Smart Digital Signage

Table of Contents

1. Introduction
1.2 Background
1.2 Problem
1.3 Research question
1.4 Delimitations

2. Extended background
2.1 Smart technology
2.2 Environmental gsychology
2.3 Atmosgheric eGGects research

3. Methodology
3.1 Choice oG research strategy and method
3.1.1 Scenario−based case study
3.1.2 Choice of research method
3.1.3 Choice of data analysis method
3.1.4 Alternative approaches
3.1.5 Scenario−based case study research ethics
3.2 Agglication of method
3.2.1 Scenario
3.2.2 Data collection
3.2.3 Data analysis technique
3.2.4 Ethical deliberations

4. Results
4.1 Thematic analysis
4.1.1 Themes from the codes
4.2 The inGluence of smart environment
4.2.1 Perception of the technology
4.2.2 Perception of overall atmosphere
4.2.3 Pleasure, Arousal & Dominance
4.2.4 Behaviour

5. Discussion
5.1 End summary
5.1.1 Study findings summarized
5.1.2 Study summarized
5.2 End discussions
5.2.1 Conclusions
5.2.2 Originality and significance
5.2.3 Limitations and future research
5.2.4 Authors final discussions

List of references

List of Figures

Figure 1 - Three different design models

Figure 2 - Influence of atmospheric variables

Figure 3 - Two Dimensions of Emotion and Eight Major Emotional States

Figure 4 - The Laboratory Environment

Figure 5 - Summarized themes of the study to answer the research question

List of Tables

Table 1 - Summary of smart object types

Table 2 - Summary table of atmospheric research

Table 3 - Measurement scales

Table 4 - Interview questions and their respective motivation

Table 5 - Interview 1

Table 6 - Interview 2

Table 7 - Interview 3

Table 8 - Interview 4

Table 9 - Interview 5

Table 10 - Interview 6

Table 11 - Interview 7

Table 12 - Interview 8

Table 13 - Interview 9

Table 14 - Interview 10

Table 15 - Themes from the codes

Abstract

Within the topic of Internet of Things (IoT) smart objects are a key concept. The concept of making everyday objects smart. Smart objects that can understand and react to their environment, creating a smart environment. However, with the fast technological development leading to more smart environments in the physical world, not much research has been done on how this will influence users from an Environmental Psychology perspective. Earlier research on smart technologies has shown that users who received real-time feedback on their behavior got their attitude influenced and also changed their behavior, creating an interest to further explore the possibilities and impact of this technology. Marketing researchers have done Environmental Psychology studies for a long time to examine how other environmental stimuli (light, music, scents and digital signage etc.) influence people’s perception, emotions and behaviors using the Mehrabian-Russell model to build stimulating environments also known as atmospherics. This study aims to solve the lack of research on how the emerging smart environments will influence consumers. In order to address the research problem, this research intends to answer the following research question:

“How will a retail example of a smart environment influence consumers from an environmental psychology perspective?”

The research strategy was a scenario-based case study, where the participants got to experience a retail scenario with a simulated smart environment in a laboratory setting. The data collection method were in-depth semi-structured interviews that was conducted on 10 participants, randomly selected. Thereafter a thematic analysis was conducted as a data analysis method. Data extracts were theory driven coded and categorized under the environmental psychology themes. The results of this study show that smart environments are perceived as a positive as useful technology contributing to a personalized and interactive atmosphere. The emotional response from the participants were strong, expressing excitement and pleasure after experiencing the smart environment. The behavioral response was also positive expressing a desire to further explore the environment together with a high degree of enhancement of performance and satisfaction of tasks performed.

This study contributes with deeper knowledge about the impact of a future networked society and also to conclude using smart environments as a self-service customer-facing technology working as an efficient atmospheric tool leading to higher customer satisfaction and most likely more sales.

Keywords - Internet of Things, Smart Environments, Environmental Psychology, Atmospherics, Retail

Acknowledgments

After huge amount of reviewing earlier research together with in-depth discussions and hard work we have been able to finalize this thesis within the area of Immersive networking at the department of Computer-Science at Stockholm University. We would like to thank our supervisor professor Theo Kanter for helping us, guide our research and keep focus on our scope of research to make a valuable contribution. We would also like to mention our thesis peer-reviewers Andree Antfolk and Rikard Branting for contributing with constructive feedback to enhance our report.

1. Introduction

This thesis is written within the field of Computer-Science towards the area of Immersive networking. Immersive networking includes topics such as the Internet-of-Things (IoT), Big Data, Cloud Infrastructure as well as privacy. This research field comprehends with the future challenges for connecting people, places and things, both in the real and the virtual world, and how it enables us to live in new ways in a Networked Society (DSV 2014).

The IoT topic focus on integrating four perspectives:People,Things,DataandProcess.

The topic covers the possibility to connectThingsthat would not regularly be considered as a part of the digital devices (Rahmani 2015). One of the essential technologies that make this possible is the increasing use of wireless networks that enable more devices and infrastructures to be implemented seamlessly into the physical environment (Poslad 2009).

These Things are seen as one of the keys for the vision of IoT, with new emerging technologies such as near field communications, real-time localization, and embedded sensors that will be able to make everyday objects into smart objects that can understand and react to their environment creating a smart environment. These objects are to be considered as the building blocks for the IoT and will enable novelty to computing applications (Kortuem, Fahim, Fitton & Sundramoorthy 2010). This concept will change the way we know the world, with IoT working as a digital extension into the physical world (iBeacon n.d.).

1.2 Background

In an increasingly digitalized world populated by human beings but also digital devices designed to enhance our life in different areas. The physical world is becoming more digitally measured and covered with smart technologies. These technologies can open doors as we approach them and turn lights on as we enter a room, together with being linked to other information systems. (Poslad 2009).

One early on smart technology is Smart Shopping Carts implemented in retail environments, Shopping carts equipped with scanners attached making it possible for consumer to keep track of their total price when shopping in real-time. An earlier study, published in the Journal of Marketing by Koert van Ittersum, Brian Wansink, Joost M.E. Pennings, & Daniel Sheehan called Smart Shopping Carts: How real-time feedback influences spending (2013), examine the influence of this self-service customer- facing technology on attitude and in-store behavior because of real-time feedback on total spending. The participants in these studies were budget and non-budget shoppers. The results of the study show that real-time feedback has an impact on the total spending behavior and that it improves the shopping experience for budget-shoppers due to reducing the stress of keeping mental track of how much you spend while shopping to not exceed your budget. According to the authors further research to examine how real-time feedback could influence other user behaviors and attitudes because of the smart technologies possibilities of skipping the checkout lane, personalization, with customized and timely offers, promotions and recommendations throughout the shopping route would be promising. Together with that “85% of leading retailers rate self-service customer-facing technologies as one of the three top opportunities for increasing consumer satisfaction and revenue” (Van Ittersum et al. 2013)

Retailing has always been evolving together with technology, but probably never as fast before as the last decade with the spread of the internet and the ubiquity of smart devices such as smartphones, tablets etc. Retailers are always working with new technology and trying to find new ways to better meet, serve their customers and to enhance the shopping experience (Grewal, Roggeveen & Runyan 2013). Philip Kotler (1974) mentioned early on how consumers in their purchase decision-making get influenced by more than just thetangible productorservicebeing offered.

Thetangible product—a pair of shoes, a refrigerator, a haircut, or a meal —is only a small part of the total consumption package. Buyers respond to thetotal product. It includes the services, warranties, packaging, advertising, financing, pleasantries, images, and other features that accompany the product.

(Kotler 1974, p. 48)

One of the total products most important feature according to Kotler (1974) is the place where it is bought or consumed, more specifically the atmosphere of the place, stating that it is more important than the product itself during the purchase decision and that the atmosphere can even be the primary product. This means that marketing planners need to master spatial aesthetics, as well as other marketing tools such as price, advertising, public relations and personal selling. The term for this used by Kotler (1974) is atmospherics. “Atmospherics is the effort to design buying environments to produce specific emotional effects in the buyer that enhance his purchase probability.” (Kotler 1974)

One relatively new popular atmospheric tool is digital signs with its technological advantages. Digital screens showing video material with content such as advertisements, community information, news and entertainment and the ability of flexibility and nimbleness being able to be networked and remotely updated (Dennis, Michon, Brakus, Newman & Alamanos 2012). The purpose is to attract, stop customers and let them view a targeted content while they are in the mood to buy. This atmospheric tool has first shown to be an effective tool to involve customers, together with other methods such as in-store displays, product trials and sampling (Dennis et al. 2012). This is of importance when previous research by Wakefield and Baker (1998) have shown that involved customers feels more excitement that leads to repatronage intentions and outshopping.

In the article New insight into the impact of digital signage as a retail atmospheric tool (Dennis et al. 2012) that was published in the Journal of Consumer Behaviour, the authors wanted to examine digital signage as an atmospheric tool from an Environmental Psychology perspective. The purpose of the article was to get insight into consumer’s perception of retail atmosphere, the emotional response and how their behavior differs when using digital signage, and when not. The results of the study indicate that digital signage is an effective environmental stimulus and that it influenced the consumer perception positive, affected consumers with enjoyment to their shopping experiences and provided useful information. According to the authors further research such as exploring the integration of smart technologies and digital signage is recommended.

Previous research has shown how these smart devices, such as smart-shopping carts, have influenced consumer behaviors and attitudes because of its ability to sense and react on user’s behavior. Together with earlier studies in Environmental Psychology that have shown how technological developments such as Digital Signage can be an effective atmospheric tool that influence consumer’s perception, emotional response and approach behaviors positive in retail environments. With IoT emerging because of the fast technological development with increasing capabilities of smart objects in the physical environment making smart environments more common. This thesis aims to further research the impact of the smart environments from an Environmental Psychology perspective using the Mehrabian-Russell model (described later) and knowledge based on previous studies. More accurately; how an example of a smart environment as an atmospheric tool, being able to providing more personalized and timely information due to smart activity-aware objects, will influence consumer’s perception, emotional response and approach and avoidance behavior.

1.2 Problem

The problem this thesis addresses therefore is that there is a lack of research on how the emerging smart environments will influence consumers using an Environmental Psychology framework.

1.3 Research question

Therefor to answer to this problem the research question of this thesis is the following:

How will a retail example of a smart environment influence consumers from an environmental psychology perspective?

When consumers interact with smart objects (smart shoes in our case), the smart objects can sense the interaction and broadcast to a smart device (digital sign in our case) that can react more timely and respond with a personalized visual content for the user. How will this retail example of a smart environment influence the user perception, emotional response, and approach / avoidance behavior.

1.4 Delimitations

This thesis will have a delimitation on the smart environment being examined. Our research example smart environment will be a combination of one smart device, a smart digital signage together with specific smart object Estimotes stickers. They are small computers with an ARM processor, memory, Bluetooth module, and temperature and motion sensors. Powered by a coin battery, they broadcast radio signals through built-in antennas. Smart devices in range receive those signals and compatible installed apps can then respond (Estimote 2016). These are detachable being able to make regular objects into smart objects. The study will be delimited to a retail scenario in a laboratory setting instead of a real scenario in an actual retail setting due to lack of resources. Due to the time frame of the thesis the response from the smart device will be simulated by the observer instead of developing an application. The extended background for this thesis gives us general knowledge of smart technology and smart environments and its possibilities together with explaining the environmental psychology framework with the Mehrabian-Russell model. Earlier studies on atmospheric effects is also being reviewed to further motivating the interview questions for answering the research question.

This paper aims to examine how consumers get influenced by an retail example of a smart environment consisting of Estimote Stickers attached to three pair of running shoes, making them into smart objects and a simulated smart device. A smart digital signage responding with relevant product information (Product name, picture, price and product recommendations) depending on which shoe the participant is interacting with.

2. Extended background

2.1 Smart technology

IoT is emerging and as mentioned before smart technologies are one of its core concepts. “The concept smart simply means that the entity is active, digital, networked, can operate to some extent autonomously, is reconfigurable and has local control of the resources it needs such as energy, data, storage, etc.” (Poslad 2009). In the book Ubiquitous Computing Smart Devices, Smart Environments and Smart Interaction by Stefan Poslad (2009) three basic architectural design patterns are proposed, shown in Figure 1 (Poslad 2009, p.26). Although they should not be seen as mutually exclusive as they overlap.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1 - Three different design models

According to Kortuem, Fahim, Fitton & Sundramoorthy (2010) these smart objects can be described with three different design dimensions:

Awarenessis a smart object’s ability to understand (that is, sense, interpret, and react to) events and human activities occurring in the physical world.

Representationrefers to a smart object’s application and programming model — in particular programming abstractions.

Interactiondenotes the object’s ability to converse with the user in terms of input, output, control, and feedback.

(Kortuem, Fahim, Fitton, & Sundrasmoorthy 2010, p. 45)

These have the possibility to sense, record and interpret events happening to them and around them, be able to react on their own, intercommunicate with other objects, and communicate information with users (Kortuem et al. 2010). After evaluating various designs through practical experimentation and prototyping these dimensions the authors identified three canonical smart-object types: activity-aware objects, policy-aware objects, and process-aware objects. Table 1 (Kortuem et al. 2010, p.46) summarize how these are related to the three design dimensions.

Table 1 - Summary of smart object types

Abbildung in dieser Leseprobe nicht enthalten

To further explore the design of these smart objects types, example applications were applied in scenarios on an industrial workplace. Industrial workplaces have an extensive external infrastructure; to overcome this they choose to convert existing work objects to smart objects using embedded sensor devices. This resulted in smart work objects being able to interpret data, make decisions and communicate to each other. They also implemented a small display to enable user output.

Most of the recent work on smart objects has been on the technical aspects. Focusing on hardware platforms, software infrastructure in areas such as supply-chain management, enterprise applications, healthcare and industrial workplace support. Meanwhile the Human-interface aspects of smart-object technology have just started to receive attention. IoT can’t be seen as only a technical system because of entanglement between physical and digital entities, IoT must also be examined as a human-centered interactive system. This approach implies that smart object design has to go further than just software and hardware. Subjects as interaction design and social aspects have to be considered as well

(Kortuem et al. 2010).

In this thesis we are going to use a similar approach using embedded sensor devices to convert existing objects into smart objects. But in this study having an example of a smart environment in a retail scenario and focus on the social and human-interface aspect.

2.2 Environmental psychology

Environment and its influence on humans and their behavior have been accepted by a broad audience from landscapers, architects, interior designers and some far-sighted retailers. In the last decades it has also gained interest from psychologists researching the area (Donovan & Rossiter, 1982). This has resulted in the discipline known asEnvironmental Psychologythat examines the connection between environments and human affect, cognition and behavior (De Young 2013).

It burrows from cognitive psychology the notion that all environments are patterns of information and that people are fundamentally information-processing organisms, deeply motivated to remain informationally, and thus environmentally, competent. In their pursuit of goals, humans need both to understand current environmental patterns and to continuously expand their proficiency by exploring and learning from new patterns.

(De Young 2013, p. 14)

The difference is subtle according to De Young (2013).

Rather environmental psychology explores the environmental context of human behavior and wellbeing. This context might be physical (e.g., home, office, park), social, conceptual (e.g., design, narrative), vast or small. It might be known from direct experience or from pre-familiarized with something not yet present, something that might be experienced only indirectly through stories or simulations. The latter is possible because one of the astonishing effects of our information- processing capability is our being able to feel at home in a place we do not yet inhabit.

(De Young 2013, p. 14)

As mentioned earlier Kotler emphasize the importance of the store atmosphere for the total product in his article Atmospherics as a Marketing Tool in the Journal of Retailing. Therefore, all marketers should master atmospherics, being able to create environments that will produce specific emotional responses in the customers to enhance purchase probability (Kotler 1974).

In the article Store Atmosphere - An environmental psychology approach by Donovan and Rossiter (1982) discuss some options why earlier research has been unable to document the effect of store atmosphere. The emotional responses are hard to verbalize, they are brief and therefore hard to recall and they influence behaviors in-store rather than external behaviors. Noteworthy according to the authors is that most studies used structured questionnaire surveys, asking the participant to rank a list of preselected attributes in term of approach behaviors. While one study by Dickson and Albaum (1977) with in-depth interviews allowed the participants to verbalize their own descriptions and produced a more emotional response.

Donovan and Rossiter (1982) presents the Mehrabian-Russell environmental psychology model as a possible theoretical framework in the study of store atmosphere.

Mehrabian and Russell (1974) suggests a model of stimulus- organism response (S-O-R) which explain that environmental stimuli (S) influence emotional response of organisms (O) which in turn, initiates consumers’ behavioural response (R).

(Ramlee & Said 2014, p. 427)

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Figure 2 - Influence of atmospheric variables

This model shown in Figure 2 (Ramlee & Said 2014, p. 428) predicts how a person will behave in a retail environment, if the environment will influence their emotional response and behavior. According to this model all responses and behavior in a retail environment can be considered as approach or avoidance. The model proposes that there are three basic emotional states that influence the approach-avoidance behavior. The emotional states are: Pleasure - Displeasure, Arousal - Nonarousal and Dominance - Submissiveness (PAD) (Donovan & Rossiter 1982)

Pleasure-displeasure refers to the degree to which the person feels good, joyful, happy, or satisfied in the situation; arousal-nonarousal refers to the degree to which a person feels excited, stimulated, alert, or active in the situation; and dominance-submissiveness refers to the extent to which the individual feels in control, or free to act in, the situation.

(Donovan & Rossiter 1982, p. 38)

Although the PAD dimensions are statistically independent the model argues for a conditional interaction between pleasure and arousal that decide the approach-avoidance.

In a neutral (i.e., neither pleasing nor displeasing) environment, moderate arousal enhances approach behaviors, whereas very low or very high arousal leads to avoidance behaviors. In a pleasant environment, the greater the arousal, the greater the approach behavior. In an unpleasant environment, the higher the arousal, the greater the avoidance behavior.

(Donovan & Rossiter 1982, p. 39)

This condition is shown below in Figure. 3 (Donovan & Rossiter 1982, p.39)

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Figure 3 - Two Dimensions of Emotion and Eight Major Emotional States

Approach refers to the desire to explore and avoid refers to a desire to leave the environment. These behaviors are considered to have four different aspects.

1. A desirephysicallyto stay (approach) or get out of (avoid) the environment
2. A desire or willingness to look around and toexplorethe environment (approach) versus a tendency to avoid moving through or interacting with the environment or a tendency to remain inanimate in the environment (avoidance)
3. A desire or willingness tocommunicatewith others in the environment (approach) as opposed to a tendency to avoid interacting with others or to ignore communication attempts from others (avoidance)
4. The degree of enhancement (approach) or hindrance (avoidance) ofperformance and satisfaction with task performances.

(Donovan & Rossiter 1982, p. 37)

Donovan and Rossiters (1982) study showed that the Mehrabian-Russell model is a valid starting point when studying retail atmosphere and the influence on shopping behavior. Many studies have since used the model to predict emotional response and behavior based on different environmental stimuli (Ramlee & Said, 2014).

In this thesis we are going to use the Mehrabian-Russell model with in-depth interviews based on the previous research in environmental psychology that found it to be valuable to forecast atmospheric effects to better be able to predict the impact of smart environments.

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