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Description of CCE (Cognitive Chrono - Ethnography)

Summary


Cognitive Chrono-Ethnography (CCE), is a new study methodology for understanding people's in situ behavior selections in daily life. People select their next behavior to maximize their satisfaction for a given behavioral goal. They appropriately coordinate available cognitive resources to make the best decisions by using their knowledge of past experiences and by processing input from the environment and individual intrinsic state. When a study field is specified, CCE starts by defining critical parameters for understanding people's behavior by considering the nature of behavior selection processes in the field in question, and then designing ethnographical field observations by taking into account the fact that their results will be described in terms of the specified critical parameters. The participants' behavior is recorded, followed by a series of structured retrospective interviews for the purpose of describing their present behavior and obtaining their history of behavioral development. Analysis of the interview results aid in developing models of present behavior selections and their chronological changes.

Introduction


A series of a person's in situ behavior selections can be regarded as the results of moment-by-moment problem-solving activities. The "problem" in this situation is to realize a goal state by successively applying moves in the problem space. Each move causes a transition from one state to another, and the move finally chosen at a specific state depends on the available resources that the individual can manipulate during the time allowed. If enough time is provided, it is possible for a person to select a move that has a greater expected benefit. In this situation, one can utilize as much knowledge as possible to achieve better solutions. However, if enough time is not allowed, the individual must choose an ordinary solution, which, in most situations, is the one that he or she has adopted most frequently in similar situations. This decision is made without deliberate consideration concerning possible future development of the course of actions.

People's in situ behavior can be understood by a two-tiered research approach: domain-independent theorization and domain-dependent instantiation, or theoretically motivated case studies. Domain-independent theorization deals with what people would do at abstract levels. For example, means-end analysis deals with the strategy that people would adopt in problem-solving situations. Newell and Simon (1963, 1972) proposed the General Problem Solver (GPS), a program for solving problems by generating heuristics by means-ends analysis. Although GPS is effective for some problem domains, its usefulness is limited in dealing with time-crucial phenomena, including people's behavior selections in real-world settings. Soar, a direct descendent of GPS developed by Laird et al. (1987), considered real-time constraints by mapping its primitive elements to human cognitive architecture. However, since Soar is not closely coupled with the external world, it is unable to deal with intimate interactions between human beings and the environment. It cannot express the dynamic aspect of human beings' behavior in which the state of the external world changes as human beings take action and human beings' actions depend on the state of the external world. The Model Human Processor with Real-Time Constraints (MHP/RT), developed by Kitajima and Toyota (2012), further extended Soar and GPS to deal with synchronization between a person's behavior and the external environment in the time dimension, which is critical for simulating people's in situ behavior under real time constraints.

Due to the development of the fundamental theoretical understanding of human beings' behavior selection processes, it has become possible to gain an understanding of our daily activities. This subsite concerns domain-dependent instantiation for understanding people's in situ behavior and proposes a novel methodology, Cognitive Chrono-Ethnography (CCE), for use in this research activity. This subsite derives CCE by considering requirements that are imposed on a study methodology for dealing with people's behavior selections in time-critical real-world settings. It first describes the CCE methodology and its requirements. This subsite also provides some case studies that applied the CCE methodology in separate section.

Cognitive-Chrono Ethnography (CCE)


Our 24-hour day is roughly divided into three parts: the hours for work to earn money, the hours for biological activities to live, and the hours for spending time for feeling satisfaction or happiness (i.e., leisure activities, such as playing sports, watching TV, traveling, going to the movies, and so on). Traditionally, the first two categories have been addressed in such study fields as human factors and ergonomics. However, the third category has seldom been studied because of the diversity involved in such activities. This section starts by describing requirements for the CCE methodology to study people's in situ behavior that belongs to the third category. It then suggests four critical factors that can be considered the primary causes of the diversity, which must be disentangled by CCE to obtain coherent understanding of how daily behavior is organized.

> Requirements for the CCE Methodology to Study People's in situ Behavior


What to Understand: We suggest that understanding human beings' in situ daily behavior selections involves understanding relationships between memes that were active at the time the behavior was undertaken and overtly observed behavior, by considering those factors as Two Minds, the multiplicity of goals, and the nature of memory processes. A detailed explanation of memes and these factors, which are called behavior-shaping factors will be given later.

Therefore, a CCE study must answer the following questions about behavioral events:

  • Which memes were activated?
  • Under which conditions were the memes activated?
  • How had the memes been formed?

The answers will be analyzed to construct models that explain and predict people's behavior in the study field.


How to Understand: Next, we discuss the kinds of data that are available for deriving answers to the above questions. The origins of the data are the results of observing people's daily behavior selection processes in real-world settings.

Data that are obtainable with little interference with the participants' activities are as follows:

  • Behavior observation records: Investigators record the participants' behavior without intervening in their activities.
  • Behavior measurement records: Sensors are attached to the participants to record their physiological activities (e.g., a pin microphone to record their vocalization, a small ear-mounted camera to record the scene they are viewing, and an electrocardiograph to record their physiological responses to the events).
  • On-site self-reports: Study participants themselves take photos, brief notes, and voice recording concerning their activities while their memories of the events remain fresh.
  • Retrospective interviews: Behavioral observation records, behavioral measurement records, and on-site self-reports described above are used to reconstruct participants' active memes at the time of events by conducting a series of retrospective interviews.

> CCE Procedure


CCE is carried out in the following six steps:

  1. Define the study field: It is important to specify the study field sufficiently. Manifestations of behavior-selection shaping factors under the characteristic atmosphere of the study field are observed in the study field.
  2. Define critical parameters: Critical parameters are initial hypotheses about the behavior-selection shaping factors that should work when people's activities are organized in the study field. Steps 1 and 2 are conducted interchangeably to define the parameter space to be explored.
  3. Select elite monitors: Study participants (elite monitors) are selected. Each point in the parameter space has values. The study question is "what such-and-such people would do in such-and-such way in such-and-such circumstance (not an average behavior)." Therefore, elite monitors are selected by consulting the parameter space. In this process, it is necessary that the points in the parameter space, which correspond to the elite monitors, are appropriate for analyzing the structure and dynamics of the study field. Monitor selection is conducted by purposive sampling rather than by random sampling.
  4. Record the monitors' behavior: The elite monitors are expected to behave as they normally do in the study field. Their behavior is recorded in such a way that the collected data is rich enough to consider the results in terms of the parameter space.
  5. Conduct interviews: The collected data are used to clarify the structure of the meme of the elite monitors by conducting a series of structured interviews. The results are analyzed for the purpose of defining the basis of the representations of the collected data.
  6. Construct models: The last step of CCE is to construct models that address "what such-and-such people would do in such-and-such way in such-and-such circumstances."

> Behavior-Selection Shaping Factors


CCE studies are carried out by keeping in mind the following critical factors for understanding people's daily behavior.

Two Minds: Recently, Daniel Kahneman, winner of the Nobel Prize in Economics in 2002, introduced behavioral economics, which stems from the claim that human decision-making is governed by Two Minds. This theory is based on the idea that human beings' behavior is the outcome of two different systems, an "Experiential Processing System (System 1)" and a "Rational Processing System (System 2)" (Evans and Frankish, 2009; Kahneman, 2003), which essentially extends the concept of bounded rationality (Simon, 1956) in the domain of judgement and decision-making under uncertainty. System 1 is a fast feed-forward control process, driven by the cerebellum and oriented toward immediate action; it is experienced passively, outside conscious awareness (one is seized by one's emotions). In contrast, System 2 is a slow feedback control process, driven by the cerebrum and oriented toward future action; it is experienced actively and consciously (one intentionally follows the rules of inductive and deductive reasoning). There is a huge difference in processing speed between the two systems; rational processing typically takes minutes to hours, whereas experiential processing typically extends from hundreds of milliseconds to tens of seconds (Newell, 1990). A large part of human beings' daily activities are immediate actions and are therefore under the control of System 1. System 2 intervenes with System 1 to better organize the overall outcome of the processing through consciously envisioning possible futures.

Meme that Mediates Individuals and Society: Moment-by-moment decision-making is carried out by utilizing knowledge that is activated from long-term memory in response to recognized objects that exist in the external world. A meme is an entity that represents the information associated with the object that a person can recognize. Therefore, an active meme plays a critical role in the decision-making process. The term "meme," originally coined by Dawkins (1976), was conceptual and was not defined clearly. However, a meme can be defined more clearly by assuming that the meme itself is structured in accord with the structure of living organisms, which is characterized by a non-linear, multilayered information structure.

The structured meme consists of the following three non-linear layers:

  • Action-level memes that represent bodily actions.
  • Behavior-level memes that represent behaviors in the environment.
  • Culture-level memes that represent culture.
Memes as a whole are a collection of information objects that reside in each layer. Each person develops his or her own relationships among objects.

Multiplicity of Behavioral Goals: Morris (2006) defined seventeen happiness goals. It is assumed that an individual pursues one of the seventeen goals at every moment, and switches to another when appropriate, by evaluating the current circumstances. CCE must identify the current goal and clarify the goal-enabling conditions.

An individual feels satisfaction when a goal is accomplished. The amount of satisfaction is influenced by the factors that characterize the shape of the trajectory of behavioral outcomes. Six critical factors make people feel satisfaction:

  1. Change: Perceptual functions work by sensing dynamic changes. Therefore, responses while the system is stable are limited. A condition for experiencing satisfactory feeling is "change."
  2. Succession of good results: Successive happiness tends to create memory traces for the best experience and the final outcome of the overall estimation of the events that have led to successive good results.
  3. Direction of absolute outcome (denoted as 2 in Fig. 1): A change in a good direction at the end of a series of events tends to create a memory trace of satisfactory feeling.
  4. Amplitude of success (denoted as 1 in Fig. 1): The greater the difference between the highest event and the lowest event in terms of strength of satisfactory feeling, the stronger the strength of memory trace for all the events, including the highest and the lowest.
  5. Absolute amount of outcome (denoted as 3 in Fig. 1) and direction of absolute outcome (denoted as 2 in Fig. 1): When the absolute outcome is acceptable and the contents in working memory at the time of the final event are good, they jointly affect the result of estimation of all the events.
  6. Bad results are not memorized: An individual strongly reacts to an event when the degree of badness of that event exceeds a certain threshold value.

MSA-fig2

Figure 1. Critical Factors that Make People Feel Satisfaction.



Usage of Memory under Strong Interaction between Environment and Behavior: Memory processes play a crucial role in the decision-making process and its result (i.e., the behavior the person ultimately selects and carries out). As Newell (1990) described in his seminal book, Unified Theories of Cognition, human beings operate differently, depending on the characteristic times of their environment (Fig. 2).

In parallel with Newell (1990), we suggest that, when real time constraints are strong, slow memory processes, which use long-term memory, do not participate in the whole processing. In other words, only the unconscious side of the Two Minds (System 1) works. In contrast, when few real time constraints exist, System 1 and System 2 work collaboratively in some cases and independently in others. Memory processes stay in the back of meme activation; therefore, when a person wants to envision active memes at the specific time of the event, he or she must take into account the plausible memory processes that operated, given the time constraint posed on the participant at that time.


Newell-time-scale-original

Figure 2. Newell's Time Scale of Human Action.






CCE-fig

Figure 3. Relationship of CCE study, ethnography, and cognitive science modeling.





References


  1. Dawkins, R. (1976) The Selfish Gene, Oxford University Press, New York City.
  2. Evans, J.S.B.T. and Frankish, K. (2009) In Two Minds: Dual Processes and Beyond, Oxford University Press, Oxford.
  3. Kahneman, D. (2003) A perspective on judgment and choice, American Psychologist, 58 (9), 697-720.
  4. Kitajima, M. and Toyota, M. (2012) Simulating navigation behaviour based on the architecture model Model Human Processor with Real-Time Constraints (MHP/RT), Behaviour & Information Technology, 31(1), 41-58. http://dx.doi.org/10.1080/0144929X.2011.602427
  5. Laird, J.E., Newell, A. and Rosenbloom, P.S. (1987) Soar: An architecture for general intelligence, Artificial Intelligence, 33, 1-64.
  6. Morris, D. (2006) The nature of happiness, Little Books Ltd., London.
  7. Newell, A. (1990) Unified Theories of Cognition (The William James Lectures, 1987), Harvard University Press, Cambridge, MA.
  8. Newell, A. and Simon, H. A. (1963) GPS, a program that simulates human thought. In Computers and Thought, (Eds) E.A. Feigenbaum and J. Feldman, McGraw-Hill, New York, 279-296.
  9. Newell, A. and Simon, H.A. (1972) Human Problem Solving, Prentice-Hall, Englewood Cliffs, NJ.
  10. Simon, H.A. (1956) Rational choice and the structure of the environment, Psychological Review, 63, 129-138.
  11. Simon, H.A. (1996) The Sciences of the Artificial, 3rd edition, The MIT Press, Cambridge, MA.
  12. Smith, M.S. and Vela. E. (2001) Environmental context-dependent memory: a review and meta-analysis, Psychonomic Bulletin & Review, 8, 203-220.


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CCE Study 1: Navigation at Train Stations

This section describes a case study that adopted the CCE methodology in order to investigate how elderly people use guide signs at train stations when they have to transfer lines, in addition to using such facilities as restrooms, lockers, elevators, and telephones. This study was sponsored by a train company in Japan; its purpose was to gain insight in order to improve the usability of guide signs at train stations for elderly passengers (see Fig. 3 for an example signboard). A brief report concerning this study was published by Kitajima et al. (2005) and by Kitajima et al. (2008) in Japanese.

Steps 1 and 2 of CCE: Defining the study field and critical parameters


The study field was a train station. The target activity was to navigate the train station on foot by using signs without asking for help from others for directions. Elderly people's navigation behaviour was to be investigated. The study question was "what would such-and-such elderly people do to carry out navigation missions at train stations by using sign boards?"

Navigating the station smoothly requires not only physical action but also cognitive and behavioral abilities, including the following activities: 1) determine a target appropriate to the purpose, 2) search for the target, 3) reach the target, and 4) achieve the mission. It was assumed that the following four cognitive abilities are necessary for elderly people to accomplish navigation missions at train stations: attention, working memory, and planning, which are known to decrease independently with age; and experience in using the train station. These constitute the critical parameters.

> Attention, Working Memory, and Planning


Attention is the ability to distinguish information pertinent to the task at hand from extraneous noises. Although the ability to separate target information from external noises plays an important role in daily behaviour, aging makes it difficult to ignore such unrelated information.

Working memory refers to a psychological system that both stores information briefly and allows manipulation and use of the stored information. This function is the basis of complex cognitive activities performed by a person. However, working memory can hold only a limited amount of information at one time. Due to this limitation, a person with an impaired working memory function is likely to lose the original goal and necessary information for a given action.

Planning is the prioritization and sequential implementation of the steps necessary to achieve a goal. It consists of repetitive cycles of appropriately setting a lower-level goal required to achieve the current goal; maintaining the lower-level goal until it is achieved; and, when that goal has been achieved, setting the next new lower-level goal.

Step 3 of CCE: Monitor Recruiting


The critical parameters for the CCE study were the cognitive functions, attention, working memory, and planning, and the experience of using the train stations where the study was conducted. Each of the four critical parameters has values, normal or weak (presence or absence in the case of experience), and the parameter spaces to explore were defined by their combinations. We were interested in studying how individual parameters affect navigation behaviour. Thus, we took the lesion approach, comparing the behaviour of participants who had a "weak" value for one parameter and a "normal" value for the other three parameters with that of participants who had no "weak" values. It was straightforward to estimate the presence/absence of experience. The following method was used to estimate normal/weak values for the three cognitive functions.

> Investigation of Cognitive Aging Characteristics


To investigate cognitive aging characteristics, we designed a cognitive function study using the cognitive aging study (Suto and Kumada, 2010) as the base, modified the contents of the study according to the contents of the current study. Table 1 indicates the study items for examining characteristics of cognitive functions.



Table 1. Study Items for Cognitive Functions.


Cognitive Function Study Item
Attention - Search for target images
- Select correct shape/figure with designated feature
Working Memory - Write mirrored characters
- Write words in reverse
Planning - Recall and write a sequence of daily actions



We conducted two studies under different monitor selection conditions. Participants in the first study were 168 elderly people registered with the Silver Human Resource Centre located in the Tokyo metropolitan area. The second study included 154 elderly people. Table 2 presents the results.



Table 2. Results of the Cognitive Aging Survey.


Ability in Cognitive Functions %
First Study
Normal ability in all functions 4.7
Weak in only one of the functions 40.4
Weak attention (only) 8.3
Weak working memory (only) 8.9
Weak planning (only) 23.2
Second Study
Normal in only one of the functions 17.6
Normal attention (only) 6.5
Normal working memory (only) 7.1
Normal planning (only) 4.0



Steps 4 and 5 of CCE: Behaviour observation and interviews at train stations


To identify the cognitive and behavioral processes of elderly people's navigation through a train station, we conducted observational studies of actual behaviour at JR East stations in the Tokyo metropolitan area.

Two field observational studies were conducted. In the first study, based on scores on pa-per-based cognitive ability assessments, four groups were defined: one with no problem, and the other three with one weak cognitive function. No group had experience in using the train stations where the observations were conducted within the past 10 years. Three participants from each group performed tasks, such as transferring from line A to line B and using facilities at one of three stations (Akihabara, Ohmiya, and Sugamo). In the second observational study, a total of 154 elderly participants took the paper tests; and three groups, each of which had one normal cognitive function, were defined. Three from each group with different use experience performed tasks at two stations (Tokyo and Shibuya).

> Train Stations, Tasks, and Participants


For the first study, we selected three stations that have different structures. This was done for the purpose of discovering factors affecting behaviour that are independent of the structure of the station and are peculiar to the cognitive function characteristics of each participant, with a focus on planning, attention, and working memory. In Table 3, we describe briefly the features of the selected train stations and the tasks at each station. We selected 12 participants, three participants from each of four groups: one group with normal ability in all functions and three groups with weak ability in one of the cognitive functions. Four participants with different cognitive aging characteristics performed the task at each of the three stations.

For the second study, we focused on the effect of the presence or absence of experience with using the train stations at the study sites on the participants' navigation behaviour. From the first study, we expected to understand the role of one cognitive function by comparing the navigation behaviour of normal participants with that of participants with one cognitive function deficit. The participants had no experience in using the study stations for at least 10 years prior to the study dates. In the second study, we selected two train stations, Tokyo and Shibuya in the Tokyo metropolitan area, and selected for each station three participants who had only one normal cognitive function. One of these participants had recently used the Tokyo station but not the Shibuya station, one had recently used the Shibuya station but had not used the Tokyo station, and one had never used either station. Therefore, we selected a total of nine participants. The tasks involved just reaching designated destinations. Since we were interested in the effect of experience and related mental models of the structure of the station, we set the task route to be longer and wider than the ones for the first study, which focused more on navigation by following signboards.



Table 3. Brief Description of the Features of the Selected Train Stations and the Assigned Tasks.


Station Feature Main Task Subtasks
Akihabara Station Platforms on two stories cross each other Change trains by moving from the No. 1 or No. 2 platform for the Yamanote / Keihin-Tohoku Line to the No. 5 platform for the Sobu Line for Shinjuku - Use the toilet
- Use a telephone
Sugamo Station Simple structure with an island-type platform 1) Move from the platform for the Togenuki Jizo and 2) Move from the arcade to the Sugamo Station and Take a train for Mejiro - Use the toilet
- Buy a ticket
- Use a coin locker (deposit and retrieve)
- Use an elevator
Ohmiya Station Has four stories for the Shinkansen, concourse, and conventional lines accompanied by a wide space Move from the east entrance to the platform for the Saikyo line and Take a train for Ikebuturo - Use the toilet
- Buy a ticket
- Use a coin locker (deposit and retrieve)



> Method


The task was explained to each participant, whose behaviour was recorded using a small wireless pinhole CMOS camera attached to the participant's hat, a wireless microphone, and a whole-back-view CCD camera (Fig. 4, left and centre). Immediately after each task, the participants were taken into a room and interviewed for their background knowledge and explanation of their behaviour while reviewing the recorded videos (Fig. 4, right).

The tasks involved searching for the place to perform the tasks. We were interested in representing the participants' behaviour in terms of state transitions in the problem space. Therefore, by comprehensively considering the video records and the results of the interviews, we divided a series of actions into segments, each consisting of a searching action, and further described them in detail using the following five items:

  • Goal,
  • Movement and behaviour observed,
  • Motivation and the object of searching,
  • Guide boards and signs referred to, and
  • Purpose of reference (i.e., collection of information or confirmation).


Field Study at the Train Stations

Figure 3. Field Study at the Train Stations; Left - participant performing a task at the Sugamo Station. Centre - the equipment. Right - interview after task.



Step 6 of CCE: Model construction


The result was then examined from the viewpoint of the cognitive characteristics of each participant. Table 4 summarizes the results of the two studies; it is an English translation of Table 4 in Kitajima et al. (2008) in Japanese.

The results essentially indicated the following, which can be regarded as preliminary models:

  • Persons with an weak planning function but with a normal attention function did not use the guide signs when they had a mental model; however, they did not gather task-relevant information but instead gathered irrelevant information when they had no mental model because of the lack of definite task goals, causing them to get lost.
  • Persons with a weak planning function and a weak attention consistently had difficulty gathering task-relevant information by using guide signs because of the vague description of behavioral goals.



Table 4. Relationships between Behaviours at Train Stations and Cognitive Functions.


P+ (normal planning function) P- (weak planning function)
A+ (normal attention function)
1st Study: Normal Group (P++, A++, WM++) 2nd Study: P−WM− Group (P−, A+, WM−)
1. Set goals flexibly according to the current situation; Acquire and confirm information necessary for accomplishing a task. 1. Confident about acquiring information at familiar places. Cling to an idea due to overconfidence.
2. Retain information for future use. Estimate task completion time beforehand. 2. Attend to appropriate objects when a mental model for the situation is available. Attend to inappropriate objects or no objects when no mental model for the situation is available.
3. Navigate with confidence when a mental model for the situation is available. Pay attention to signboards for confirmation.
4. Acquire information that is not useful for navigation when no mental model for the situation is available. Endeavor to understand the current space.
5. Strongly influenced by an idea. Difficult to acquire appropriate information at unfamiliar places. Influenced by unnecessary information and/or inappropriate interpretation of acquired information.
5. 6. Efficiency of information acquisition depends largely on the existence of a mental model for the current situation.
1st Study: WM− Group (P+, A+, WM−) 1st Study: P− Group (P−, A+, WM+)
1. Exhibit navigation behaviour similar to that of the normal group. 1. Rarely uses signboards.
2. Influenced more by past experience and mental model than the normal group. Forgets part of the tasks occasionally. Sets goals less flexibly according to the current situation than the normal group. 2. Acquires information narrowly. Clings to an idea; Does not confirm the status appropriately. Does not change behaviour flexibly.
3. Does not acquire concrete information even when looking at signboards due to underspecification of behavioral goal.
4. Does not acquire concrete information even when behavioral goal is appropriately specified, due to inability to select appropriate information.
5. Unable to utilize mental models concerning the structure of the station and/or past experience.
A- (weak attention function)
2nd Study: A−WM− Group (P+, A−, WM−) 2nd Study: A−P− Group (P−, A−, WM+)
1. Able to behave strategically by setting subgoals even without mental models. 1. Tends to wander around, due to inability to select the appropriate information source.
2. No problem in acquiring information from the environment, reading maps, and understanding the information on the signboards. 2. Pays attention to a salient object. Acquires information coarsely.
3. Able to pay attention to multiple sources of information. Able to use appropriate information in a timely manner. 3. Has difficulty understanding 3-D space. Has difficulty reading maps. Takes the wrong route.
4. Able to correct behaviour early even when necessary information has been overlooked, by acquiring alternative information. 4. Acquires fragmentary information. Has difficulty integrating information sources (e.g., an arrow and the name of a place) to make sense.
5. Sets a concrete goal when the target is close. Tends to become lost if the concrete goal is wrong. Able to backtrack and switch to an alternative goal if appropriately triggered even when the selected goal is not the correct one. 5. Difficult to activate a mental model that is useful to select an information source.
6. Tends to become lost because he/she clings to an idea and tries to search for information, based on an inappropriate idea.
1st Study: A− Group (P+, A−, WM+)
1. Tends to search for the target itself and/or the label attached to the target, not search for a complicated signboard.
2. Has difficulty acquiring information in parallel. Tends to acquire and confirm information frequently

Notes: P, A, and WM denote Planning, Attention, and Working Memory, respectively. The ranges of average scores of respective cognitive functions are represented by "++"; score ≥ 75%, "+"; 75% > score ≥ 25%, and "-" 25% > score ≥ 0%.

Discussion


One distinctive feature of CCE is its participant sampling process. It does not use a random sampling process but a purposive sampling process. In order to do this, it is necessary to define a parameter space in which the participants to be recruited will be uniformly distributed. In the case of train station study shown in this paper, the parameter space was defined by the following four dimensions; attention, working memory, planning, and experience. In the first study, the percentage of participants with normal ability in all functions was 4.7%. This indicates that if a random sampling process had been employed, the performance of participants in this group would not have been adequately represented because of its small occurrence rate. CCE is not concerned with the average behaviour of people in the study field but the characteristic behavioral features of pre-defined specific segments in the study field.

In the train station study, CCE was successful because it was able to identify the behavioral characteristics of elderly participants. Most importantly, it suggested the limitation of the concept of universal signage: Although the conventional guideline for the elderly is based on the presumption that elderly people will look at signs, the results suggested that such a sup-position is not always true. This finding gives us an important clue to solving usability problems at train stations. For the weak-attention group, for example, it may be useful to provide appropriate symbolic images. For the weak-planning group, however, individual guides may be necessary.

CCE uses behavioral records of participants in retrospective interviews. In the train station study, the behavioral records included video-image of a small CMOS-CCD camera mounted on a participant's hat, video-image recorded by a whole-back-view camera, and voice re-corded by a wireless microphone. The recoded data were used in the interview sessions that were scheduled just after the behavioral data recordings at the sites of the study. It turned out that the recorded behavioral data were extremely effective for the participants to report not only then-active contents in their working memory but also the episodes that were related to the activated contents which were stored in their long-term memory. This is consistent with the nature of memory, i.e., context-dependent memory (Smith and Vela, 2001).

The primary feature of CCE is that it enables comprehensive analyses of human beings' daily activities by integrating the outcomes of different research fields: meme in the field of evolutionary biology (Dawkins, 1976), multiplicity of goals in the field of cultural anthropology (Morris, 2006), cognitive bands in the field of cognitive science (Newell, 1990), and Two Minds in the field of behavioral economics (Kahneman, 2003).

However, a CCE study does not automatically produce useful and significant results. The critical part of a CCE study is the identification of critical parameters and a field study design that is sensitive to the critical parameters, allowing the diversity of participants' behaviour to be explained in terms of the space of the critical parameters. In the case study at train stations, the field study was carefully designed; the participants had to rely on their own cognitive resources to make decisions. Therefore, their meme activation process depended solely on their cognitive resources (planning, attention, and working memory), or critical parameters. Some of their activity was automatic (System 1), and the rest was deliberate (System 2). The characteristic times significantly differ between System 1 and System 2. We could easily identify which activity belonged to the result of which system. With this design of the CCE study, the participants' behaviour was understood in terms of the critical parameters.



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CCE Study 2: Watching Professional Baseball Games at Stadium

This section describes a case study of CCE. The field of study was the ballpark of a Japanese professional baseball team, the Hokkaido Nippon-Ham Fighters. This study focused on the repeat visiting behavior of loyal fans of the Fighters. The specific study questions were: "Why do loyal fans repetitively visit Sapporo Dome to watch professional baseball games?" and "How have they evolved to their current status of loyal fans?"

Steps 1 and 2 of CCE: Defining the study field and critical parameters


> Study field: Hokkaido Nippon-Ham Fighters


The Hokkaido Nippon-Ham Fighters is a professional baseball team in Japan's Pacific League. The team takes its name from the major shareholding company, Nippon Ham, which is the corporate name of Nippon Meat Packers, Inc. In 2004 the Fighters moved from Tokyo to Sapporo, the largest city on the island of Hokkaido. The team uses Sapporo Dome, a stadium located in Toyohira-ku, Sapporo, Hokkaido, Japan, that is primarily used for football and baseball. It is the home field of the football club Consadole Sapporo and the baseball team Hokkaido Nippon-Ham Fighters. Sapporo Dome opened in 2001 and currently has 42,126 seats. This stadium hosted three games during the 2002 FIFA World Cup.

During the five years since the Fighters moved to Sapporo, its number of fans has increased dramatically. There were 38,776 fans registered with the official fan club in 2004, 41,817 in 2005, 41,193 in 2006, 60,216 in 2007, and 74,974 in 2008 (as of September 30 of each year). It is easy to enumerate plausible reasons behind the continuous increase in the number of fans. First is the so-called Shinjo effect. Outfielder Tsuyoshi Shinjo joined the Fighters in 2004, after his three-year career with Major League Baseball teams the New York Mets and the San Francisco Giants. The phenomenon known as the Shingo effect was created with his outstanding talent in making professional baseball an entertaining show. Second, the Fighters won the Pacific League championship in the 2006 and 2007 regular seasons. Third is the contribution of manager Hilman. Finally, we can list the efforts of the players and the front-office staff who visited various places, including local schools, in an effort to establish intimate relationships with local communities.

However, nobody knows exactly why the Fighters have achieved such great success. This CCE study aimed at abswering this question

> Structures of fans and features


Loyal fans (repeaters) of a professional baseball team have their own individual histories in arriving at their current fan stage. As shown in Figure 4, they started in a pre-fan stage, passed through the fan stage, and ultimately reached their current loyal-fan stage. In the pre-fan stage, fans know little about the team, or at most they pay a certain amount of attention to the team and/or have some interest in the team. However, their attitude toward the team is passive, and they exert no aggressive action. Starting from this pre-fan stage, they advance to the fan stage, when they aggressively desire to have a relationship with the team. For example, fan-stage individuals display emotion towards the results of the games, and start to become interested in watching live games at the stadium. However, they do not have much interest in information about the team. A fan-stage person advances to a loyal fan by breaking through these passive characteristics. Loyal-stage fans aggressively collect information about the team, go to the stadium to watch live games when time allows, or even arrange their activities so as to give top priority to watching live games at the stadium.


Evolution of fan loyalty

Figure 4. Evolution of fan loyalty.



Step 3 of CCE: Monitor Recruiting


We conducted a Web survey and recruited nine highly loyal fans (elite monitors) from the Fighters' fan club members who had different attitudes towards professional baseball, cheering, and merchandising, and had visited Sapporo Dome several times since the Fighters moved to Sapporo. The nine selected fans were supposed to represent different "fan styles" and had different histories in reaching their current fan status (i.e., loyalty status).

Steps 4 of CCE: Behaviour observation


We had the elite monitors visit Sapporo Dome three times to watch designated Fighters-hosted games. We recorded their viewing behavior using a DVD camera recorder located three rows in front of the monitors' seats to capture their game-viewing behavior, installing a small ear-mounted CCD camera to record the scene they were viewing, recording their vocalizations with a pin microphone, and using an electrocardiograph and an accelerometer to capture their physiological responses to the events of the game (Figure 5). The designated games were a three-game series with the Softbank Hawks in July, a three-game series with the Orix Buffalos in August, and a three-game series with the Rakuten Golden Eagles in September. Each elite monitor was asked to attend all three series.


field-observation-at-stadium

Figure 5. Illustration of field observation. (a) an electrocardiograph and an accelerometer, (b) ear-mounted CCD camera, (c) the view of the ear-mount camera, and (d) three elite monitors in their seats watching a game.



Steps 5 of CCE: Interviews


We conducted structured interviews after each visit to Sapporo Dome, replaying the behavior records, the viewing-scene records, and the broadcasted TV video of the game for the characteristic events, including scoring scenes, field events between innings, and events for which the participants exhibited remarkable changes in physiological data (See Figure 6). Each participant was interviewed three times. The purpose of the first interview was to understand how the participants enjoy the game. The purpose of the second interview was to understand how participants developed their loyalty from the pre-fan stage several years ago, to the fan stage a few years ago, and then to the current repeating stage. The purpose of the third interview was to understand what triggered the state changes and what factors helped them retain each fan stage.


interview-baseball-fan

Figure 6. An interview session.



Step 6 of CCE: Model construction


We compiled the results of interviews in the form of a fan-loyalty evolution diagram (FLE diagram) as shown in Figure 7 that represented in detail how individual participants had evolved their loyalty by specifying triggers for stage changes, circumstances that made them stay at a particular stage, and activities in both the regular season and in the off-season. Nine FLE diagrams were created. We then collapsed them to derive mod-els of developmental processes of repeaters, which will be described in the next section.


fan-loyalty-diagram

Figure 7. Fan loyalty evolution diagram and characteristic episodes.



The following section describes results of analysis of the evidence collected during the interview ses-sions that focused on triggers that caused monitors to step up a stage (i.e., from pre-fan stage to fan stage, and from fan stage to loyal-fan stage), and the condi-tions that made or make them stay in a particular stage. These triggers and conditions define a rough qualitative model of the developmental process of fan loyalty.

> From the pre-fan stage to the fan stage


Progressing from the pre-fan stage to the fan stage. Three cases were found in the study:

  1. "Retirement of a star player" and "expectation of league championship." In the 2006 regular season, two events triggered three participants who had little knowledge about professional baseball and another three participants who had knowledge about professional baseball but did not have enough interest in it to progress to the fan stage. One event was an announcement by the then-star player, outfielder Tsuyoshi Shinjo, that he was retiring, relatively early in the regular season. This news was reported frequently in various media. The other event was that the Fighters were in the first championship race of the league and Japan's professional baseball leagues.
  2. "Watch the fans cheering." Two participants who had little knowledge about professional baseball and one participant who had little interest in professional baseball advanced to the fan stage after watching live cheering in the stadium.
  3. "Know the players and the team" and "unexpected talent of players outside baseball." Regardless of their knowledge level of professional baseball, knowing players and the team triggered participants to progress to the fan stage. Three participants who knew professional baseball reacted to the players' behavior outside baseball, causing them to advance to the fan stage.

> From the fan stage to the loyal-fan stage


Advancing from the fan stage to the loyal-fan stage. Ten cases were found in the study:

  1. "Watching live games at the stadium."
  2. "Knowing the rules of baseball and the team."
  3. "Watching games by oneself," "one's wife became a fan by following his lead," "communication with his/her friends at the stadium," or "meeting persons who visited the stadium." The common feature of these triggers is the establishment of an environment where fans could comfortably watch the games at the stadium with someone who contributed to building a relationship with them (e.g., spouse or friends).
  4. "Presence of players who always come to mind." Participants who had little knowledge about baseball or professional baseball, those who were fans of other professional baseball teams, and those who became fans at the end of the regular seasons tended to find opportunities that should provide information about players, teams, and the Fighters in particular. These participants were eager to attend off-season events such as talk shows and advanced to loyal fans in the next regular season.
  5. "Collecting the Fighters' goods."
  6. "Recording events of live games and/or collecting the recordings as proof of watching the games."
  7. "Expectation of the climax series and the Nippon series," and "eagerness to watch those series."
  8. "Communication with the other fans when watching live games."
  9. "Network community" that they accessed during live games to exchange information and post opinions.
  10. "Seeing the players closely", e.g., visiting camp in Okinawa, and those who had special interest (or who followed pro-baseball) said that their greatest interest was in seeing live action on a professional field.

> Developing from a pre-fan to a repeater


While they were in the pre-fan stage, the nine elite monitors were classified into three categories in terms of their interest in baseball or professional baseball. (a) Three elite monitors didn't have interest in baseball, (b) another three were interested in base-ball in general but did not have interest in profession-al baseball, and (c) the rest had interest in profession-al baseball but were not interested in purchasing tick-ets to visit Sapporo dome for watching Fighters' games.

Figure 8 illustrates the cases of the groups (a) and (c). The pre-fans who didn't know baseball well, (a), have developed into either repeaters who enjoy cheering or those who enjoy watching games. The pre-fans in the (c) category have developed into re-peaters who enjoy watching games.


fan-development-process

Figure 8. The development processes from the pre-fan stage to the repeater stage. Top - pre-fans who did not know baseball well. Bottom - pre-fans who had interest in baseball but not had strong interest in watching games at the stadium.



Conclusion


The case study revealed histories of nine elite monitors, which demonstrated how they moved through the fan stages, from the pre-fan stage to the fan stage and ultimately to the loyal-fan stage. We identified three features that motivated participants to advance from the fan stage, and ten features that motivated them to advance from the fan stage to the loyal-fan stage. These features should suggest possible paths that potential loyal fans follow and define possible their needs when they are at the pre-fan stage and those when they are at the fan stage in the future.



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