Digitalization at Leuphana Universität | Flashcards & Summaries

Lernmaterialien für Digitalization an der Leuphana Universität

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Psychometric profile and targeting

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•test the effects of psychological persuasion on people’s actual behavior over 3.5 million individuals with psychologically tailored advertising
• matching the content of persuasive appeals to individuals’ psychological characteristics significantly altered their behavior as measured by clicks and purchases
• Persuasive appeals that were matched to people’s extraversion or openness-to-experience level resulted in up to 40% more clicks and up to 50% more purchases than their mismatching or unpersonalized counterparts
• the application of psychological targeting makes it possible to influence the behavior of large groups of people by tailoring persuasive appeals to the psychological needs of the target audiences

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Consequences of Digitalization

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1. jobs will change dramatically

  • Computerization (bottle-neck-variables according to Frey & Osborne): 
    • social intelligence, e.g. PR-manager won't lose his job, a dishwasher will
    • creativity, e.g. fashion designer will stay, court clerk will go
    • perception and manipulation, e.g. surgeon stays, telemarketer goes
  • Job profiles will be changed due to automation and digitalization
    • missing skills is one of the main gaps in digital transformation (77%)

2. cyber security has to be increased 

3. new regulations need to be put in place

4. ethical question: 

  • several factors should be taken into consideration
    • interest of general public, conflicting interests, balance of power, contribution to data generation, data right



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Why does the ECJ treat the original publication (in "La Vanguardia"'s website) different from the results of a search engine?

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just the link with his name has to be deleted, not the whole newspaper article, because it is a legal publication
• it is much harder to find, if google doesn’t show it
• Article 17 Right to erasure (“right to be forgotten”)
• the erasure of personal data, if they are no longer necessary
• this might be a compromise

• ECJ thinks that a google result is much worse than a simple publication on a website, but as soon as google find it withnin the search for a name it is much relevant for personal data protection

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Vial, 2019: Understanding digital transformation

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Defining DT

  • digital transformation (DT) has emerged as an important phenomenon in strategic information system (IS) research: 
    • Definition: DT encompasses the profound changes taking place in society and industries using digital technologies 
    • organizational level: argued, that firms must find ways to innovate with these technologies by devising "strategies that embrace the implications of digital transformation and drive better operational performance" 

Observations

  • DT primarily relates to organizations 
  • Important differences exist across definitions with regards to the types of technologies involved as wenn as the nature of the transformation taking place
  • In spite of the differences, similarities exist across definitions

Differences

Analysis reveals that circularity, unclear terminology, and the conflation and its impacts, among other challenges, hinder the conceptual clarity of DT

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Different levels of digital transformation

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  1. process level: improving existing processes by implementing digital technology
  2. Business Capability Level: implementing new processes and capabilities (but the business model stays the same) 
  3. Enterprise level: Transformation of business model
  4. Ecosystem/ Industry Level: transformation beyond the scope of the enterprise (mainly business/ platform ecosystems) 
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Problems/challenges with MLPA

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Reliability, validity and (a-)theoretical foundation
- content-free “scale development” → a-theoretical, e.g. Hell Kitty; younger age, high openness, low agreeableness/conscientiousness/emotional stability
- discriminant validity between Big 5 factors (shared indicators)
“Substantive”, content validity logically a challenge
- Data collected → then variables extracted (curly fries →intelligence)
- Hence → theoretically identify “logical” indicators
Algorithms a predictive “black box” → what do they actually measure?
Recommender systems → revealing pregnancy of an unmarried woman

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2. Job creation and destruction


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2.1 potential effects of automation


  • displacement of employees due to automation of jobs/task
  •  productivity effect: innovations increase firms‘ productivity, reduce costs and prices, demand increases, output increases; new/better products/services can be produced; the economy expands
    → labour demand increases–potentially also in sectors that do not adopt new technologies due to a multiplier effect
  • reinstatement effect: evolves either because new tasks are complementary to the new technologies or because the displacement effect increases the amount of labour that is available for performing new/more productive tasks→ more workers required to perform new tasks → labour demand increases
  • net effect: theoretically unclear → empirical question


2.2 Job creation and destruction on different levels


  • firm level: firms‘ technology investments did not reduce their net employment (displacement effects offset by technology induced firm-growth) in Germany
  • sector level: takes into account reallocation of workers between less and more innovative firms (additional use of robots between 1993 and 2007 raised labour
    productivity and value added, no effect on total hours worked in 17 OECD countries)
  • Regional level: net neutral effects of robots in German local labour markets between 1994 and 2014 (2.12 job losses in manufacturing per additional robot, compensated by rising service employment)
  • - small negative net effects of robots in US local labour markets between 1993 and 2007
  • - Productivity and reinstatement effects of robots apparently strong enough to compensat displacement effects in Germany, but somewhat weaker in the US (possible  employment protection and vocational training)
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Aspects & Drivers of Indutry 4.0

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Aspects of Industry 4.0
• Digital supply chain
• Communication network infrastructure
• Big data / data science
• Artificial intelligence & machine learning
• 3D printing (manufacturing)
• Robotics (automation / automated guided vehicles)
• Sensor Technology
• Augmented reality
• Digital twin = (simulation) models
• Cyber security

•  --> field of action morw dynamic, unpredictable & turbulent (processing speed and flucating demand for products)


Drivers
• Low priced sensors available
• CPU is available cheap and unlimited
• Data mining: Analyse big data close to real-time
• Performance advantages by decentralized networking
• Internet is available worldwide
• Worldwide GPS localization
• Increase in soft-/hardware usability
• Storage is available cheap and unlimited

•  globalization + international competition

•  shortened product lifecycle

•  high cost pressure


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First Generation of MLPA

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  • Text analysis, 167 Facebook users - correlate with Big Five, r =.16-.26; e.g., favorite book, friends
  • 50 twitter users, tweet length - correlate with Big Five, r =.24-.40
  • Smartphone use of 83-117 users (call / SMS length) - correlate with ten item Personality inventory (r =.11-.26) Text analysis, correlate with Big Five, r=.16-.26
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Automation, jobs & tasks

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automation doesn‘t eliminate all jobs
• tends to eliminate tedious and repetitive tasks
- manual: washing clothes, drying dishes, mowing lawn, digging holes
- cognitive: making change for purchase, memorizing maps, adding numbers
• only if you eliminate all the tasks associated with a particular job, you eliminate that job
• but: that is rare
• 270 detailed occupations listed in the 1950 US Census
• 1 of them has to been eliminated due to automation (elevator operator)


• most jobs are more complicated than we think
• O*NET data base contains a rich set of variables that describe work and worker characteristics, including skill requirements
• example of landscaping and groundskeeping workers
some of those tasks can be automated, but can all of them be automated = what fraction

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TESTE DEIN WISSEN

Development of the labour market (Overview)

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  • 1935: “Thinking Machine Replace the Thinker
  • same now: “Smart robot could soon steal your job”
  • there have always been strong changes in the Employment-to-population ratio (shows the proportion of a country's working-age population that is employed)

USA

  • shared increased in the last 70 years roughly from 56% to 65 % in the year 2000
  • first decline = 1980 dotcom bubble
  • second decline = 2008 in the financial crisis
  • increase to again 61 % in 2019

EU 

  • ratio was larger in 2017 than in 1992
  • also a decline in EU in 2008 for financial crisis

Germany

  • nowadays around 58% → more people in employment than ever in the past
  • even though there are more robots
  •  no decline within the last 30 years
  • negative trend on the German labor market in the late 1990s
  • but then strong positive trend
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Appinio

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• Appinio = the fastest market research solution worldwide
• Why founding a new market research solution:
1. The gut feeling
2. Linear development without customer involvement (leads to products or slogans which are misunderstood or not useful) → no market need is main reason for failure which is costly solution: being more customer centric with agile + iterative development + customer involvement 

products are more successful + profitable (involving testing + user feedback tofurther develop)

• but most options for being more customer focused are to slow or there is screening bias (you can get screened out so at some point so you lie to be part of the survey) → which is because of extrinsic motivation (also leads to speeding/bad free text)
• the goal is to have intrinsic motivation where appinio comes in
• features: quickie questions + ask own questions + gamification + compare opinions with others

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  • 13664 Karteikarten
  • 503 Studierende
  • 19 Lernmaterialien

Beispielhafte Karteikarten für deinen Digitalization Kurs an der Leuphana Universität - von Kommilitonen auf StudySmarter erstellt!

Q:

Psychometric profile and targeting

A:

•test the effects of psychological persuasion on people’s actual behavior over 3.5 million individuals with psychologically tailored advertising
• matching the content of persuasive appeals to individuals’ psychological characteristics significantly altered their behavior as measured by clicks and purchases
• Persuasive appeals that were matched to people’s extraversion or openness-to-experience level resulted in up to 40% more clicks and up to 50% more purchases than their mismatching or unpersonalized counterparts
• the application of psychological targeting makes it possible to influence the behavior of large groups of people by tailoring persuasive appeals to the psychological needs of the target audiences

Q:

Consequences of Digitalization

A:

1. jobs will change dramatically

  • Computerization (bottle-neck-variables according to Frey & Osborne): 
    • social intelligence, e.g. PR-manager won't lose his job, a dishwasher will
    • creativity, e.g. fashion designer will stay, court clerk will go
    • perception and manipulation, e.g. surgeon stays, telemarketer goes
  • Job profiles will be changed due to automation and digitalization
    • missing skills is one of the main gaps in digital transformation (77%)

2. cyber security has to be increased 

3. new regulations need to be put in place

4. ethical question: 

  • several factors should be taken into consideration
    • interest of general public, conflicting interests, balance of power, contribution to data generation, data right



Q:

Why does the ECJ treat the original publication (in "La Vanguardia"'s website) different from the results of a search engine?

A:

just the link with his name has to be deleted, not the whole newspaper article, because it is a legal publication
• it is much harder to find, if google doesn’t show it
• Article 17 Right to erasure (“right to be forgotten”)
• the erasure of personal data, if they are no longer necessary
• this might be a compromise

• ECJ thinks that a google result is much worse than a simple publication on a website, but as soon as google find it withnin the search for a name it is much relevant for personal data protection

Q:

Vial, 2019: Understanding digital transformation

A:

Defining DT

  • digital transformation (DT) has emerged as an important phenomenon in strategic information system (IS) research: 
    • Definition: DT encompasses the profound changes taking place in society and industries using digital technologies 
    • organizational level: argued, that firms must find ways to innovate with these technologies by devising "strategies that embrace the implications of digital transformation and drive better operational performance" 

Observations

  • DT primarily relates to organizations 
  • Important differences exist across definitions with regards to the types of technologies involved as wenn as the nature of the transformation taking place
  • In spite of the differences, similarities exist across definitions

Differences

Analysis reveals that circularity, unclear terminology, and the conflation and its impacts, among other challenges, hinder the conceptual clarity of DT

Q:

Different levels of digital transformation

A:
  1. process level: improving existing processes by implementing digital technology
  2. Business Capability Level: implementing new processes and capabilities (but the business model stays the same) 
  3. Enterprise level: Transformation of business model
  4. Ecosystem/ Industry Level: transformation beyond the scope of the enterprise (mainly business/ platform ecosystems) 
Mehr Karteikarten anzeigen
Q:

Problems/challenges with MLPA

A:

Reliability, validity and (a-)theoretical foundation
- content-free “scale development” → a-theoretical, e.g. Hell Kitty; younger age, high openness, low agreeableness/conscientiousness/emotional stability
- discriminant validity between Big 5 factors (shared indicators)
“Substantive”, content validity logically a challenge
- Data collected → then variables extracted (curly fries →intelligence)
- Hence → theoretically identify “logical” indicators
Algorithms a predictive “black box” → what do they actually measure?
Recommender systems → revealing pregnancy of an unmarried woman

Q:

2. Job creation and destruction


A:

2.1 potential effects of automation


  • displacement of employees due to automation of jobs/task
  •  productivity effect: innovations increase firms‘ productivity, reduce costs and prices, demand increases, output increases; new/better products/services can be produced; the economy expands
    → labour demand increases–potentially also in sectors that do not adopt new technologies due to a multiplier effect
  • reinstatement effect: evolves either because new tasks are complementary to the new technologies or because the displacement effect increases the amount of labour that is available for performing new/more productive tasks→ more workers required to perform new tasks → labour demand increases
  • net effect: theoretically unclear → empirical question


2.2 Job creation and destruction on different levels


  • firm level: firms‘ technology investments did not reduce their net employment (displacement effects offset by technology induced firm-growth) in Germany
  • sector level: takes into account reallocation of workers between less and more innovative firms (additional use of robots between 1993 and 2007 raised labour
    productivity and value added, no effect on total hours worked in 17 OECD countries)
  • Regional level: net neutral effects of robots in German local labour markets between 1994 and 2014 (2.12 job losses in manufacturing per additional robot, compensated by rising service employment)
  • - small negative net effects of robots in US local labour markets between 1993 and 2007
  • - Productivity and reinstatement effects of robots apparently strong enough to compensat displacement effects in Germany, but somewhat weaker in the US (possible  employment protection and vocational training)
Q:

Aspects & Drivers of Indutry 4.0

A:

Aspects of Industry 4.0
• Digital supply chain
• Communication network infrastructure
• Big data / data science
• Artificial intelligence & machine learning
• 3D printing (manufacturing)
• Robotics (automation / automated guided vehicles)
• Sensor Technology
• Augmented reality
• Digital twin = (simulation) models
• Cyber security

•  --> field of action morw dynamic, unpredictable & turbulent (processing speed and flucating demand for products)


Drivers
• Low priced sensors available
• CPU is available cheap and unlimited
• Data mining: Analyse big data close to real-time
• Performance advantages by decentralized networking
• Internet is available worldwide
• Worldwide GPS localization
• Increase in soft-/hardware usability
• Storage is available cheap and unlimited

•  globalization + international competition

•  shortened product lifecycle

•  high cost pressure


Q:

First Generation of MLPA

A:
  • Text analysis, 167 Facebook users - correlate with Big Five, r =.16-.26; e.g., favorite book, friends
  • 50 twitter users, tweet length - correlate with Big Five, r =.24-.40
  • Smartphone use of 83-117 users (call / SMS length) - correlate with ten item Personality inventory (r =.11-.26) Text analysis, correlate with Big Five, r=.16-.26
Q:

Automation, jobs & tasks

A:

automation doesn‘t eliminate all jobs
• tends to eliminate tedious and repetitive tasks
- manual: washing clothes, drying dishes, mowing lawn, digging holes
- cognitive: making change for purchase, memorizing maps, adding numbers
• only if you eliminate all the tasks associated with a particular job, you eliminate that job
• but: that is rare
• 270 detailed occupations listed in the 1950 US Census
• 1 of them has to been eliminated due to automation (elevator operator)


• most jobs are more complicated than we think
• O*NET data base contains a rich set of variables that describe work and worker characteristics, including skill requirements
• example of landscaping and groundskeeping workers
some of those tasks can be automated, but can all of them be automated = what fraction

Q:

Development of the labour market (Overview)

A:
  • 1935: “Thinking Machine Replace the Thinker
  • same now: “Smart robot could soon steal your job”
  • there have always been strong changes in the Employment-to-population ratio (shows the proportion of a country's working-age population that is employed)

USA

  • shared increased in the last 70 years roughly from 56% to 65 % in the year 2000
  • first decline = 1980 dotcom bubble
  • second decline = 2008 in the financial crisis
  • increase to again 61 % in 2019

EU 

  • ratio was larger in 2017 than in 1992
  • also a decline in EU in 2008 for financial crisis

Germany

  • nowadays around 58% → more people in employment than ever in the past
  • even though there are more robots
  •  no decline within the last 30 years
  • negative trend on the German labor market in the late 1990s
  • but then strong positive trend
Q:

Appinio

A:

• Appinio = the fastest market research solution worldwide
• Why founding a new market research solution:
1. The gut feeling
2. Linear development without customer involvement (leads to products or slogans which are misunderstood or not useful) → no market need is main reason for failure which is costly solution: being more customer centric with agile + iterative development + customer involvement 

products are more successful + profitable (involving testing + user feedback tofurther develop)

• but most options for being more customer focused are to slow or there is screening bias (you can get screened out so at some point so you lie to be part of the survey) → which is because of extrinsic motivation (also leads to speeding/bad free text)
• the goal is to have intrinsic motivation where appinio comes in
• features: quickie questions + ask own questions + gamification + compare opinions with others

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