IN
DEGREE PROJECT INDUSTRIAL ENGINEERING AND MANAGEMENT,
SECOND CYCLE, 30 CREDITS STOCKHOLM SWEDEN 2017,
Smart Locks for Smart Customers?
A Study of the Diffusion of Smart Locks in an Urban Area
SANNE BJARTMAR HYLTA PETRA SÖDERBERG
KTH ROYAL INSTITUTE OF TECHNOLOGY
Smart Locks for Smart Customers?
A Study of the Diffusion of Smart Locks in an Urban Area by
Sanne Bjartmar Hylta Petra Söderberg
Master of Science Thesis INDEK 2017:88 KTH Industrial Engineering and Management
Industrial Management
SE-100 44 STOCKHOLM
Smart Locks for Smart Customers?
A Study of the Diffusion of Smart Locks in an Urban Area av
Sanne Bjartmar Hylta Petra Söderberg
Examensarbete INDEK 2017:88 KTH Industriell teknik och management
Industriell ekonomi och organisation
SE-100 44 STOCKHOLM
Master of Science Thesis INDEK 2017:88
Smart Locks for Smart Customers?
A Study of the Diffusion of Smart Locks in an Urban Area
Sanne Bjartmar Hylta Petra Söderberg
Approved
2017-06-06
Examiner
Niklas Arvidsson
Supervisor
Cali Nuur
Commissioner
Glue Home
Contact person
Luisa Orre
Abstract
This thesis investigates the smart lock market and diffusion of smart locks in the context of an urban area in Europe. More specifically, the empirical study was conducted in London, United Kingdom. Smart Lock technology has the potential to make life easier for professionals as well as to solve the emerging last mile delivery problem. The last mile delivery refers to final movement of goods from the hub to the customer. It is the final leg of the complete journey of the goods and consists of obstacle and complexity.
The aim of the thesis was to examine the current market for smart locks and identify barriers and drivers for the future diffusion of smart lock in urban areas. This was done through a survey of convenience in London and interviews with stakeholder in the smart home and last-mile delivery sector. The results show that there are both large
opportunities as well as barriers for the smart lock market and that it is of high
importance for the smart lock producers to create different use-cases around the smart lock in order to create relative advantage. The diffusion of smart locks is a complex multi-dimensional process depending on the use case of the smart lock. Smart lock producers need to find creative solutions to find effective use cases and to
communicate these to potential customers. They need to have a strong client support and a comprehensive insurance- and security plan as security concerns among customers is one of the biggest obstacle for its further diffusion.
Key-words: Smart Locks, Internet of Things (IoT), Diffusion of Innovations
Examensarbete INDEK 2017:88
Smart Locks for Smart Customers?
A Study of the Diffusion of Smart Locks in an Urban Area
Sanne Bjartmar Hylta Petra Söderberg
Godkänt
2017-06-06
Examinator
Niklas Arvidsson
Handledare
Cali Nuur
Uppdragsgivare
Glue Home
Kontaktperson
Luisa Orre
Sammanfattning
Denna uppsats undersöker marknaden för smarta lås och diffusionen av smarta lås i urbana områden i Europa. Mer specifikt så genomfördes den empiriska studien i London, Storbritannien. Smarta lås har potentialen att göra vardagslivet enklare likväl som att lösa det växande ”last mile delivery” problemet. Detta refererar till den sista biten av leverans till kunden, en komplex resa som ofta kantas av hinder. Syftet med denna uppsats var att undersöka den nuvarande marknaden för smarta lås samt att identifiera potentiella hinder och drivande krafter för framtid diffusion av smarta lås.
Detta gjordes genom en enkätundersökning i London och intervjuer av folk med
professionell expertis inom teknologi för smarta hem samt i leveransindustrin. Resultatet visar att det finns hinder likväl som stora möjligheter för smarta lås. Det är av stor vikt för smarta lås tillverkare att skapa fler funktioner kring låset mer än den primära lås- funktionen för att skapa relativa fördelar. Diffusionen av smarta lås är en komplex
multidimensionell process som ser olika ut beroende på användningsområdena som det smarta låset möjliggör. Producenter behöver skapa kreativa lösningar för att hitta
effektiva användningsområden och för att kommunicera och förklara till kunder. De behöver en stark kundsupport och en genomgående försäkring- och säkerhetsplan då säkerhet och rädsla för inbrott är det största hindret för diffusion av smarta lås.
Nyckelord: Smarta lås, Internet of Things (IoT), Diffusion of Innovations
Contents
List of Figures 3
Foreword 5
1 Introduction 5
1.1 Background . . . 5
1.2 Smart Homes . . . 6
1.3 Problem Formulation . . . 6
1.4 Purpose . . . 7
1.5 Research Questions . . . 7
1.6 Limitations . . . 7
1.7 Contribution to Previous Research . . . 7
1.8 Outline of the Thesis . . . 7
2 Literature Review 9 2.1 Rogers Di↵usion of Innovation Theory . . . 9
2.1.1 Elements in the Di↵usion Process . . . 9
2.1.2 Attributes of Innovation . . . 10
2.1.3 Adopter Categories . . . 11
2.2 The Chasm Model . . . 13
2.3 Factors A↵ecting Di↵usion of Technology . . . 15
2.4 The Product Life Cycle . . . 17
2.5 Internet Of Things . . . 18
2.6 Summary of Literature Review . . . 19
3 Method 20 3.1 Research Approach . . . 20
3.2 Research Process . . . 20
3.2.1 Literature Review . . . 20
3.2.2 Interviews . . . 21
3.2.3 Survey . . . 21
3.2.4 Data Analysis . . . 21
3.3 Validity and Reliability . . . 22
3.4 Generalizability . . . 22
3.5 Summary of Method . . . 22
4 Empirical Findings 24 4.1 Mapping of the Smart Lock Market in London . . . 24
4.1.1 The Smart Home Technology Market . . . 24
4.1.2 The Smart Lock Market and Mapping of Available Smart Locks . . . 24
4.1.3 Competitive Substitutes . . . 26
4.2 Consumer Behaviour and Adoption in London . . . 28
4.2.1 Survey of Convenience . . . 28
4.2.2 Industry Interviews . . . 32
4.3 Summary of Results . . . 37
5 Analysis 39 5.1 Rogers Di↵usion of Innovations . . . 39
5.2 The Chasm Model . . . 43
5.3 Factors A↵ecting Di↵usion of Technology . . . 45
5.4 The Product Life Cycle of Smart Locks . . . 46
5.5 IoT Framework and External Factors A↵ecting the Smart Lock Market . . . 47
6 Conclusion and Further Research 48 6.1 Conclusion . . . 48
6.2 Implications . . . 51
6.3 Further Research . . . 51
7 References 52 8 Appendix 55 8.1 Survey Questions and Results . . . 55
8.2 Interview Questions . . . 74
List of Figures
1 Illustration of the Outline . . . 8
2 Main Elements of Di↵usion, (Rogers, 2003) . . . 9
3 Attributes of Innovation, (Rogers, 2003) . . . 10
4 Roger’s Di↵usion Of Innovation Bell (Rogers, 2003). . . 12
5 Di↵usion of Colour Televisions in the UK (Tidd & Bessant, 2009). . . 13
6 The Chasm Model . . . 14
7 The Whole Product Model . . . 15
8 Product Life Cycle (Utterback & Abernathy, 1975). . . 17
9 Available Smart Locks and Features . . . 25
10 Smart Locks Market Competition . . . 27
11 Characteristics of the Respondents . . . 28
12 Technological Attitudes of the Respondents . . . 29
13 Smart Lock . . . 30
14 Respondents Attitudes towards Delivery . . . 31
15 Respondents Trust for In-Home Delivery and their Digital Key . . . 32
16 Results from how early the survey participants perceive themselves to try new products com- bined with Roger’s Bell curve . . . 40
17 Areas of importance for future di↵usion of smart locks . . . 49
18 Summary of Analysis of Frameworks (red implies problem areas, yellow is neutral, green is good) . . . 50
Foreword
This master thesis report was written by Sanne Bjartmar Hylta and Petra S¨oderberg at the Royal Institute of Technology, Stockholm, Sweden, the department of Industrial Engineering and Management. The master thesis project was conducted during the period of January 2017 and June 2017.
We would like to express our gratitude to our supervisor at KTH, Cali Nuur, professor in Industrial Dynamics. During the master thesis project, Nuur has been able to supervise and coach us with excellent advises during the entire project. We would also like to thank Richard Backteman whom have provided us with feedback and valuable input during the project and seminars. The guidance has always aided us to improve our thesis project, and we can undoubtedly say that our thesis benefited from their assistance.
Thank you Cali and Richard!
We would also like to express our gratitude to the industry professionals who agreed to be interviewed despite their busy schedules. Without them, this thesis would not have been able to be written!
Thank you all for your valuable inputs and knowledge!
Finally we would like to thank our families and our dear partners Charles and Luca.
Thanks to our familes, Charles and Luca for your endless support!
Sanne Bjartmar Hylta & Petra S¨oderberg, Stockholm, Sweden, 2017-06-01
1 Introduction
This chapter introduces the background of the research, where the research problem, the purpose, the research questions, limitations of the research and contribution to previous research is defined.
1.1 Background
Information and Communications Technology (ICT) has drastically changed how people work, communicate, learn and live. The rise of so called Big data and the Internet of Things (IoT) fuels growth of ICTs, and ICTs are shaping the business landscape with new innovations as well as old innovations which have made comeback. Schumpeter argues that innovation in business is the major reason for increased investments and business fluctuations (Sweezy, 1943). New innovations involves an enormous amount of uncertainty, human creativity, and chance (Utterback & Abernathy, 1975). A lot of literature aims to understand di↵erent innovations and the di↵usion process of new innovations.
Rogers (2003) defines di↵usion as a special type of communication concerned with the spread of messages that are perceived as new ideas. It is the process by which an innovation is communicated through certain channels over time among the members of a social system. Rogers is the founder of the technology adoption lifecycle, a sociological model that describes the adoption of a new innovation according to the demographic and psychological characteristics of defined adopter groups over time.
The rate of product innovation in an industry or product class is highest during its formative years.
This is a period called the fluid phase, during which a great deal of experimentation with product design and operational characteristics take place among competitors. Within a rich mixture of experimentation and competition, some center of gravity eventually forms in the shape of a dominant design. Once the dominant design emerges, the basis of competition changes radically, and the ecology of competing firms changes from one characterised by many firms and unique designs, to one of few firms with similar product designs (Utterback, 1996).
To become the dominant design, a company need to cross the chasm. The chasm is the gap between two adoption groups early adopters and early majority in Roger’s technology adoption life cycle. The early majority is only interested in buying from the market leader. A company can hence only become the market leader if they win over the innovators and the early adopters. Since the product o↵ering and marketing to the di↵erent adoption groups di↵ers a lot, it is important for technological companies to understand who they are currently targeting with their innovation. (Moore, 1991)
Many new innovations today are aiming to make homes smarter and the everyday life easier, now achiev- able due to the advanced data analytics and the emergence of artificial intelligence (Angelakis et al, 2017). A smart home is a relatively new concept, defined as a convenient home setup where appliances and devices can be automatically controlled remotely from anywhere in the world using a smart phone or other networked device (Investopedia, 2017). Smart home products is a wide concept with many di↵erent product groups.
One of them is the smart lock. This is an electromechanical lock which is designed to perform locking and unlocking operations on a door when it receives such instruction from an authorized device, for example a smart phone.
The smart lock is a current example of an innovation in the fluid phase. In the smart lock market there are many di↵erent product designs with di↵erent operational characteristics as well as many active competitors. The fluid phase for smart locks implies that the technology might soon cross the chasm and that the dominant design thereby will be determined.
The smart lock is a possible part of the solution to the so called ”last mile delivery” problem for delivery companies. The last mile in parcel delivery is often complex, as it requires the customer to be at home if delivered to the door. Smart locks would enable the owner to grant temporary access to, for example, deliverers which could eliminate the need to deliver the same parcel more than one time.
1.2 Smart Homes
The definition of a smart home, according to the UK Department of Trade and Industry, is ”a dwelling incorporating a communications network that connects the key electrical appliances and services, and allows them to be remotely controlled, monitored or accessed” (Baliga, 2015). The smart home technologies are increasing in number which is causing compatibility issues. Many are now striving for more standardised smart home technologies. What is perceived as a smart home also di↵ers. In the real estate industry this has become a real problem since many believe a house will be sold faster if they claim it to be smart. This has led to a more refined definition which require a home to have at least two features from a list of smart options. With this definition, only one out of four houses are smart in the US, even thought 87 percent acknowledge the value of a smart home. (Olick, 2016)
Some of the functionalities o↵ered by smart homes are related to economic and comfort-related aspects such as light and heater systems automatically turning on/o↵ according to the inhabitant’s location/presence within the home. Another large element witnessed from smart homes is the arise of independent living for those su↵ering disabilities. The introduction of technology and technological support into the lives of such patients o↵ers the potential for them to undertake daily activities which they previously would have relied upon from external support (Augusto & Nugent, 2006). Today’s smart homes are mainly focused on sustainability and security, with products such as automated lights, thermostat adjustment and remote video surveillance. People spend more time away from the house nowadays and therefore the new smart systems are providing a connectivity with your house, which many customers are appreciating. (Olick, 2016)
How the future of smart homes will turnout is not certain. Many believe it will be similar to what is seen in the movies with digital and robotic agents taking care of all chores. MIT House n group, on the other hand, suggests that research should focus on creating technology that requires human e↵ort. This, to keep life mentally and physically stimulating as people age since losing a sense of control can be debilitating.
Instead of having everything done for you, sensors will provide you with ”Just-in-Time” information giving you more control over the decision-making. (Intille, 2006)
1.3 Problem Formulation
The smart lock technology is currently in the fluid phase and there is no dominant design, neither has population di↵used the innovation fully. IoT innovations are becoming increasingly important in today’s business landscape and at the same time are people getting more concerned about personal integrity. The lock has always been a symbol of security and safety, so what happens when it is turned into a smart product?
Will it be di↵used as previous smart technology or are there new obstacles that will slow this di↵usion down?
By using a smart lock, there are many benefits a customer can experiencing in terms of convenience and increased visibility. Nevertheless, the benefits the society can experience are even bigger as this product can eliminate the last mile delivery problem and the extra pollution this is accompanied by. Therefore, it is not only important to ensure a fast di↵usion of the smart lock for the smart lock producers and delivery companies, but also from an environmental point of view. Furthermore, from an academical point of view,
are the factors identified in existing theories of di↵usion enough or are there factors they are not covering?
1.4 Purpose
The purpose of this thesis is to analyse the current market for smart locks and to identify drivers and barriers for the continued di↵usion of smart locks in urban areas.
1.5 Research Questions
To fulfill the purpose of the study, the research question that needs to be answered is the following:
• How can the di↵usion of smart locks in urban areas be accelerated?
To answer the research question thoroughly, it has been divided into three sub-queries:
• What are the main factors hindering the di↵usion of smart locks among customers in an urban area?
• Which factors does the existing theories of di↵usion classify as the main obstacles of the di↵usion of smart locks?
• What substitutes to smart locks are o↵ered, and how can they influence the continued di↵usion?
1.6 Limitations
This study aims to understand di↵usion of smart locks in urban areas. This study is limited to the di↵usion of smart locks in London. London has the largest e-commerce markets in Europe and the characteristics among the population are well aligned with the adoption groups early adopters and early majority.
The city is perceived as a pioneer when it comes to new innovations. We will hence analyse the di↵usion of smart locks in London to analyse the future di↵usion of smart locks in Europe as a whole. Other areas such as Asia and the US have di↵erent conditions of smart lock di↵usion due to standardisation of locks, and the study is hence primarily used to analyse the di↵usion of smart locks in Europe.
However, market research and literature review will also take other geographical areas and other products into account to obtain a broader perspective of the smart lock market.
There are currently many smart products available on the market besides smart locks and smart home technology. These products will not be discussed in this thesis due to the big di↵erence in application.
1.7 Contribution to Previous Research
The smart lock technology is a relatively new technology, which means that theory concerning this niche mostly will be found in articles and blogs with limited scientific reliability. This study of the smart lock di↵usion, with high scientific reliability, will hence contribute with the establishment of this technology and concept.
1.8 Outline of the Thesis
This thesis consists of six chapters. After this introduction chapter, a literature review and method will be presented with relevant theory and methods, designed to answer our research questions. Thereafter, the empirical findings from both the literature review, survey and interviews will be presented. Finally, the empirical findings will be analysed and conclusions will be drawn and a recommendation of further research will be given.
Figure 1: Illustration of the Outline
2 Literature Review
This chapter presents existing theoretical frame works, which will be split between Roger’s di↵usion of inno- vation theory, the chasm model, factors a↵ecting di↵usion of technology, the product life cycle and Internet of Things (IoT). The thesis intends to analyse the di↵usion of smart locks and its barriers in urban cities by combining existing findings and theories about di↵usion with a survey of convenience and industry interviews.
2.1 Rogers Di↵usion of Innovation Theory
The interest for the innovation and di↵usion process as an academic field of research has exploded since Rogers presented his work ”Di↵usion of Innovations” in 1962, one of the most cited work in di↵usion research (Tidd, 2010). Di↵usion of innovation is a theory that seeks to explain how, why and at what rate a new technology spreads. According to Rogers (2003), di↵usion is a social process in which actors of the social system create and share information through communication channels over time. Rogers defines the innovation as an idea, practice or object perceived as new by an individual or other unit of adoption. Di↵erent parts and perspectives on the di↵usion process is addressed in Rogers work. Roger’s theory of elements in the di↵usion process, attributes of innovation and adopter categories will presented here as well as further research that addresses this theory.
2.1.1 Elements in the Di↵usion Process
Rogers (2003) argues that di↵usion is the process by which an innovation is communicated through certain channels over time among the participants in a social system. The four main elements in the di↵usion are:
Innovation, Communication channels, Time, Social system. (Rogers, 2003)
Figure 2: Main Elements of Di↵usion, (Rogers, 2003)
Innovation
The innovation is a broad category that is relative to the current knowledge of the analysed unit. Any idea, practice, or object that is perceived as new by an individual or group could be considered as an innovation.
Communication Channels
It is through the communication channels the Innovation spread across the individuals. This can take any form, like word of mouth, any sort of literature, advertising, etc.
Time
The time refers to the length of time that is necessary for the innovations to be adopted. New innovations are rarely adopted instantaneously.
Social System
The social system is the combination of external influences, such as mass media and governmental mandates, and internal influences such as social relationships. There are many di↵erent roles in a social system, and their combination represent the total influences on a potential adopter.
2.1.2 Attributes of Innovation
The rate of adoption is determined by the characteristics of the innovation, as perceived by the member of the social system. There are five attributes of innovation: Relative advantage, Compatibility, Complexity, Trialability, Observability. (Rogers, 2003). These identified characteristics can be grouped into three cate- gories: characteristics of the innovation itself, characteristics of the individual organizational adopters and characteristics of the market environment and communication networks (Tidd, 2010)
Figure 3: Attributes of Innovation, (Rogers, 2003)
Relative Advantage
This is the degree to which an innovation is perceived as better than the idea it supersedes. Relative advan- tage refers to the extent to which the innovation is more productive, efficient, costs less, or improves in some other manner upon existing practices. This can be measured in economic terms but important factors are also social prestige, convenience and satisfaction. The adopter is more likely to adopt a new innovation if it finds a relative advantage of it. The greater perceived relative advantage of an innovation the higher rate of adoption, i.e. the relative speed with which an innovation is adopted by members in the social system. Tidd
& Bessant (2009) highlights that it is useful to distinguish between the primary and secondary attributes of an innovation. Primary attributes, such as size and cost, are invariant and inherent to a specific innova- tion irrespective of the adopter. Secondary attributes, such as relative advantage, may vary from adopter to adopter, being contingent upon the perceptions and context of the individual adopter. Increasing the perceived relative advantage of the innovation, subsidizing trials or reducing the cost of incompatibilities are
incentives that may be used to promote the adoption of an innovation.
Compatibility
This is degree to which the innovation is perceived as being consistent with the existing values, past ex- periences, and needs of potential adopters (Rogers, 2003). There are two distinct aspects of compatibility:
values and norms; and existing skills and practices (Tidd & Bessant, 2009). An innovation must be consid- ered socially acceptable to be implemented and some innovations require much time and discussion before they become so. An innovation that is incompatible with the existing values and norms of a social system will not be adopted as fast as an innovation that is compatible. New values and norms must first be adopted and accepted, which can be a relatively slow process. (Rogers, 2003). The extent to which the innovation fits the existing skills, equipment, procedures and performance criteria of the potential adopter is important and relatively easy to assess. Network externalities can a↵ect the adoption process. For example, the cost of adoption and use, as distinct from the cost of purchase, may be influenced by: the availability of information about the technology from other users, of trained skilled users, technical assistance and maintenance and of complementary innovations, both technical and organizational. (Tidd & Bessant, 2009)
Complexity
This is the degree to which the innovation is perceived as difficult to understand and use. Innovations which are simple for potential users to understand will in general be adopted more rapidly than those which require the adopter to develop new skills and knowledge. (Rogers, 2003)
Trialability
This is the degree to which the innovation may be experimented with on a limited basis. Innovations are in general easier to adopt if they can be tried out in part, on a temporary basis, or easily dispensed with after trial. A trialable innovation represents less uncertainty to potential adopters and allows learning by doing.
(Rogers, 2003). The exception is where the undesirable consequences of an innovation appear to outweigh the desirable characteristics. In general, adopters wish to benefit from the functional e↵ects of an innovation, but avoid any dysfunctional e↵ects. However, where it is difficult or impossible to separate the desirable from the undesirable consequences trialability may reduce the rate of adoption. (Tidd & Bessant, 2009)
Observability
This is the degree to which the result of the innovation are visible to others. The model of di↵usion assumes that innovations spread as potential adopters come into contact with existing users of an innovation. The chances of adoption are hence greater if other adopters easily can observe relative advantages of the new technologies. (Rogers, 2003)
2.1.3 Adopter Categories
Rogers (2003) specify five di↵erent adopters categories, an classification of the members of a social system on the basis of their innovativeness. Innovativeness is defined as the degree to which an individual adopts a new idea, relatively to the other members of their social system. There are five di↵erent adopter groups:
Innovators, Early Adopters, Early Majority, Late Majority, Laggards. The figure below illustrates the rate in which the di↵erent adopter category di↵use innovations.
Figure 4: Roger’s Di↵usion Of Innovation Bell (Rogers, 2003).
The rate of adoption is initially low, and adoption is confined by the innovators. Innovators are most open to new ideas, willing to take risk and have close contact with scientific sources. Next to adopt are the early adopters, then the late majority and finally the curve tails o↵ as only the laggards remain. Laggards are, on the contrary to Innovators, the last to adopt to new innovations and often tend to be old with a low social status. The curve is indicating each categorization in percentage of the total population. Each adopter group have their own characteristics: (Rogers, 2003)
Innovators
Innovators are willing to take risks and tend to have a high social status and financial liquidity. They are social and have a close contact to scientific sources as well as with other innovators. They have a high risk tolerance, which helps them to adopt technologies that may fail. Their financial resources help them to absorb the these failures.
Early Adopters
Early adopters have the highest degree of opinion leadership among the adopters categories. Similar to the Innovators, they often have a high social status and financial liquidity. They have a higher education and are more social than later adopters. They are more slow in adoption compared to the Innovators and use judicious choice of adoption to help them maintain a central communication position.
Early Majority
Early majority adopt new innovation significantly slower than the Innovators and Early Adopters. They often have above average social status and contact with early adopters.
Late Majority
Late majority adopt new innovations slower than the average adopter. They tend to have below average social status, little financial liquidity and little opinion leadership. They are have a high degree of skepticism towards new innovations and have contact mainly with others within the late majority and people from the early majority.
Laggards
Laggards are the last group to adopt new innovations. They often have a low social status, low financial liquidity, are old relative to the other adopters and are in contact only with family and close friends. They have little or no opinion leadership.
The di↵usion of an innovation can also illustrated by the S-shaped curve shown in Figure 5. Many of marketing studies have attempted to fit the adoption of specific products to the S-curve, ranging from television sets to new drugs.
Figure 5: Di↵usion of Colour Televisions in the UK (Tidd & Bessant, 2009).
Rogers di↵usion of innovation bell- and S-curve was the earliest model and still the most commonly used.
It assumes a homogeneous population of potential adopters, and that innovations spread by information transmitted by personal contact and geographical proximity of existing and potential adopters. The model has been criticized because it assumes that all potential adopters are similar and have the same needs. (Tidd
& Bessant, 2009)
2.2 The Chasm Model
Many start-ups are currently facing problems to get their technology to the big market, the majorities. They have managed to reach the innovators and early adopters, but then they reach ”the chasm”. The chasm is
explained as the gap between the early market (innovators and early adopters) and the mainstream market (early and late majority). The mainstream market di↵ers a lot from the early market in the sense that they are far more pragmatic and need fully functioning solutions to actual problems. The early market on the other hand, finds it enough to just see the potential in a product and are willing to use it even if it is not fully developed. The promise of a solution to their problems is enough. (Moore, 1991)
Because of the chasm, the step between the early market and the mainstream market is the most difficult to transition through. Both early and late majority need a fundamentally di↵erent marketing strategy and product development than innovators and early adopters do. In Moore’s model, the innovators are referred to as technology enthusiasts, early adopters as visionaries, early majority as pragmatists, late majority as conservatives and laggards as skeptics. Moore (1991) argues that the marketing of a technological advanced product should be focused on one of the groups of adopters at a time. (Moore, 1991)
Figure 6: The Chasm Model
The pragmatists want to have a reference base before choosing a product. Unfortunately, pragmatists believes that visionaries references are worthless. They only want references from peers. On the contrary, the visionaries are comfortable with having technology enthusiasts as references. Hence, when a company is trying to make the transition from visionaries to pragmatists they do not have a reference base as they did when they moved from technology enthusiasts to visionaries. At the same time, the products might not be suitable for the mainstream market. The mainstream market wants generic and stable products, while the early market is looking for customisation and innovation. Therefore, when crossing the chasm, both the references and the products need to change. (Moore, 1991)
The Market Segment
Moore (1991) states that to be able to become the market leader, the early market needs to be fully satis- fied and suggests niche marketing. The pragmatists only want to buy from market leaders which makes it important to choose an early market segment big enough to become the market leader.
The Product O↵ering
A major problem for many start-ups is to deliver a ”whole product”. There needs to be a whole product concept. When the early market has provided their feedback this needs to be incorporated into the product o↵ering. Pragmatists will only buy whole products that solve their needs perfectly and is fully developed.
The product should give them a practical improvement to what they do, without any bugs or missing fea-
tures. The choice of buying the product should be easy. (Moore, 1991)
Figure 7: The Whole Product Model
The Competition
To cross the chasm, there need to be competition. Pragmatists require it. Competition enables the product to continuously be developed and upgraded. Moore (1991) even suggests to create credible competition if there is a lack of it. If there is no competition, the chasm is not ready to be crossed.
Distribution and Pricing
Moore (1991) categorises most distribution channels into two general categories: demand creators and de- mand fulfillers. First, a new technology needs to be well established on the market. To establish the technology, demand needs to be created. Hence, the first distribution channel should be direct sales, a demand creator. Direct sales is optimised to creating demand since you have a sales forces explaining the technology and its benefits directly to customers. When the product is accepted by the mainstream market, other channels, the demand fulfillers, can be used. The most optimised demand fulfiller is retail sales. Price will confirm the leadership position, therefore, a premium should be paid. The price should be set through competitive pricing and not value-based pricing.
2.3 Factors A↵ecting Di↵usion of Technology
Rosenberg (1972) research concerning di↵usion of technology are more focused on the technology rather than whom is adopting it. He argues that the rate at which a new technology replaces an old one is dependent on how fast it is possible so overcome a number of supply side problems. He wants to identify factors that causes the slowness of adoption and explains the variations in the rate of di↵usion between di↵erent technologies.
The factors are focused on certain supply side considerations and will not consider factors such as commodity prices.
Continuity of Inventive Activity
When examining the history of di↵usion of technology, there is an overall slowness identified and what ap- pears to be a wide variation in the rate of di↵usion between di↵erent inventions. The variation in the rate of di↵usion can partly be explained by selection of dates. The invention of a new technology is a continuous process which starts with the initial conceptualization, then the establishment of technical feasibility and finally the commercial feasibility. Between these phases lies series of inventive activity. In reality, an inven- tion is in the beginning often filled with flaws and is only a slight improvement from earlier technologies.
The later inventive activity is often what shapes the possibility for di↵usion by creating the technical and commercial feasibility. Despite this, there has been a perception that technological change is a discontinuous phenomena, mainly due to the convenience of having a set date for when a new technology was created.
How fast the di↵usion rate appears to be therefore depends on whether you set the date from when the first conceptualization happened or when the products became feasible. Hence, this can makes the lag between initial invention and adoption larger and increases the impression of slowness of di↵usion. (Rosenberg, 1972)
Improvements of Inventions after First Introduction
The actual pace of di↵usion is influenced by several categories of technological considerations. As mention before, the inventions are often inefficient or unpredictable when first introduced. There will be very few advantages for using the new innovation, sometimes no advantages at all. Therefore, the di↵usion is bound to be slow and the rate depends heavily on how fast the improvements of the invention are made. (Rosenberg, 1972)
Rosenberg (1972) points out that some new technologies are difficult to anticipate the use of. There is a tendency to take new innovations and conceptualizing them in terms of something familiar. Therefore, the transition is often slowed down as it attempts to break away from the old forms and logic.
Technical Skills Among Users
There is not only the improvements of the innovation that matters for its di↵usion, it is also important that the users skills gets developed. For an innovation to be e↵ectively used, the user needs to understand how to use it. This learning period depends on factors such as complexity of innovation, the extent to which they rely on skill already available and if the skills are transferable from other industries. Depending on how fast the users can acquire the skills, there will take time for the innovation to become superior to previous solutions. (Rosenberg, 1972)
Skills in Machine-Making
The next skill that needs to be developed is the skills and facilities in the machine-making. Successful di↵usion of inventions requires a growth in the capacity to devise, adapt and produce at low cost. Many inventions have been forced to sit on the shelves for a long time due to the lack of mechanical skills, facilities and design and engineering capacity required to realize them. All inventions has a period were the capital goods industries adapt themselves to the requirements of the new technology. Hence, the speed of which the performance are improved, techniques adapted to meet the needs of users and the price is reduced heavily a↵ect the di↵usion of the technology. (Rosenberg, 1972)
Complementaries
The complementarity in productive activity between di↵erent techniques a↵ects the di↵usion rate. For an invention to reach its full potential, other inventions must create bypassing constraints to not hinder the di↵usion of the intervention. There is rarely one single technology that constitutes the complete innovation.
(Rosenberg, 1972)
Improvements in Old Technologies
Rosenberg points out that one of the reasons that new technologies displace old ones slowly is that the old technologies continue to improve. Innovations often appears to induce responses on the part of industries for
which they are providing close substitutes. A new innovation have many times in history served as a e↵ective trigger to improvements in existing products. This form of competition generates economically beneficial consequences, and plays a significant role in explaining the rate of di↵usion of some technologies. As the competition of existing products increases, the new technology needs to improve in order to replace the old.
(Rosenberg, 1972)
2.4 The Product Life Cycle
Innovation in industry is a process that involves an enormous amount of uncertainty, human creativity, and chance. Utterback & Abernathy (1975) created a model of the innovation cycle and argues that any innovation has a finite life. An innovation will eventually get old and be replaced by an new innovation.
They authors divide the Product Life Cycle into three phases; Fluid Phase, Transitional Phase and the Specific Phase.
Figure 8: Product Life Cycle (Utterback & Abernathy, 1975).
The fluid phase represents the formative years of the product. The rate of product innovation is highest during the fluid phase. A great deal of experimentation with product design and operational characteristics take place among competitors during this phase (Utterback & Abernathy, 1975). During the transitional phase the producers learn more about the technology application and about customer needs for the specific innovation. Within a rich mixture of experimentation and competition some center of gravity eventually forms in the shape the dominant design. The dominant design product has features that competitors and innovators mush adhere if they hope to command significant market share following. The emergence of a dominant design is a result of the interplay between technical and market choices at a particular time.
Once the dominant design emerges, the basis of competition changes radically, and the ecology of com- peting firms changes from one characterised by many firms and unique designs, to one of few firms with similar product designs. This is the specific phase, and the competition now shifts from di↵erentiation to product performance and cost (Utterback, 1996).
2.5 Internet Of Things
The Internet of Things (IoT) is defined as the networks of connected machines and sensors with the ability to monitor and manage object in the physical world electronically. IoT is rapidly gaining popularity, not only in industrial and commercial environments, but also in personal life by means of smart devices at home. The vision for IoT is to make our everyday lives easier and boost the efficiency and productivity of businesses and employees and that analysis through data collection will make us do smarter decisions. Data collecting and tracking is essential for IoT, however this is also perceived as a privacy threat by some (Lee, 2017). Protection of data and privacy is on of the biggest challenges for customer adoption of emerging IoT innovations (Badkas et al., 2015).
There are a number of obstacles that IoT needs to overcome in order to successfully be adopted by the majority and deliver its full potential. These are both technical as well as structural and behavioral. These are Technology, Interoperability, Privacy and confidentiality, Security, Intellectual Property, Organization and talent, Public Policy (Lee, 2017).
Technology
The cost of basic hardware and computing power needs to continue to drop in order for a widespread adop- tion of IoT. The price of radio-frequency identification tags, low-cost batteries and other commonly used IoT hardware parts need to decrease. It is also important that the price of computing power and storage continues to decrease for IoT to be able to use all available data and analyse it e↵ectively. (Lee, 2017)
Interoperability
Di↵erent IoT devices and system need to work together in order to realise the full value of IoT applications.
This can for example be accomplished by adopting an open standard or by implementing systems or plat- forms that integrate IoT applications with each other. (Lee, 2017)
Privacy and Confidentiality
IoT often requires a lot of data. The type, amount and specificity of data gathered has created concerns about privacy, confidentiality and integrity. Providers of IoT-products need to provide transparency in what data they collect and how it is used as well as ensure that data are appropriately protected. (Lee, 2017).
Security
Organisations and IoT that gather data must be able to protect the data from unauthorized access and be able to deal with new categories of risk that IoT introduce. (Lee, 2017)
Intellectual Property
There must be a common understanding of the ownership rights to data produced by connected devices. It needs to be clarified who has what rights to the data from a sensor manufactured by one company and part of a solution deployed in a setting owned by a third party. (Lee, 2017)
Organization and Talent
IT is embedded in the physical assets and the IT function and the operating organizations needs to be closely aligned. Furthermore need capacity and mindset to use the IoT to guide data-driven decision making, as well as the ability to adapt their organizations to new processes and business models. (Lee, 2017)
Public Policy
Some IoT applications cannot proceed without regulatory approval. On example is self-driving cars. In addition, regulators must establish rules about liability. Governments also play a big role in setting rules for data practices regarding collection, sharing and use of IoT data. (Lee, 2017)
2.6 Summary of Literature Review
Di↵usion of innovations seeks to explain how, why and at what rate a new technology spreads. Rogers (2003) argues that di↵usion is the process by which an innovation is communicated through certain channels over time among the participants in a social system. These participants, called the adopters, are divided in five categories; innovators, early adopters, early majority, late majority and laggards. The rate of adoption is determined by the characteristics of the innovation as perceived by the social system. There are five attributed of innovation: Relative advantage, Compatibility, Complexity, Trialability and Observability.
”The chasm” is the gap between early adopters and early majority and is considered the most difficult transition between two adopter groups. Both the marketing and the product o↵ering need to be altered to fit the mainstream market. (Moore, 1991)
Rosenberg’s (1972) research concerning di↵usion of technology are focused on the technology rather than whom is adopting it. He has identified six factors that causes slowness of adoption; continuity of inventive activity, improvements of inventions after first intro, technical skills among users, skills in machine-making, complementaries and improvements in old technologies. He explains how these supply side factors a↵ects the various rate of di↵usion in di↵erent inventions and how the rate can sometimes be perceived as faster or slower due to these factors.
Innovation in industry is a process that involves uncertainty, human creativity and change. Utterback
& Abernathy (1975) developed the Product Life Cycle, which aims to explain the di↵erent phases in the innovation cycle. The initial period in which the product innovation is formed is called the ”fluid phase” and involves experiments with product design and many active competitors. The dominant design eventually appears and only a few players with similar product design are then left.
The Internet of Things (IoT) is defined as the networks of connected machine and sensors with the ability to monitor and manage object in the physical world electronically. IoT is rapidly gaining popularity but there are obstacles in the customer adoption such as protection of data and security, that the IoT needs to overcome in order to reach its full potential.
In the next chapter, we will discuss the methods used to fulfill our purpose to analyse the market and the drivers and barriers for the future di↵usion of smart locks in urban areas.
3 Method
This chapter presents our research approach and research process. The research approach describes the inductive approach and why it is chosen. The research process describes the process of conducting the case study, the literature review, the survey and the interviews. Lastly, an analysis of the validity, reliability and generalizability is presented.
3.1 Research Approach
This thesis aims to analyse the current market of smart locks in urban areas and identify drivers and barriers for the future di↵usion through an exploratory prestudy. London has been used as a case city. The main reason for choosing London is that it is one of the biggest cities in Europe. Europe is the continent dominating the global market for smart locks (Transparency Market Research, 2016). Furthermore, London is the biggest e-commerce market in Europe and has a lot of high-income citizens working long hours (Centre of Retail Research, 2016). Hence, the need for services at the home, such as cleaning, is potentially higher and the additional use-cases around a smart lock could therefore be more desirable.
An inductive research approach has been used in this thesis. An inductive approach starts with specific observations with aim to identify patterns and thereafter reach a general conclusion that is most likely true.
Our observations are in the form of a survey, interviews and literature research. Usually, the inductive approach is used when having qualitative methods of data collection, as in this thesis. Even though an inductive research approach cannot guarantee its conclusion, the approach is usually preferred in situations with incomplete information. (Trochim & Donelly, 2008)
To minimise the risk of data source bias (Jick, 1979) and maximise the validity and reliability of the thesis (Denzin, 1978), triangulation was chosen. Triangulation is defined as ”the combination of methodologies in the study of the same phenomenon” (Denzin, 1978). Therefore, more than one method and source of data collection has been used in this thesis. Hence, both a qualitative method and a quantitative method has been used. For triangulation to be e↵ective, the di↵erent methods need to compensate each other so the weakness of one is counter-balanced by the strength of another, otherwise, the triangulation is unnecessary (Jick, 1979).
3.2 Research Process
The research process is consisting of the data collection and the data analysis. The data collection is conducted through three main methods; literature review, interviews and a survey.
3.2.1 Literature Review
To reach a vaster understanding of the smart lock market and the problems associated with last mile delivery, a thorough literature review was conducted. The main sources of the literature review was online databases, such as KTH Primo and Google Scholar, books and published studies in the field. The focus of the literature review was on customer adoption in general, research about smart homes and smart locks and dynamics of industrial innovation. Since the concept of smart locks is relatively new, there was problems with finding published studies on this subject. The main key words used when finding relevant literature were: Smart locks, customer adoption, di↵usion of technology, Smart home technology, Internet of Things.
3.2.2 Interviews
The interviews were primarily semi-structured and conducted face-to-face. In some cases there was no possibility to meet the interviewee in person, in these cases the interview was conducted via phone or mail.
When the interview was conducted via mail, it was structured. All interviews were between 30-60 minutes.
The semi-structured interviews were organised around a number of themes and question areas. The main reason for primarily choosing semi-structured interviews is because they allow for questions to be created during the course of the interview, which is positive as we aim to understand the whole concept around smart locks and customer adoption. Therefore, we needed to understand our interviewees’ opinion about its development and future. (Blomkvist & Hallin, 2015)
Five interviews was held with people with a great knowledge of the smart lock market and customer adop- tion in general. In the interviews we were looking for multiplicity and complexity, rather than comparable answers. This require us to be critical through the whole process. (Blomkvist & Hallin, 2015)
All the interviews were recorded in order to present the results correctly. The majority of the interviews were conducted by two persons in order to minimize the risk of misinterpretation of the interviewees answers (Eisenhardt, 1989).
3.2.3 Survey
The survey was originally conducted with 54 potential customers in London, where 43 of them responded to the entire survey and 11 dropped out before completing it. The respondents were almost evenly divided between males (56%) and females (44%). To ensure that the respondents were potential customers we attempted to target young people working long hours with high disposable income. These people appears to be most likely to buy smart home technology and to appreciate the services built around the smart locks such as easier access for cleaners or deliverers. It was difficult for us to get a randomized sample within this target group since the majority of the people conducting the survey was people reached through our contacts, social networks and people asked on the streets of London. Therefore, the sampling method chosen was non-random sampling, also know as convenience sampling (Blomkvist & Hallin, 2015). The questions focused on customers attitudes and experiences with smart locks and deliveries. In order to understand what type or person was answering the survey, general questions about the person and their housing was also included in the survey. This showed that the majority of the respondents were between the age of 19-34.
Many of the respondents have an annual household income of over £125,000 and 67% worked 46 hours per week or more. The survey also contained attitude questions to determine which type of adopter is answering.
Since we was using convenience sampling, we have to take into consideration that the results from the survey might not represent the entire population. The survey was sent out before the interviews started, mainly because of time limitations. We wanted to ensure the respondents could answer the survey in time for us to analyse the results. If the survey had been conducted after the interviews, the survey could have been adjusted to the answers received in the interview. Since we did not have time for this, we reached out to industry professionals before the survey was sent out to get feedback on the questions.
3.2.4 Data Analysis
After the data collection was completed and presented in the chapter Empirical Findings, the results were analysed using the di↵erent theories and models presented in the previous chapter. All qualitative and quantitative results were combined to reach a high validity and reliability (Denzin, 1978).
The results were organised and the key factors of each model were analysed. In Rogers (1962) model of di↵usion, we first classified which type of adopter is currently buying the smart locks. Thereafter, we analysed the attributes (relative advantage, compatibility, complexity, trialability and observability). The Chasm model (Moore, 1991) were used to understand if the smart lock market is ready to cross the chasm yet and was analysed through its market segment, product o↵ering, competition, distribution and pricing. To further understand the di↵usion process and rate of adoption of smart locks, the market was analysed using Rosenbergs (1972) factors. To understand which phase the smart lock market is currently in, the product life cycle (Utterback & Abernathy, 1975) was used. This model help us categorise the phases in fluid phase, transitional phase and specific phase. Finally, the empirical findings were analysed using the IoT framework and external factors that might influence the smart lock markets were discussed.
3.3 Validity and Reliability
To assess the scientific quality of the thesis we have analysed the method in terms of validity and reliability.
Validity is about relevance and whether the thesis answers the intended question. Reliability measures if the study is done in a correct way, if it is possible to repeat the study and get the same result. (Blomkvist &
Hallin 2015)
To increase the validity, triangulation has been used. The semi-structured interviews have entailed a focus on the research questions, making the answers relevant for the thesis. The written sources have been chosen with great consideration of context to ensure their relevance for answering the research question.
A high reliability will be ensured through source criticism. When conducting the semi-structured inter- views, the possibility of a bias interviewee have been considered and taken into account when analysing the answers. Only sources considered as credible will be used. As mention before, there is a lack of academic papers on smart locks. To find credible, written sources, we have focused on that the author is knowledgeable or has experience within this field.
3.4 Generalizability
In this thesis we have chosen to use London as a representation of all big cities. We cannot for certain know that the findings here will be applicable for all other big cities. Hence, the statistical generalizability will be low (Blomkvist & Hallin, 2015). The analytical generalizability will, on the other hand, be high due to the great detail in describing how we conducted the study (Blomkvist & Hallin, 2015).
The statistical generalizability for the quantitative survey is also low due to the non-random sampling.
3.5 Summary of Method
In order to analyse the current market of smart locks in urban areas and identify drivers and barriers, London was used as a case city. Mainly because its size, both in population but also their e-commerce market. We have used an inductive research approach building on observations from a survey, interviews and literature review. To minimise the risk of data source bias and maximise validity and reliability, triangulation was chosen.
The literature review focused on the smart lock market, customer adoption in general and the last mile delivery problem. The main sources on information was online databases such as KTH Primo and Google Scholar, books and published studies.
The interviews were mainly semi-structured and face-to-face or via phone. One was conducted through mail and therefore structured. The reason for using semi-structured interview was because we wanted to understand the whole concept of smart locks and the interviewees’ opinions about its future. All interviews were between 30-60 minutes.
The survey had 54 respondents, mostly found through contacts, social networks and on the streets of London. Only responses from Londoners were used in the results. The sampling method we used was convenience sampling since it was difficult for us to reach a randomized sampling through the channels we used. The people we targeted was young people with high disposable income that works long hours. The questions were focused on customer attitudes, smart locks and deliveries.
After all results were collected, an analysis was conducted using the theories and frameworks presented in previous chapter. The empirical findings was analysed with the key factors of all theories.
To increase the validity and reliability, several sources of information has been used and possible biases of the interviewees have been considered in the analysis. The statistical generalizability will be low since we cannot ensure that London can represent all urban cities and the survey sampling method was non-random.
The analytical generalizability will be high due to great detail in describing how the study was conducted.
In the next chapter the empirical findings from the literature review, survey and interviews be presented.
4 Empirical Findings
This section will present the results from our empirical studies. This is divided into three parts: a study of the smart lock market in the chosen empirical context, London, a presentation of the results from a survey of convenience conducted in London as well as the results from interviews with professionals in the smart home and last-mile delivery market.
4.1 Mapping of the Smart Lock Market in London
4.1.1 The Smart Home Technology Market
The current state of consumer adoption for smart home technology is between early adopters and early majority (Branca, 2016). Thus, at the chasm (Moore, 1991). Innovators and early adopters makes up about the first 15% of the market and it is hence important to cross the chasm and start to capture the largest part of the early majority. However, 80% do not see the extra value of buying smart products, which makes the chasm hard to cross. (Branca, 2016)
The two groups identified as the more likely to buy smart home products are called ”Nesters” and
”Impressers” and make up 25% of the total market for smart homes. A survey conducted by over 7000 consumer shows that both Nesters and Impressers are more willing to pay for quality, purchase tech before others, pay for convenience and invest in home improvement than the average consumer. The majority, over 69%, of the consumers in these groups are over 35 years old. The two most crucial factors to drive consumer adoption is (1) strong value propositions and (2) design and user experience. With strong value proposition means connected and integrated solutions, end-to-end support and service integrations. Collaborations between companies that can provide smart home products and service and companies that support value- added applications in the smart home needs to exist in order to provide a strong value proposition. (Branca, 2016)
A forecast by Joseph Branca at Strategy Analytics (2016) shows a significant growth in total consumer spending on smart home products and services the upcoming year. Total growth spending is expected to grow from $73 billions in 2016 to $128 billions in 2020 globally and from $12 billions in 2016 to $20 billions in Western Europe (Branca, 2016).
Many of the smart home technology companies are still experimenting with di↵erent strategies. It is hard to determine which companies that will succeed, but there are indications on factors that are increasing the probability of success. Companies that are doing well in the smart home market often invest heavily in sales and customer support. They also often o↵er a professional installation and have an e↵ective marketing plan.
This is important, as many potential customers still do not fully understand a smart home technology’s potential. Many companies also have an end-to-end control and control almost every part of the o↵ering.
There are also factors that companies that are doing less well in the smart home technology market have in common. This is lack in investment, a revenue model built around one-time purchases and that many companies lack the personnel and capabilities to launch consumer products (Branca, 2016).
4.1.2 The Smart Lock Market and Mapping of Available Smart Locks
There are several companies o↵ering smart locks. Most of these are relatively new start ups but also the established British lock maker Yale has introduced their smart lock in the United Kingdom (Yale, 2016).
The design and function of the smart lock di↵ers between di↵erent producers and smart lock models.
All identified smart lock producers use Bluetooth to open the door via the Smart phone and some also have internet (WiFi) solution. The user needs to be close to the lock in order to open via Bluetooth while the user can be anywhere in the world when opening via internet. All producers have another key connected to the lock, mostly physical key fobs. The majority of the identified lock models have additional functions available.
This includes being able to grant temporary access and being able to see who and when someone access the door through an activity log. Today’s smart home technology products are mainly focused on sustainability and security (Olick, 2016). Smart locks are primarily used to increase security and awareness. Being able to give out temporary electronic keys to service personnel or friends who need to access the house when the owner is away is an additionally convenience factor with the smart locks. The smart locks produced by Yale are the only models that not o↵ers access sharing and activity log (Yale, 2016). Figure 9 shows a summary of the features of the di↵erent smart lock available to buy and use in the United Kingdom.
Figure 9: Available Smart Locks and Features
August Smart Lock and Glue Home are two companies that has created more use-cases for the smart lock, meaning more functions, by creating partnership with other companies. August Smart Lock have a partnership with Airbnb (August, 2015). Airbnb is an online marketplace and hospitality service, enabling people to list or rent short-term lodging including vacation rentals, apartment rentals, homestays, hostel beds, or hotel rooms. The company is merely a broker and does not own and lodging. (Airbnb, 2017). This partnership means that the tenants automatically receives an notification that they will have access to the rental during a specific time period. When the reservation ends, access to the property is automatically revoked. (August, 2015). Both August and Glue Home have created partnership with food and delivery companies in their initial home-market, the US and Sweden. Glue has a partnership with the delivery companies Postnord and Bring, which means that the property owner can allow these to delivery the parcels into their home while being away. ICA is a Swedish food grocery company and the partnership allows them to deliver the food directly to the fridge while the owner is away. (Orre, 2017a)
The functions that August Smart Lock and Glue Home has created around their smart locks adds another dimension to the market for smart locks. Furthermore, it builds up a revenue model that is not only built around one-time purchases. The smart lock producers can take a charge when other companies are using their access and build a sustainable revenue model.
The research conducted by Grand View Research, Inc. (2016) shows an anticipated market size for smart locks globally at $24.20 billion by 2024, compared to estimated market size of $404.1 million in 2015. The increase of cloud-based lock management solutions and home access will contribute to the expected growth.
The main challenges the smart lock manufacturers are facing are the high RD costs and the increase in in electromechanical door locks instead of the customary mechanical locks. Even thought the design and function di↵ers a bit between the locks many are similar to each others. Therefore, manufacturers are focusing on creating easy-to-install locks to di↵erentiate themselves.
A similar analysis has been conducted by Transparency Market Research (2016) on the global smart locks market. They have identified the main driver to be an increasing demand for secure locks. The governments have also been an important factor in the rapidly expanding smart lock market. Many o↵ers support in the aim to broaden the scope of the smart city infrastructure. The main treats for the smart locks manufacturers identified here are the treat of cyber-terrorism. It will be important for the manufacturers to have top-tier security solutions to minimise the risk for hacking. Europe is currently dominating the global market for smart locks.
4.1.3 Competitive Substitutes
There are other competitive solutions to the smart lock market, as the smart lock have many di↵erent use cases. This means that the smart lock can provide di↵erent functions, the most primary being to lock and unlock the door electronically. As seen in the mapping of available smart locks some products also o↵ers other use cases, such as in-home delivery through partnership with di↵erent companies. The collaboration between smart lock producers and di↵erent delivery companies can be a solution to the growing “last mile delivery” in London. Other solutions to this problem are hence competition for the smart lock market.
The last mile delivery refers to final movement of goods from the hub to the customer. It is the final leg of the complete journey of the goods and consists of obstacle and complexity. The last mile involves around 30% of the total logistic cost. The exponential growth of e-commerce in London and today’s more empowered consumers has increased the expectations for speed and the experience of deliveries. The retail and e-commerce has adapted to this, but the last-mile still poses many challenges. (Cohen, 2016). London
is the biggest e-commerce market in Europe. B2C sales accounted for 15.2% of total B2C sales in the United Kingdom 2015 compared to 7.4% of total B2C sales worldwide. (Centre of Retail Research, 2016)
There are several companies, start-ups as well as established companies, with di↵erent solutions in how to provide a convenient delivery to customers. Amazon and InPost UK have lockers located in London where products are delivered and fetched using a personal code emailed to the receiver (InPost UK, 2017), (Amazon, 2017). Click and Collect is also a growing trend among retail and grocery companies. The customer purchases over Internet and choose to pick it up at the store or an assigned pick up station located in for example grocery stores. Doddle Parcel has several pick-up stations in London where customers can pick up parcels from connected companies (Doddle, 2017). Several companies have an in-house Click Collect function where customers can order products on the website and collected in store. Doddle are selling infrastructure systems for companies to create their in Click Collect functions. Argos, one of the largest high street retailers online, is one example of a company which has a successful in-house Click Collect. The company trades both through physical stores and online. They o↵er Click and Collect, same day delivery and delivery in the weekends. (Argos, 2017). Click Collect and other delivery solutions are in in-direct competition to the smart lock market as they provide the customers with some of the utility as the smart locks. Figure 10 provides a summary of the market competition for the smart lock market.
Solutions to the last mile delivery problem are also beneficial from an environmental perspective. If the parcel is delivered directly at the first try of delivery it prevents several journeys with car or other transportation. The current situation where the parcel is being brought to the receiver and then back to the delivery station if no one is home to receive and open the door often require several tries and travels between the delivery point to the receiver.
Figure 10: Smart Locks Market Competition
4.2 Consumer Behaviour and Adoption in London
4.2.1 Survey of Convenience
The answers from the survey of convenience are presented below, divided between the categories Charac- teristics of the Respondents, The Respondents Homes, Technological Attitudes of the Respondents, Smart Locks, Shopping Habits and Trust.
Characteristics of the Respondents
As mentioned in the Method chapter, the respondents are almost evenly divided between males (56%) and females (44%). The majority (87%) of the respondents are between the age of 19-34 with 30% between 19-24 and 57% between 25-34. A large part of these respondents (41%) have an annual household income of over
£125,000. 67% of the respondents are working 46 hours per week or more, with 30% working more than 60 hours per week.
Figure 11: Characteristics of the Respondents
The Respondents Homes
The most common type of housing is an apartment with either a locked key or a key fob at the entrance (50%) and the second most common is a house with their own entrance door (26%). The most common types of locks are ”Key cylinder on outside” (26%), ”High security night latch rim lock” (26%) and ”Euro cylinder with separate handle” (24%). A lot of the respondents have several di↵erent types of locks.
Technological Attitudes of the Respondents
The majority (73%) of the respondents do not currently own any smart home products. Of the respondents that have smart home products, the smart thermostat is the most popular with 16% claiming that they own one. No one currently owns a smart lock. When asked about how early you generally try a new technology, the majority identify themselves as being ”In the middle” (45%). Thereafter, the answers were fairly evenly divided between ”Among the first” (20%) and ”Among the last” (30%).
