Teaching notes: Knowledge-work services

Summary of Cutolo and Kenney (reading/previous session)

PDE: Platform-dependent entrepreneur

Sources of power in platform owner-PDE relationship

  • Techno-economic bases of platform power (intermediary, network effects, lock-in, “panoptic” control)
  • Platform incentives and resources to PDEs
    • Access to customers
    • Provision of boundary resources
    • Platform governance

Consequences of the power imbalance: Risks for PDEs

  • Separation from customers
  • Algorithmic management: ratings, rankings, and recommendation systems
  • Entry into the PDE’s business
  • Changing the terms of participation
  • Platform access and delisting

PDE responses: Power balancing operations

  • Multihoming (platform and channels)
  • Income diversification
  • Collective action
  • Government action

Development of costs/risks/uncertainty over time

  • From positive platform effects on startup to negative platform effects in the maturity stage

Digital markets for knowledge-intensive services

  • Trillion-dollar: Billionen

Literature review method illustration (blackboard)

  • Problem formulation: objectives / review type (describe / understand / explain / test) / scope and key terminology
  • Search: scope / techniques: database search (keywords / search query), citation search, table-of-content-scan…
  • Screen (prescreen: titles/abstracts - pdfs - screen based on pdfs)
  • Synthesis (depending on the review type)

Announce that we will encounter challenges in each of the three steps (after problem formulation).

Illustration on evidence-based searches

  • basis: existing sample of included (relevant) and excluded (irrelevant) papers.
  • current best practice (litsearchr): look for those terms that are common in the included papers and consider them as keywords E.g., digital platform / microsourcing
  • problem: they could be equally predictive of irrelevant papers (illustrate by highlighting dots representing papers)
    • digital platform -> relevant (5%)
    • digital platform -> irrelevant (95%)
    • microsourcing -> relevant (100%)
    • microsourcing -> irrelevant (0%)
  • more interesting question: what are the terms that predict inclusion? TERMS -> INCLUSION -> key idea: it is equally important to consider irrelevant papers to identify effective queries
  • how can we find the queries that are effective? (e.g., digital platform AND service …)

Illustrate small-scale statistics

Irish soccer fans (100.000) - business or tourists?

  • small scale statistics: few research assistants distribute a survey

    • significance (e.g., 10x more business travelers as usual) is important!

  • large scale statistics: all fans who have a smartphone fill out the survey (99.99%)

    • significance is not important (we have data on almost the entire population)
    • effect size matters! (2% more business travelers or 10x more?)