key strategic actions.

X

Polat, S. The paper points out the evolvement of value creation through innovation.

X

Porter, M.E., Kramer M.R.

The paper elaborates on the ways that creation of economic value could at the same time create social value and benefit the society.

X

Ramaswamy, V. The research investigates the creation of value for the consumers by

examining the experience of different individuals. X

Aquilani, B., Silvestri, C., Ruggieri, A.

The journal connects, through extensive literature review. Sustainability, value co-creation, TQM, EM and IMS literature suggests new mechanism of value creation.

X

Baden-Fuller, C., Morgan, M.

The paper indicates how business models act inside a corporation

and how they form and describe companies along with managers. X

Bocken, N. M.P. Short, S. W. et

al.

This paper aims to formalise a category of business model innovation to create sustainability by using a systematic review approach.

X

Bocken, N., Short, S., et al.

The authors explain how the adoption of sustainability can assist companies to formulate social, economic and environmental value.

X

Boons, F., Lüdeke-Freund,

F.

The paper tries to connect sustainability and innovation to the adoption of business models.

X

Dart, R. This paper tries to step away from the economic models and elaborates on the social values based on institutional perspective.

X

Seelos, C., Mair, J.

In this paper, social entrepreneurship is presented, by explaining its concept, its mission and the ways it can affect society.

X X

Upward, A.,

Jones, P. The research indicates a framework of strongly sustainable business models and presents several ways to deal with its weaknesses. X Wilson, F.,

Post, J.E.

The authors explore the hybrid phenomenon of social business. X X

Yunus, M., Moingeon, B.,

Lehmann-Ortega, L.

The article follows the growth of “Grameen’s expertise” in creating social business models, which need new value creation and makes it resemble to business model innovation.

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Model Social Value Value Co-Creation Wójcik, P. This study tries to connect the notions of creating shared value

(CSV) to corporate social responsibility (CSR). X Current study Aim to deliver a novel framework which has the potential to guide

new IoT driven business models in delivering social innovation in line with what service users expect to receive

X X X X

The above table (Table 1) elaborates on the identified gap in the literature related to the four focus points of the study. Those four focus points are IoT, business models, social value and value co-creation. Particularly, this paper concentrates on IoT driven business models for delivering social value in line with what service users expect to receive. Several scholars have elaborated on social value creation but to the extent of my knowledge, there is no prior research concerning the social impact of IoT. Thus it would be interesting to capture the perspectives of service users in the role of IoT in delivering social values to our society.

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3. Proposed Conceptual Framework

In order to develop a well-rounded image, a theoretical framework will be created, which would combine all the aspects of social value. Therefore, the Stakeholder Model Canvas as proposed by Joyce & Paquin (2016) is selected in this study, to bridge technology and social value creation, which builds on a stakeholder’s management approach the organization's social impact. All of the important social impacts will be examined to understand which are improved by social innovation extensively. Table 2 presents the different “building blocks” of the framework and their definitions according to the paper of Joyce& Paquin (2016).

Table 2 - Definitions of the building blocks within the Stakeholder Model Canvas (Joyce& Paquin, 2016)

Building Block Definition

Social value “The company’s mission to create value for its stakeholders and society”

Social impacts “The social costs of the company. It complements and extends the financial costs of the economic layer and the biophysical impacts of the environmental layer”

Social benefits “The positive social value creating aspects specifically based on the company’s action” Local

Communities

“The social relationships built with suppliers and local communities”

Governance “The organizational structure and decision-making policies of the organization”

Employe es

“Considers the role of employees as a core organisational stakeholder. How for example employee-oriented programs contribute to the organization's long-term success" Societal culture “The potential impact of an organization on society as a whole”

Scale of outreach “The depth of the relationship built with the stakeholder through the company’s actions overtime”

End-user “How the organization contributes to the user’s quality of life”

The Stakeholder Model Canvas is chosen because it is constructed by multiple components (“building blocks”) that capture all the influences between stakeholders and the organisation and the key social impacts. Each component of the Stakeholder

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Model Canvas is called “building block” and we identify the relevant factors within each building block through our literature review.

Zwetsloot et al. (2013) examined in their paper the core values and value factors that support health, safety and well being, and some of them were divided in the adequate building block. Furthermore, Kaldaru & Parts (2014) have also introduced social factors for sustainable economic development and discussed the importance of those determinants for growth and development.

Local communities: Three items relevant to IoT applications, which are mainly institutional capacity, Collaboration and Unified communication, are selected for this building block (Reed’s et al. 2006). A brief description of each item is presented in the following.

Institutional capacity: This item refers to the enhanced capacity of communities due to developing structures and processes, often used in the sense of technology transfer. Collaboration: This item points to a process of participation through which people, organisations and things (in our case) work together to achieve optimal results.

Unified communication: This item relates to all types of communications exchanged via Internet network, which creates the opportunity to easily communicate through a range of integrated components.

Governance: For this building block the items Liability, Surveillance and Public safety were chosen by considering Cisco’s article by Gopalratnam talking about how the Internet of Things will impact governance and business, as well as exploring Cisco’s site on government benefits.

Liability: This item refers to the importance of governance being legally responsible for the misuse of IoT.

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gather information about a person or a group of people.

Public safety: Refers to the extend to which IoT creates value by ensuring a broad range of safety due to the number of information released. However it is government’s responsibility to protect the public in terms of privacy.

Social Value: NEC’s brochure “Social Value creation via IoT” helped perceive the units of this building block, Freedom, Equality and Satisfaction. This brochure by Jacobs (2016) helped also define items from different building blocks as for example, Socital Culture, Social Impacts and Social Benefits.

Freedom: This item shows the ability of technology to help people live without geographical or restrictions.

Equality: Refers to the refusal of social divide by allowing equal opportunities. Satisfaction: The fulfillment of expectations or needs derived from IoT technology. Societal Culture: The items Individuality, Responsibility and Experience resulted from the above literature and were chosen due to the building blocks’ explanation meaning of Joyce & Paquin, which wants it to be social impacts but not social costs. Individuality: It refers to the value of being able to act independently, being self-reliant with the help of this technology.

Responsibility: Having control over someone or something. IoT is a great example of creating environmental responsibility as it can operate by serving the environment with sensors, for example, that allows temperature control in buildings.

Experience: With IoT the overall experience of different operations changes as decisions can be made faster and more productively.

End-User: For this building block McKinsey’s Global Institute report of 2015 on the Internet of Things was very enlightening as it has a whole part of implications for stakeholders, which mentions consumers as well as employees. So the items Cost,

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Control, Efficiency and Facilitation were selected.

Cost: This item refers to the cost savings of users employing IoT technology by helping in energy management for example, or any other sources.

Control: Having the possibility to control several objects in matters of maintenance and security through IoT.

Efficiency: This item refers to the ability to perform in the best possible way, by avoiding waste of any kind (energy, effort, time)

Facilitation: The action of providing flexibility, connection to the external world and enabling people to work more effectively.

Employees: By choosing the factors Workplace collaboration, Productivity, Comfort and Organisational Mindfulness we consider the employee as the core organizational stakeholder and understand what values can the IoT provide him.

Workplace collaboration: This item refers to achieving the best possible results by new structures of communication in the working environment.

Productivity: It shows the capacity of being more productive by, for example, enhancing daily commute with the help of the interconnectivity of vehicles, roads and mobile devices.

Comfort: It refers to the feeling of satisfaction that can be enhanced by sentiment of having control over your life.

Organisational Mindfulness: It refers to the awareness of what is happening in the workplace and helps reduce stress over matters people feel they do not know.

Scale of Outreach: Here the values are considered more long-term and that is why Transparency, Adaptivity and Awareness were chosen, as they were values found in literature but are considered to be created more in the long-term usage of IoT technology.

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Transparency: This item implies openness and refers to operating in a way that it is easy to see what actions are performed. The data sharing of IoT technology allows different systems to have information about what is happening.

Adaptivity: This item shows the ability to adapt to new conditions in order to cope with the surroundings and be able to survive.

Awareness: The ability of being conscious of the events surrounding the person. IoT technology has this potential with the interconnected sensors being able to give information about several events.

Social Impacts: As well as from the above literature those three items were also derived from a report from 2016 of GrandViewResearch on IoT market analysis. Security and Privacy were mentioned as the bigger issues, which also can influence the Living Conditions.

Security: Refers to unauthorized access to data, which can threat confidentiality. Privacy: This item points to personal data being revealed or/and misused.

Living conditions: This item refers to the changes IoT brings which affect peoples’ lives with regard to their health and happiness.

Social Benefits: Here the items Autonomy, Quality of life and Social well-being were chosen as these social values can be created when companies chose to adopt IoT Autonomy: It refers to one’s power to control external forces and the capacity to do it all by oneself.

Quality of life: This item refers to the broader meaning of the general well being of people not just their standard of living which is based on income. IoT is highly relevant with this value as we realize that it results in faster and better decisions. Social well being: This item points to the feeling of social inclusion and people’s connection to society. IoT helps in the maintenance of social ties by keeping people

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connected and aware.

Figure 1 - Stakeholder Model Canvas (Joyce & Paquin, 2016)

Local Communities Institutional capacity Collaboration Unified Communication Governance Liability Surveillance Public Safety Social value Freedom Equality Satisfaction Societal Culture Individuality Responsibility Experience End-User Facilitation Cost Control Efficiency Employees Organisational mindfulness Comfort Productivity Workplace collaboration Scale of Outreach Transparency Adaptivity Awareness Social Impacts Living conditions Security Privacy Social Benefits Social well being Quality of life Autonomy

After defining each building block we need to capture the significance of the identified factors. Precisely, this thesis strives to identify the factors, which are important from the perspective of service users. As it is shown in figure 2, by doing so we can deliver a novel social model framework which has the potential to guide new IoT driven business models in delivering social innovation in line with what service users expect to receive. Therefore, we expect the outcome of our research to provide useful insights to practitioners on implementing new IoT applications, which are in line with what service users expect to have.

Figure 2 – Social innovation as the outcome of the proposed conceptual framework

IoT

technology

adoption

Social Value

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4. Methodology

In this chapter, an outline is provided on how this study is carried out. The first part of the chapter explains in depth the research design in which the method and sample of this research are discussed. The second part describes the operationalization of constructs, in which the characteristics of variables that are investigated in this research are specified. The third part comprises the data collection and data analysis and the fourth and last part concludes with a brief description of the statistical procedure with which this study pursues.

4.1 Research Design 4.1.1 Method

In this research, an empirical research methodology is used to identify the building blocks and building block factors for our IoT based novel framework. Subsequently, the relative importance of these factors and the identified building blocks is determined by using the results of a survey, which was conducted based on the paper of Dijkman et al (2015). An online survey using the qualtrics software was the most adequate way to reach as many respondents as possible. A quantitative research design is conducted, therefore, to examine the significance of these social factors when applying IoT technology. The introduction of the survey included a statement of confidentiality and stated the main goal of this research. The respondents checked that they understood the basis of the study and agreed to participate in it. It was also mentioned that the survey was for the purposes of a Master Thesis from a student of the University of Amsterdam and that the responses were going to be used only for the purposes of this particular study.

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4.1.2 Sample

There are no restrictions in the population participating in this survey. Due to the fact that the survey was about the social influence of IoT there is a need for a large and diverse population in order for it to be valid. The sampling technique used was a non-probability sampling such as convenience sampling aiming to reach as much more people as possible. The online survey was distributed to various online platforms such as Facebook and in IoT focused groups on LinkedIn to try and attract also a population familiar with the IoT field. Moreover, emails were sent to the University network as well as my personal network and acquaintances were asked to share the survey with their surroundings as well. The survey was published online from the 6th_{of May until the 23}rd_{of May 2018. The initial target sample was} approximate 300 responses. This is because earlier research about this topic shows that there is a possibility that only core questions of the questionnaire are completed, therefore the responses must be two times more than the final resulting cases (Dijkman et al., 2015). However, the responses gathered were 590.

4.2 Operationalisation of constructs

The questionnaire was introduced with an anonymity affirmation to make clear the need for honesty, and then it was followed from four different parts. The first part consisted of demographic questions, such as their age (ratio variable), gender (nominal variable), educational background (ordinal variable) and level of expertise with the Internet of Things (ordinal variable).

In the second part of the survey respondents will rate the importance of factors on a 6-point scale, labeled 6(extremely important), 5(very important), 4(moderately important), 3(slightly important), 2(not important), 1(opposed to my values) (Schwartz, 1992, 2006a), for society. This scale will be used to measure the

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importance of the factors following the structure of Dijkman et al., (2015) adapting it to the 9 social stakeholder building blocks, which will help us understand if technology helps achieve social innovation. Before the rating, two scenario examples would be written in which IoT will be explained in an easy and comprehensible way so respondents can familiarize themselves with IoT technology. The questionnaire is included in Appendix A.

4.3 Data collection and analysis

The survey resulted in 590 responses of which 415 fully completed the survey. The partially completed cases were deleted list wise, therefore are not used in the dataset analysed. This resulted in a response rate of 70.3%. Furthermore, to prevent participants to take the survey more than once, the "Prevent Ballots Box stuffing" option was chosen, which doesn't allow respondents to take the survey twice by putting a cookie on their browser everytime they submit a response. By detecting the cookie, qualtrics doesn’t permit the user to retake the survey. Furthermore, to prevent as much as possible careless responding to the time spent to fulfil the survey was checked. As qualtrics indicated an average of 7minutes to complete the survey based on the number of questions included every survey, which was fulfilled in 5minutes or less was not considered to be valid. Based on this, 80 cases were deleted. Finally, the standard deviations (st. dev) of the factors of the building blocks were computed in a new variable. In the case that the st.dev is 0, it means that the values in the building block were exactly the same; hence, the answers consistency makes them unreliable and maybe also dishonest.

In order to examine the data, the first thing needed to be done is to go through the data and identify reverse scored constructs and then reverse them to be sure we are measuring them correctly. The only score we reversed was from a negatively keyed

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item question, which was phrased negatively in purpose in order to detect acquiescence bias (the tendency to respond positively or negatively in all questions indiscriminately). Furthermore we calculated the standard deviation of all responses to examine if there where any responses which did not deviate at all (st.dev=0) which shows a tendency to respond similarly in all questions. By deleting those 8 cases due to similar answers left us 327 observations to be analysed (N=327).

Table 3 - Descriptive Statistics of survey respondents Gender Male 120 36.7% Female 207 63.3% Age group Under 18 1 0.3% 18-24 54 16.5% 25-34 95 29.1% 35-54 118 36.1% 55+ 59 18% Education No degree 2 0.6%

High school degree 43 13.1%

Bachelor’s degree 120 36.7%

Master’s degree 148 45.3%

Doctorat 14 4.3%

Familiarity with IoT

Not familiar at all 66 20.2%

Slightly familiar 61 18.7%

Moderately familiar 109 33.3%

Very familiar 72 22%

Extremely familiar 19 5.8%

Table 3 shows the descriptive statistics of the respondents of the survey. The sample consisted of 120 male respondents (36.7%) and 207 female respondents (63.3%). Furthermore, the target age of the majority of the respondents was between 35-54 (36.1%) and in total 82% has obtained either a Bachelor’s or a Master’s degree. Regarding the familiarity with IoT 20.2% of our participants mentioned that they

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were not familiar at all while 18.7% said were slightly familiar. The majority of the respondents was moderately familiar (33.3%), another 22% were very familiar and only 5.8% of the respondents were extremely familiar.

The way this data will be analysed will first be using Exploratory Factor Analysis (EFA). We will use this method as we have multivariate statistics, and it is the way to identify the structure of a large set of variables like the one we have. By doing this we explore whether there are any unrevealed factors besides our predefined building blocks (Dijkman et al., 2015). We are using the exploratory type of factor analysis because we do not want to set any predefined structure, as this way we will understand better how our variables/items are affected in a data structure. The results will reveal if the variables are under the right building block as well as if they are interrelated with the items of the same building block.

Next to measure the importance and significance, one sample t-tests will be performed within each building block separately. One sample t-tests is the way to calculate the variable’s mean and determine whether it is statistically different from the building blocks mean. The relative importance and significance of each item is displayed in Appendix 3.

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5. Results

The results of our analysis are reported in this section. As previously mentioned the guidelines for the analysis were derived from Dijkman et al. (2015). A variability analysis for every building block was done to compute their Cronbach Alpha. Then the correlation matrix of our variables was constructed. Subsequently, we ran an exploratory factor analysis to find out about the constructs that may exist behind our data. Factor analysis can provide us an insight on which variables hold together and appear to measure the same construct. Finally, we conducted sample t-tests to find out the importance or significance of the factors.

5.1 Correlation Matrix

In order to calculate the correlation matrix, scale means of all the building blocks have been computed. Scale means of all the building blocks have been computed and were coded with the name of each building block (i.e., EmployeesTOT). Table 4 presents the correlation matrix of the new variables as well as the number of items (N), mean and standard deviation (St. Dev).

As we can see from Table 4, all building blocks are positively correlated with a significance of p<.05. The variables have a low degree of correlation with the demographic variables (0<r<0.2) except Governance that has a correlation of 0.202 with Gender, which can be still considered as quite low. The only sings of significance between the demographics and the building block variables has been between Age and Societal Culture (p<.01) and between Gender and the variables Governance, Societal Culture, Social Impacts and Social Benefits (p<.01). Level of education and Familiarity with IoT did not have any significant correlation with the building block variables; on the contrary, they were negatively correlated with some of them. Governance, Societal Culture, Social Benefits, Scale of Outreach, End-User

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and Social Impacts have negative correlations with the level of education and the familiarity with IoT, although the correlations are weak (r<0.1). Moreover, we see that 8 out of 9 constructs have strong correlations with each other (r>0.3), which suggests that they have a reasonable factorability. The ones that have a weaker correlation are Social Benefits with Governance and Social Impacts with Local Communities. Another interesting observation is related to the differences among the calculated means of the constructs. We notice that the calculated means of the Scale of Outreach and Social Impacts are higher than the others. That is to say, from the view point of the service users, their factors have been considered to be more important than other constructs

Cronbach Alpha is measured for all variables to check the factor’s consistency within a building block and see how closely are the factors are related. Cronbach Alpha of all the variables are adequate and they exceed the benchmark value of 0.70 and all items have a good correlation between the items of the same construct (more than 0.30). The building block with the lowest level of reliability was Social Impacts. It had a Cronbach Alpha of .690, but the removal of the Living Conditions component from this construct would improve this to .746. This resulted in deleting this item to improve the reliability of this construct. After examining this case and the reason behind the need of its removal it was noticed that the Living Conditions factor may not have had a clear meaning to the respondents as it could be represented by many different ways. Another reason for this might be that the other two factors of the construct refer to social impacts that can affect IoT negatively while living conditions are mostly interpreted positively. This could have influenced the internal consistency of the building block and the correlation with the other factors.

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Table 4 - Correlation Matrix

The table presents the number of items of each variable, mean, standard deviation, correlation matrix and the Cronbach Alpha indicated in parenthesis

N Mean Std. Dev.

Gender 1 1.63 0.483 1

Age 1 3.55 0.98 0.059 1

Level of education 1 3.39 0.791 -.222** 0.02 1

Familiarity with IoT 1 2.75 1.177 -.137* -0.043 -0.011 1

Local CommunitiesTOT 3 4.6116 0.81086 0.021 0.06 0.015 0.037 1 (.727) EmployessTOT 4 4.6911 0.81338 0.048 0.014 0.014 0.037 .502** 1 (.772) GovernanceTOT 3 4.6086 1.01574 .202** 0.036 -0.105 -0.004 .463** .432** 1 (.701) Social ValueTOT 3 4.6983 1.01523 0.107 0.054 0.042 0.002 .351** .408** .311** 1 (.756) Societal CultureTOT 3 4.474 0.87333 .157** .115* -0.072 -0.001 .342** .500** .399** .595** 1 (.703) Scale of OutreachTOT 3 5.051 0.82405 0.101 0.058 0.002 -0.051 .347** .378** .378** .563** .557** 1 (.840) End UserTOT 4 4.8739 0.75073 0.071 0.066 0.025 -0.054 .404** .430** .351** .446** .462** .503** 1 (.755) Social ImpactsTOT 2 5.1172 0.85813 .178** -0.022 -0.039 0.066 .283** .399** .436** .475** .421** .396** .442** 1 (.746) Social BenefitsTOT 3 4.9949 0.86256 .160** 0.011 -0.017 -0.008 .421** .483** .230** .547** .529** .533** .507** .443** 1

** Correlation is significant at the 0.01 level (2-tailed).

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5.2 Exploratory Factor Analysis

In order to evaluate the goodness of our scale as well as to examine the similarities between the variables, we perform an Exploratory Factor Analysis. The factorability of the 28 items (factors) inside the building blocks was examined. The purpose of this test is to check if the items group together to create a construct. We are using the principal component method in the exploratory analysis because we do not assume any causal relationship between the items. Since we know that the factors are correlated to one another from our previous correlation matrix we use the oblique factor analysis rotation (promax), which is the one also used in Dijkman’s paper. The calculated Kaiser-Meyer-Olkin (KMO) value extracted is .904, which is much greater than the recommended value of 0.6. Those were the desired results, as KMO ideally has to be greater than .8. Bartlett's test has to be as small as possible and in our sample, it is exactly 0, which means that the set of observed variables is appropriate for our analysis. The Bartlett’s test, which indicates if the variables are unrelated, is significant and this means that the items are not normally distributed; they are skewed, which was the desired outcome as it indicates that a factor analysis is useful for this data. Furthermore, the communalities were all above 0.5, which is much higher than the benchmark of 0.3 (see Table 5). This confirms that the factors share common variance with each other and the extracted components represent the constructs well.

The eigenvalues indicated that the first 6 constructs (building blocks) have a value of more than 1 and explained a total of 61.745 of the total variance. Those constructs are Scale of Outreach, Social Benefits, End-User, Local Communities, Social Value and Social Impacts. Both promax and varimax solutions were tested, and there was no difference between the two analysis. However, as previously explained

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promax was chosen. Since the factor loading should be more than .45 in the pattern matrix (Table 5), we decided to suppress coefficients smaller than .20 so that Table 5 could stay cleaner and clearer and see better the existing patterns. Due to minimum criteria of loading item .45 seven items were eliminated. Satisfaction and Responsibility were eliminated first as they did not meet the minimum criteria (of >.45 loading). Then Public safety, Organisational mindfulness, Comfort, Experience and Efficiency were also deleted for having factor loadings in multiple factors greater than 0.3 but with a difference of less than 0.2 of the factor loading in another construct. This showed in the pattern matrix that those items fitted poorly with the different constructs, as they didn’t have a clear loading of more than .45 in one only construct.

The extracted factors retained from the EFA suited the stakeholder model canvas we proposed completely. Despite the fact that some items needed to be removed from the proposed conceptual framework, the findings support its underlying structure.

Table 5 - Exploratory Factor Analysis

The table presents the pattern matrix of the 9 different constructs

1 2 3 4 5 6 7 8 9 Communalities Adaptivity 0.91 0.685 Awareness 0.857 0.677 Transparency 0.851 0.671 Quality of life 0.972 0.669 Social well-being 0.785 0.658 Autonomy 0.557 0.645 Cost 0.874 0.627 Facilitation 0.798 0.597 Control 0.649 0.591 Unified Communication 0.873 0.576 Collaboration 0.748 -0.255 0.571 Institutional capacity 0.695 0.365 0.56 Freedom 0.929 0.56

Service user perspectives on delivering social innovation : an implication of the internet of things for business