Universiti Teknologi MalaysiaInternational Business School

Doctoral Seminar in Digital Marketing

Student: Kevin Koo Seng Kiat

Presented: 6th December 2015

Study 1

● Russell K.H. Ching Pingsheng Tong Ja-Shen Chen Hung-Yen Chen, (2013),"Narrative online advertising: identification and its effects on attitude toward a product", Internet Research, Vol. 23 Iss 4 pp. 414 – 438

● H1.Advertisement interactivity positively affects a consumer’s attitude toward a product.

● H2.Advertisement vividness positively affects a consumer’s attitude toward a product.

● H3.Advertisement entertainment positively affects a consumer’s attitude toward a product.

● H4.Self-referencing positively affects consumers’ attitudes toward a product.

● H5a.High advertisement involvement enhances the positive relationship between interactivity and attitude toward a product.

● H5b.High advertisement involvement enhances the positive relationship between vividness and attitude toward a product.

● H5c.High advertisement involvement enhances the positive relationship between entertainment and attitude toward a product.

● H5d.High advertisement involvement enhances the positive relationship between self-referencing and attitude toward a product.

Methodology

A survey instrument was developed with measures adapted from previous studies. Minor modifications were made. 7 point Likert scale was used. Pilot study was carried out.Adjustmenta were made to instrument. Exploratory factor analysis and Cronbach alpha examined. 2 items deleted.

In the data collection phase, data was collected online. Questionnaire was partially completed. A video was shown. Remainder of questionnaire was completed.

SEM used to test hypotheses.

Findings

● H1 to H4 supported.

● H5a, H5b, and H5c Not supported.

● H5d supported: Advertisement involvement enhances the effect of self-referencing on attitudes toward a product.

Study 2

● Hsin Hsin Chang Hamid Rizal Hanudin Amin, (2013),"The determinants of consumer behavior towards email advertisement", Internet Research, Vol. 23 Iss 3 pp. 316 – 337

● H1.E-mail that offers high-quality information negatively influences perceived intrusiveness.

● H2.E-mail that offers entertainment value negatively influences perceived intrusiveness.

● H3.E-mail that offers financial rewards negatively influences perceived intrusiveness.

● H4.Perceived intrusiveness negatively influences attitudes toward e-mail advertising.

● H5.Perceived intrusiveness mediates between advertising values and attitudes toward e-mail advertising.

● H6.Attitudes toward e-mail advertising positively influence intentions toward the sender.

● H7.Attitudes toward e-mail advertising positively influence consumer response.

● H8.Intentions toward the sender significantly influence consumer response.

● H9.There is a significant different between permission-based e-mail and spamming e-mail in e-mail advertising.

Methodology and Findings

● 7 constructs were examined from the literature. 28 items reworded to fit the study. 2 scenarios were developed to differentiate between permission based emails and spamming. Respondents shown the 2 scenarios before answering the surveys.

● 400 questionnaires distributed, 221 returned. Confirmatory factor analysis was used to purify the measurement scale. Goodness of fit also tested.

● H1 to H4 and H6 to H9 were supported.

● Using t-test, respondents were shown to perceive greater intrusiveness in spamming than in permission-based email.

Study 3

● Katherine Taken Smith, (2012),"Longitudinal study of digital marketing strategies targeting Millennials", Journal of Consumer Marketing, Vol. 29 Iss 2 pp. 86 – 92

● RQ1: What forms of online advertising do Millennials prefer?

● RQ2: Which web site features grab the attention of Millennials?

● RQ3: How can marketers prompt Millennials to repeatedly visit a web site?

● RQ4: What motivates Millennials to write online reviews?

● Methodology: Millenials at a prominent southwest US university were studied for 3 years.

Hypotheses

● H1. Millennials will increasingly prefer coupons as a mode of online advertising.

● H2. Personalization will be the most successful web site feature for grabbing the attention of Millennials.

● H3. Competitive pricing will be a strong incentive for Millennials to repeatedly visit a web site.

● H4. Millennials are motivated to write online reviews if there is a personal benefit involved.

Findings● H1 supported, percentage of respondents selecting coupons

increased every year. Side panel ads remained steady. Email marketing preference increased. Game ad preference decreased. Pop up ads preference remained low.

● H2 is not supported. Personalization not important to Millennials. Graphics are most important to Millenials. Millenials also prefer simple professional layout, interactive site, and bright colours.

● H3 is not supported. Competitive pricing did not attract Millennials for repeat visits but good shipping rates and coupons do.

● H4 is supported. Millenials are highly motivated to write online reviews if there is personal benefit for them. During the 3 years, millennials were also found to be vocal about their opinion through social media.

Study 4

● Hean Tat Keh Wenbo Ji Xia Wang Joseph A. Sy-Changco Ramendra Singh , (2015),"Online movie ratings: a cross-cultural, emerging Asian markets perspective", International Marketing Review, Vol. 32 Iss 3/4 pp. 366 – 388

● RO1: to examine the influence of volume and valence of online movie ratings on consumers’ risk perceptions and purchase intentions

● RO2: to examine the moderating impact of cultural values

Hypotheses - Volume

● H1a.Consumers’ perceived risk is lower when the volume of online ratings is large (vs small).

● H1b.Consumers’ purchase intention is higher when the volume of online ratings is large (vs small)

● H2a.The impact of the volume of online ratings on consumers’ perceived risk is stronger for consumers with high (vs low) levels of conservation.

● H2b.The impact of the volume of online ratings on consumers’ purchase intention is stronger for consumers with high (vs low) levels of conservation.

● H3a.The impact of the volume of online ratings on consumers’ perceived risk is stronger for consumers with high (vs low) levels of self-transcendence.

● H3b.The impact of the volume of online ratings on consumers’ purchase intention is stronger for consumers with high (vs low) levels of self-transcendence

Hypotheses - Valence● H4a.Consumers’ perceived risk is lower when the valence of the average

online rating is positive (vs negative).

● H4b.Consumers’ purchase intention is higher when the valence of the average online rating is positive (vs negative).

● H5a.Large (vs small) volume amplifies the impacts of positive (negative) average rating and reduces (increases) perceived risk.

● H5b.Large (vs small) volume amplifies the impacts of positive (negative) average rating and increases (reduces) purchase intention.

● H6a.The valence of the average rating on consumers’ perceived risk is stronger for consumers with high (vs low) levels of conservation.

● H6b.The valence of the average rating on consumers’ purchase intention is stronger for consumers with high (vs low) levels of conservation.

● H7a.The valence of the average rating on consumers’ perceived risk is stronger for consumers with high (vs low) levels of self-transcendence.

● H7b.The valence of the average rating on consumers’ purchase intention is stronger for consumers with high (vs low) levels of self-transcendence.

Methodology & Findings● Two field studies conducted in four emerging Asian markets (China,

India, Chinese Macau, Philippines). Consumers were approached in shopping malls.

● First study tested H1-H3 while second study tested H4-H7.

● Questionnaire first developed in English and used in India and Philippines. Translated to Chinese and translated back to ensure semantic equivalence.

● Study 1 : 204 respondents, each compensated about USD4 in their national currency. Respondents asked to read online ratings of 2 fictitious new movies. Small volume review had 993 reviews, large volume review had 4997 reviews. Repeated ANOVA conducted on results.

● Volume and perceived risk: H1a and H2a supported. H3a not supported. Volume and purchase intention: H1b and H2b supported. H3b not supported.

Methodology & Findings● Indian respondents found to perceive more risk in low-volume

situations. Indian respondents' intention to purchase more affected by small volume situation. Indian respondents found to be more conservative than other markets. Indian respondents' age is older than other respondents but age was ruled out as factor.

● Study 2: 376 respondents, each also compensated about USD4 in their national currency. Similar procedure followed where respondents asked to read online reviews of two fictitious new movies. Valence represented by average rating of movie. Positive valence represented by 4.2 out of 5 points rating. Negative valence represented by 1.8 out of 5 points rating. Neutral valence represented by 3 out of 5 points rating.

● High and low volume of reviews maintained at 4,997 and 993 reviews repectively.

Methodology & Findings● Repeated ANOVA conducted.

● Effect of average rating on perceived risks: H4a supported. H5a partially supported (in high rating situation, even small volume of ratings can lower perceived risks). H6a and H7a not supported.

● Effect of average rating on purchase intention: H4b and H5b supported. H6b and H7b not supported.

● In all 4 markets, average rating, volume and perceived risk interacted significantly. In low average rating situation, Filipinos perceived lower risk when volume was low, suggesting Filipinos are less risk averse.

● In low-average rating situation, Indians and Filipinos had greater intention to purchase with low volume compared to large volume. In high-average rating situation, all 4 markets showed purchase intention was higher with large volume of reviews.

Study 5● Rodney Graeme Duffett , (2015),"Facebook advertising’s influence on

intention-to-purchase and purchase amongst Millennials", Internet Research, Vol. 25 Iss 4 pp. 498 – 526

● RO1: to determine whether advertising on Facebook has an influence on the behavioural attitudinal component of Millennials in an emerging country such as South Africa

● RQ1.Does Facebook advertising have an effect on intention-to-purchase among South African Millennials?

● RQ2.What impact does advertising on Facebook have on purchase amid Millennials in SA?

● RO2: to establish if usage factors, which include how Facebook is accessed (87 per cent of Facebook users in SA access FB via mobile phones; Wronski and Goldstruck, 2013), length of usage, log on duration, log on frequency and profile update incidence, have an influence on Millennials’ intention-to-purchase and purchase perceptions of advertising on Facebook.

● RQ3.What influence do South African Millennial usage variables have on intentionto-purchase owing to Facebook advertising?

● RQ4.Do usage characteristics of Millennials in SA have an impact on purchase as a result of Facebook advertising?

● RO3: to determine if demographic factors (gender, age and ethnic orientation) have an impact on Millennials’ intention-to-purchase and purchase perceptions of Facebook advertising

● RQ5.Do demographic factors have an effect on intention-to-purchase among South African Millennials owing to Facebook advertising?

● RQ6.What effect do demographic variables have on purchases that are attributable to advertising on Facebook amongst Millennials in SA?

Methodology● Self-administered questionnaires were distributed to young

employed individuals, students and young adults who were still seeking employment (more representative of Millenials). Respondents were from rural and urban areas in Western Cape, South Africa, representing 11% of the population. A multi-stage sampling technique was used.

● Questionnaires were administered by researchers on face-to-face basis. Respondents were screened to ensure they used Facebook and they had noticed advertisements on Facebook.

● Pre-test of questionnaire: 100 respondents. Pilot test: 100 more respondents. Usable questionnaires: 3,521 respondents, collected between April to June 2013.

● Results analysed by SPSS. ANOVA used Wald's X^2 and used Generalised Linear Model to establish significant differences between usage characteristics, demographic factors and behavioural attitude components.

Findings● 64.5% of respondents accessed FB on PC and mobile. More

than 60% logged on every day. They spent one to two hours per log on. More than 72% updated their profile once a week or more.

● Wald X^2 test revealed significant difference at p <0.001 for intention-to-purchase because of FB advertising.

● No significant differences were found for access, length of usage, log on frequency, gender and age, whereas Bonferroni correction pairwise comparisons of estimated marginal means disclosed the significant difference between the next variables.

Findings● Respondents who logged on less than 1 hour had lower

intention-to-purchase compared to those who had logged on for 2 hours.

● Respondents who update status every day had higher intention-to-purchase compared to those who update status once a week or less. Those who updated status 2-4 times a week had increased intention-to-purchase compared to those who updated 2-4 times a month or less.

● White respondents had less intention-to-purchase compared to black and coloured respondents.

Findings● Finding 1: Log on duration and profile update incidence show

the largest degree of influence on Facebook advertising intention-to-purchase and purchase.

● Finding 2: Access, length of usage and log on frequency had little effect on the behavioural attitudinal component.

● Finding 3: Ethnicity displayed the greatest amount of influence on Facebook advertising intention-to-purchase and had some effect on purchase, but not at a significant level.

● Finding 4: Gender had some impact on Facebook advertising purchase, but not at a significant level.

● Finding 5: Gender had little effect on intention-to-purchase.

● Finding 6: Age had no influence on Facebook advertising intention-to-purchase and purchase.

Study 6● Sue Vaux Halliday Alexandra Astafyeva , (2014),"Millennial

cultural consumers: co-creating value through brand communities", Arts Marketing: An International Journal, Vol. 4 Iss 1/2 pp. 119 – 135

● A conceptual paper about millennial cultural consumers (MCCs) based on consumer theory and branding theory. The paper also considers how to attract and retain younger audiences in arts organisations.

● Gen Y key motives in consuming include: intimacy/new relationships; awareness/self-actualization; balance in work-life or education-entertainment.

● There are common motives between brand communities of cultural organizations and friend groups: social interaction and belonging, entertainment and experience, self-development/self-actualization, and prestige.

Propositions● Online communities are relevant to the MCC's in development

of communities. A 2007 paper by Schouten et al about transcendent consumer experiences (TCE) has not been developed further. (Potential for further research)

● P1: For MCCs experience creates value; the experience is made up of emotions, feelings, memories, relationships and self-development.

● P1b.(Management implication) when designing cultural product (experience) for present-day youth audience cultural organisations’ managers should include in this product opportunities for self-development, as well as creation of emotions, feeling and memories.

● P2. MCCs will be more likely to participate in cultural organisations’ activities when they are actively recruited to engage in activity both online and offline.

Propositions● P2b.(Management implication) whilst MCCs will more easily

join a virtual brand community, this membership needs to be supplemented by real time personal contact and interaction.

● P3. MCCs’ desire for transcendent experience, their feeling of being special, their desire to contribute to the greater whole and other need can be met by much greater involvement in co-creation of arts experiences.

● P3b.(Management implication) when recruiting MCCs to engage in cultural organisations’ activity, marketing managers should consider and meet key MCCs’ attendance motives, such as: social interaction and feeling of belonging; entertainment and experience; self-development/self-actualization; and, finally, prestige.

Propositions● P4. The loss of control by organisations in the virtual world is

counter-balanced by MCCs exercising autonomous choice as to what art to consume, when to consume it and how frequently, as part of ongoing identification with arts as brands.

● P4b.(Management implication) noting loss of control in the virtual world, cultural organisations practitioners should develop a dialogue that can contribute to the MCCs’ need to continuously create identity and meaning via exercising their choice preferences.

We interrupt this broadcast...

“What gets measured, gets managed.” - Peter Drucker

What are tech start-ups in Silicon Valley measuring?

Introducing Pirate Metrics (AARRR)

Unfortunately...

Let's Learn Some More

● Startup Metrics for Pirates by @breadnbeyond (cartoon): https://youtu.be/VTeaAlinX9E

● Startup Metrics (AARRR) by Dave McClure (video): https://youtu.be/irjgfW0BIrw

● SlideShare Presentation by Dave McClure: http://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-nov-2015-platzi

● Edith Yeung's adaptation of AARRR to mobile apps (MO-AARR): http://www.slideshare.net/EdithYeung/startup-metrics-for-mobile-pirates-moaarrr

● Venture capitalists and angel investors pay attention to these metrics.

● Source: http://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-version/4-Example_Conversion_Metrics_note_not

Metrics Measured by Investors1.CAC (Customer Acquisition Cost): how much it costs you to get 1

customer

2.Retention Rate: percentage of people who use your product in month 1 and still use it in month 2 (etc.)

3. ARPU (Average Revenue Per User) & LTV (Life Time Value): The amount of money that a company earns for each of its customers over a given period of time.

4.Viral Coefficient: the organic growth of your company. (K-value)

5.Activation: Speed at which clients are becoming active, including events, in addition to various actions on the website. E.g. conversion of visitors to registered users / registered users to buyers / how long it takes users to purchase after registering etc.

6.Repetition rate: What percentage of your database uses your product again after making 1 purchase/reservation/whatever it may be.

7.Revenue: How much money your company is making.

Source: http://www.barcinno.com/7-metrics-for-raising-vc-money-in-record-time/

Other Metrics Measured by VC's1.Financial

a)Monthly Revenue Growth

b)Revenue Run Rate

c)Margins

d)Burn Rate and Runway

2.User Metricsa)K-Value (Virality)

b)Proportion of Mobile Traffic

c)Cohort Analysis and Churn

3.User Acquisition and Marketing Metricsa)Cost of Acquiring a Customer and

Payback

b)Net Promoter Score

4.Sales Metricsa)Magic Number

b)Basket Size and Order Velocity

c)Average Sales Cycle

d)Long Term Value

5.Market Metricsa)Total Addressable

Market

b)Average Wallet SizeSource: http://techcrunch.com/2014/01/31/the-complete-quantitative-guide-to-judging-your-startup/

Drip Email Campaigns

● Example of Drip Campaign: http://www.slideshare.net/simplycast/drip-marketing-slideshow-31405509

● Drip campaigns start when you opt-in into a newsletter or sign up for a waiting list (e.g. on a landing page).

Some important trends to take note of:

● Content marketing / content creation● SEO; search engine, and app-store● Woo-back campaigns● User Experience (UX) and User Interface (UI)● Podcasting

Metrics & Tech Startup Valuation● Problems of valuing startups identified by Prof. Aswath Damodaran

(http://people.stern.nyu.edu/adamodar/pdfiles/papers/younggrowth.pdf):– No history– Small or no revenues, operating losses– Dependent on private equity– Many don't survive– Multiple claims on equity– Investments are illiquid

● Traditional methods such as DCF (Discounted Cash Flow) and Asset Growth rely on historical data.

● Prof Aswath suggests starting by understanding:– Total market size and projected growth / evolution of market– Market share– Operating expenses / margins– Investments for Growth– Computing tax effects.

● Dark side of venture capitalist valuation of young companies:– Top line (revenues) and bottom line (earnings), no detail

– Focus on the short term, rather than the long term

– Mixing relative with intrinsic valuation

– Discount rate as the vehicle for all uncertainty

– Ad hoc and arbitrary adjustments for differences in equity claims

● Problems with VC valuation:– VC's push down earnings and revenues, giving them greater

equity.

– VC's do not calculate cash flows in depth and use multiples

– VC's tend to incorporate company failure into the discount rate

– VC's fail to recognise that money investment taken out cannot be computed as part of post-money value.

Some Questions

● Are tech companies pursuing and measuring the right metrics?

● Are tech companies blindly following the crowd?

● These are some of the questions I asked myself when I joined the courses at MaGIC.

Study 7• Bentley, R.A.; O'Brien, M.J.; Brock, W.A. (2014) “Mapping Collective

Behaviour in the Big-Data Era” Behavioural and Brain Sciences, Vol. 37, pp. 63-119

● Conceptual paper about the decision-making behaviour of crowds based on 2 factors: Transparency of information regarding decision payoff, and individual/social decision.

● Hypothesis: Big data may oversimplify the study of decision making, thus a new framework is proposed based on discrete-choice theory, describing decision making based on two axes: (1) an east–west dimension that represents the degree to which an agent makes a decision independently versus one that is socially influenced, and (2) a north–south dimension that represents the degree to which there is transparency in the payoffs and risks associated with the decisions agents make. Each quadrant represents a certain type of behaviour and movement from one quadrant to another are considered as behaviour.

Independent Variables Moderating Variables Dependent Variables

(1) Knowledge of decision impact(2) Confidence

Trial-and-Error (Experience) Independent Decision Making with Transparent Payoffs (DV1)

(1) Social learning(2) Recognition of benefits of decision

Independent learning Copying of Decisions of Majority or Those with Most Skill / Prestige (DV2)

(1) Strong social forces(2) Lack of choices

(1) Lack of Models to follow(2) Weak feedback loops(3) Confirmation bias(4) Individual learning

Copying of Other Models' Decisions(DV3)

(1) Individuals do not have knowledge of other models' decisions(2) Knowledge of decision payoff is lacking(3) Too many choices

Individualized decisions without knowledge of payoff (DV4)

Implications

DV1: The individuals will continue to apply such decisions until better decisions are found.

DV2: The individuals may miss out on better opportunities because they do not explore or test their assumptions.

DV3: In times when there is explosion of information e.g. Internet, this can lead to large scale copying without certain knowledge of outcome.

DV4: Since everybody is making their own decisions based on their own criteria, it is unlikely that any single decision will become popular.

- Large societies require individualized learning to form unique but correct decisions that will guide the rest of society.

- In large societies the existence of technologies will propagate best decisions so that many others will quickly copy.

- Data shows that as societies grow larger, the numbers of inventors increase at an increasing rate, suggesting that inventors benefit from additional information availability.

- Top Twitter users tend to remain on top and retain their influence for long periods of time, but the mean periods of popularity for the top 10 Twitter users and the top 1000 Twitter users are quite similar, thereby discounting the effect of celebrity bias.

- Because of their vast popularity, Twitter celebrities can act as evangelists and bridges for grassroot causes.

- Online social networks tend to gravitate towards the southwest, due to blind copying of crowd behaviour.

- Wealthy people tend to gravitate towards the northeast, due to copying of skillful behaviour.

Peer commentary 1● 1. “Big data” needs an analysis of decision processes by

Analytis, P.P. et al. ● a) Based on a simulation, it is shown that the proposed

conceptual framework is incomplete without taking into consideration people's decision processes.

● b) 1,000 agents were simulated who choose sequentially from a set of 100 items (e.g., cameras, wines) drawn from a multivariate normal distribution. The agents aim for the item with the highest possible quality. The agents cannot evaluate the quality of the item with certainty but have to infer it from three attributes.

● c) In the same environment, two decision processes can generate strikingly different collective behaviour.

● d) In environments that differ substantially in transparency, the same process can produce the same type of behaviour.

Peer commentary 2

● 2. “The map is not the territory” by Bookstein, F.L.● a) The conceptual map proposed by Bentley et al is flat

and is an oversimplification.● b) Bookstein suggests, as alternatives, tetrahedron with

four interconnected points; a globe with an axis; and a map consisting of four situations with a “neutral center”.

● c) Bookstein admits that none of the other topologies are more consistent with the authors data but contends that different topologies will generate different types of hypotheses.

● d) Bookstein feels that the choice of the flat “map” has limited the range of hypotheses that can be generated.

Peer commentary 3

● 3. Extending the global village: Emotional communication in the online age by Buck, R.

● a) The conceptual map neglects to include emotion as a factor in decision-making.

● b) Emotions can influence decision making positively, while in other situations it can disrupt decision making.

● c) The figure illustrates emotional versus rational influences of online communication media.

Peer commentary 4● 4. Mapping collective behavior–beware of looping by Christen, M.

and Brugger, P. ● a) Christen and Brugger observe that self-reflection affects the

actors behaviour, in a variant of the “looping effect”, in which the product of investigation influences the object of investigation.

● b) They suggest that this can be viewed as the “height” of the map. ● c) As social influence increases from West to East axis, “looping”

adds a component of knowledge, “because people make models (simple theories) based on themselves as well as on other people with respect to mechanisms driving their behaviors”.

● d) Even as people are affected by varying degrees of transparency, the element of self-reflection may help individual decision makers realize that their decision are not efficient, thus helping them to move from one quadrant to another more quickly.

● e) Self-reflection and knowledge from self-learning is a useful component that should be included in the proposed framework.

Peer Commentary 5● 5. Modesty can be constructive: Linking theory and evidence in

social science by Durlauf, S.N.● a) Bentley et al have overcome the traditional limitations faced by

economists and statisticians. ● b) Economists frequently make their theories but are unable to

exploit data mining to justify their theories. Whereas, statisticians use of statistics can create models of higher predictive power, but are often unknowing of the underlying theory.

● c) The framework proposed by Bentley et al show how behavioural models can be used to understand patterns found in large data sets.

● d) Even though the paper by Bentley et al does not contain any formal hypotheses, statistical calculations, etc the paper has been supported by strong economic theories to explain data patterns.

● e) Bentley et al may be considered to have constructed a vision of “big” social science for “big” data.

Peer commentary 6● 6. The crowd is self-aware by Fan, J.E. and Suchow, J.W.● a) Fan and Suchow propose that understanding the collective

dynamics of decision-making requires consideration of factors that guide movement across the map.

● b) They propose that self-awareness can lead a group to seek out new knowledge and re-position itself on the map.

● c) Political awareness can lead people to find gaps in each others' knowledge. Through public debates, emerging scientific literature and interaction between interested groups, outside information may be introduced into the decision making group. Technology may help to disseminate the information, thus pushing the group northwards.

● d) Self-awareness allows groups to seek new sources of information, adopt new modes of decision making, and generate new knowledge.

Peer commentary 7● 7. Adding network structure onto the map of collective

behavior by Fortunato, S.; Saramaki, J. and Onnela, J-P.● a) Fortunato et al propose an extension of Bentley et al's map

by incorporating an aspect of underlying network structure that captures modes of collective behaviour.

● b) The effect of network structure on outcome can be quite dramatic, for example an online service was more rapidly adopted when social networks were more highly clustered.

● c) For decision-making processes where social influence plays a role, Fortunato et al argue that the key feature is social group structure that limits the number of options available for social learning. Strong group structures with only a few connecting nodes will lead to situation where social influence originates from each group. The opposite may be group structures where everybody is fully connected.

d) Fortunato et al also argue that the North East and South East quadrants may be caused by the mediation of network dynamics on social influence, and not to the transparency of the decision pay off.

Peer commentary 8

● 8. Missing emotions: The z-axis of collective behaviour by Garcia, A.N.; Torralba, J.M.; Gonzalez, A.M.

● a) Garcia et al propose that emotions be integrated into Bentley et al's framework along a z-axis to register emotional depth and involvement.

● b) Emotions can explain isolationist behaviour as opposed to social behaviour.

● c) Their proposed addition is as follows:

Peer commentary 9● 9. Capturing the essence of decision making should not be oversimplified by

Godzinska, E.J. and Wrobel, A.● a) Criticized the oversimplification of decision-making committed by Bentley

et al for the sake of creating the framework. For example, they claim that:● i. distinctions between different strategies in decision making are not

examined in depth.● ii. Social linking has been equated with herdlike behaviour. ● iii. The role of social interactions is not examined in-depth.● b) Even though Bentley et al are proposing a continuous map, the layout of

the map seems to be a 2x2 quadrant of four distinct states. Additionally, the position of different types of behaviour are not identified.

● c) Bentley et al fail to recognise that transparency of information may influence individualized or social decision making.

● d) Godzinska and Wrobel recommend that Bentley et al include neurobiological processes to help explain better how the brain's processes may explain the behaviour of crowds. However, this is not likely to be feasible as Bentley et al's proposed framework is based on large crowds.

Peer commentary 10● 10. Conflicting Goals and their impact on games where payoffs

are more or less ambiguous by Hopfensitz, A.; Lorini, E.; and Moisan, F.

● a) Since Bentley et al have proposed that the East-West axis of their proposed framework may represent the linkage of individuals' to certain groups, Hopfensitz et al propose that it is representative of social ties.

● b) Since Bentley et al discuss their framework in context of friendship networks and language use, Hopfensitz et al propose that the framework be extended for decisions in games.

● c) Hopfensitz et al propose, when there are social ties between two persons, the first person will be motivated to help the group provide the second person is also motivated to help the group.

●

● d) Hopfensitz created a model to test the decision of a player to enter into a coordination game based on the strength of social ties. They proposed to students whether they would be keen to enter into coordination games with people from the same university compares to people from the same team. It was shown that people preferred to enter the coordination game when they would be participating with people from the same team (closer knit group).

● e) In discussing the southern quadrants, Hopfensitz et al believe that when payoffs are not precise (e.g. by giving only general information), coordination becomes “easier for socially tied individuals since it is clearer what the optimal outcome is for the group.”

● f) Hence, it is possible that the South East quadrant may be more efficient than the Northern quadrants when “players are strongly tied”.

Peer commentary 11● 11. It’s distributions all the way down!: Second order changes in

statistical distributions also occur by Keane, M.T. and Gerow, A.● a) They observe that many studies are about first order effects, i.e.

about changes in a single statistical distribution. Studies about second order effects are less common, i.e. studies about changes to distributions at population-levels. Most of these studies are about “wisdom of crowds” and “herd-like behaviour” but not how “wise crowd becomes a stupid crowd”. Bentley et al have proposed a framework that may explain this.

● b) Within second order effects, there can be divided into between-distribution and within-distribution effects. Between-distribution effects are about changes in a distribution from one time to another time, from one type of behaviour to another.

● c) Within-distribution effects are changes within the properties of a distribution from one period to another. Bentley et al's framework does not explain much about this type of effect. It is mostly focused on movement within the South East quadrant.

Peer Commentary 12● 12. Keeping conceptual boundaries distinct between

decision making and learning is necessary to understand social influence by Mens, G.L.

● a) Bentley et al base their Framework on four assumptions. Three are accepted by Mens. The third assumption, however, blurs “the distinction between learning and decision making”.

● b) Learning and decision making are proposed to drive social influence.

● c) If agents are motivated to reach the same alternative as others, and coordination to switch to a better alternative is problematic, learning does not matter. The driving force of social influence is fear of failure to coordinate.

d) On the other hand, if main social influence is social learning, due to lack of information on the best alternative, decisions will be made on basis of popularity. However, there may be large swings in popularities. Some contradictory information may also cause popularity increase to be disrupted.

● e) If social influence is spread through sampling, agents make decisions based on their own experiences. There will be low turnover among most popular alternatives.

● f) Thus, depending on the dominant social influence, a person seeking to influence the crowd may rely on certain means to achieve such ends.

● g) Today people can customize their sources of news, and even narrow the information they get from certain sources. This may lead to reduction of news diversity.

● Unfortunately due to time constraints I was unable to finish summarizing all the peer commentaries.

THANK YOU for your time.