Understanding Network Effects and Organizational Structure in Digital Economics
Network effects play an important role in digital economics Formally, a good exhibits network effects if the demand for the good depends on how many other people purchase or use it. Network externalities are situations in which the consumption of one individual directly or indirectly influences the utility of another individual. Customers generally select the network, which is expected to consist of most users and thus provides the highest value. These effects commonly occur in network industries and are especially obvious in IT-based services. Fundamentals of network economy Market with network Effekts External effects describe a situation in which the consumption of one individual directly influences the benefit of another individual. Network effects or network externalities are a special case of external effects: The individual benefit of a good depends on the number of other users. If this relationship is positive, we speak of a positive network effect. Direct network effects If the increase in application benefit is caused by interoperability between applicants/users, we speak of a direct network effect. For example, a telephone network: the more new users from our own circle of acquaintances, the greater the added value. New users without a direct personal relationship do not generate greater direct application benefits. I.e. the interaction between the users generates the added value! Indirect network effects There is no direct interaction between the applicants/users. Indirect network effects can result from price effects or multi-fold effects: If the increase in the number of users also increases the variety of products and services on offer, this is referred to as a diversity effect. Multi-fold effect: Growing demand creates more diverse supply with a positive effect on demand. For example, CDs or DVDs: the more users ask for DVDs, the more offers are created by different producers. Price effect: Through economies of scale the average costs decrease; thus the offer costs fall with each additional applicant/user. This price effect has a positive effect on demand. Markets with network effects Economies of scale and multiple effects can lead to network effects (if positive feedback arises). Multi-fold effects do not necessarily go hand in hand with economies of scale. Markets with large economies of scale on the supply side tend towards standardization, hence towards one technology. If, at the same time, the demand side does not demand great diversity, the probability of a positive network effect is high. Network Effects: Probability that the market tends towards a technology. Generate positive Feedback: Evolution: Backward compatibility/ Revolution: completely new product with out backwards compatibility with significant high performance/Openness: access to the customer base for others/ Control: reduces competition, increases value of customer base.
Organisation in Corporations and Structuring Information Flows Organizational Structure: Formal aspects: Enterprise politics/Structure/Processes/Job descriptions/Balance sheets/Plans, rules. Informal aspects: Power/Social relations/Trust/Values/Motivation/Roles, expectations, needs/Organizational culture. Organizational structure: Management’s effort to structure the complex process of operational performance and utilization of performance in such a way that efficiency losses at the execution level are minimized. Developing Organisational Structure: Enterprise goals/tasks analysis/Coordination of positions/Organizational structure of enterprise. Task Analysis: Function oriented (Material management/Production/Marketing) Object oriented (Product A, B, C) Matrix Organization (Fila: Function oriented//Columna: Object oriented). Information Flow: Formal information flows are based on predefined processes or organizational structures that shape the business process in companies. Supply/Customer (value Proposition)-> Process design/SimulationOrganizational structure-> Information logistics/Informational networks. Modeling Methods (OBJECT ORIENTED MODELS): Static representation of static relationships: ER-Models(Data models, organigram)/ Static representation of dynamic relationships: Structogram/PAP/EPC/ Dynamic representation of static relationships/Dynamic representation of dynamic relationships (Petri Net/ finite Automata/ Simulations. Conceptual models ideally have the following characteristics: Implementation independent/Modular/Analyzable/Abstract/Formal/Comprehensible. Entity Relationship Models and Business Modeling: Database Systems: Manages data in a logical entity on an external storage/Software to manage Database. Modeling IT-systems: Data base modeling with Entity-Relationship Models (ER): Abstraction of the real model by using entities and their relationships/An entity is an abstraction of an object of the real world with properties (attributes)/A structure description is called an entity type./An entity set comprises logically related entities that define themselves using the same attributes./If the entity of an entity set can be uniquely identified by an attribute set, this attribute set is called the key candidate/A key candidate is defined as the primary key/A relationship represents relationships between entities. Cardinality Relationship types are classified according to the cardinality of the occurring entity types. In the case of a relationship type between two entity types A and B: 1:1 Relationship: An entity of type A is related to at most one entity of type B (and vice versa)/n:1 Relationship: A type A entity is related to the highest of a type B entity and a type B entity can be related to multiple type A entities/n:m Relationship: An entity of type A can be related to multiple entities of type B and vice versa.
Final Event Driven Process Chains: Constructs of EPC Designation (Representation)-> texto abajo. Function (individual activity or activity of an organization)/(Sub-) Process chain (Representation of condensed process chains)/Events (Occurrence of a state)/Connection (Connection function – event)/Control flow (Time-logical dependencies between events and functions)/Organisation entity (structure of the company)/Informations/Material-/Resource- Object (object)/Information/material flow (relationship Object – Function)/Mapping of organizational entity (relationship Function – Organizational entity). Informal Networks: Official view/Advice network.
Problem Formulation: Information requires: Targeted search for relevant information/Recognition and collection of the own need for information/Procedure for determining the need for information (Subjective/objective/Mixed)/Information Sources: Internal (MIS systems support the research and provision of internal information/Enterprise portals and wikis for internal information exchange)/External(research organizations/specialist publications) BOTH: validity/Trustworthiness/actuality/Relevance in the task context. Definition of Alternatives: Identification of restrictions or conditions that a possible solution must meet. Bsp: Time restrictions/budget constraints/resource constraints. Only alternatives that can be implemented are to be compared/Ways to solve given decision problems: Finding or inventing possible alternatives requires a sufficient degree of relevant expertise, experience and creativity/Search for alternative courses of action-> Which alternatives are available?/Many potential ways to solve given decisions problems/Only a small number of management decisions are structured and can therefore be resolved by familiar procedures/Interdisciplinary approach usually increases the quality of the alternatives developed/Decision theory provides only limited support in the generation of alternatives./Information management provides the means to reduce uncertainty about the alternatives generated. Choice of Alternatives: The basis of a rational decision is an assessment of the consequences of an alternative/In reality, decisions are almost always made with imperfect information/Decision-makers can form an opinion on the probability of the results Occurring/The level of information determines the forecast quality for a result. Decision Theory and Decisions Economic decision Information key role in evaluation and implementation of economic decisions. Asymmetric Information-> never disclose if there is something wrong with the car, unless economic incentive. Buyer doesn’t know. Economic decisions: selection of investment, customer segments, staff selection. Decisions: Structured(Stock/Credit assessment): decisions are taken repeatedly, routinely and according to a defined procedure. / Unstructured (Strategic decisions): non-routine decisions where an assessment, evaluation and understanding of the problem needs to happen. No uniform decision-making processes. Decision theory Provides methods that are formalized w help of information systems and enable structured decision process/Prescriptive: focus on decision logic and rational behavior and establish rules to make the best decisions. Problems: selection of mutual exclusive alternatives/Descriptive: describes why and how decisions are actually made and aims to formulate hypothesis about behavior of people and make predictions or control decision behavior. Basic model: Objective function(decision rule formally)/ A decision field composed of Action alternatives (A= a1,a2,a3…)/ Environmental conditions(Z= z1,z2…)/ Results in forms of a result function or matrix. Game theory, this not take into account actions of other actors (Competitors). Preference Function: Assigns a unique preference value to each alternative. Use: Qualification pf utility values for a set of alternatives. / Theoretical basis of preferences and the consequent rational decisions. If “A” denotes a finite set of alternatives and for each pair a1, a2 belonging to A: – a1 ≽ a2 that the decision-maker slightly prefers a1, a2 – a1 ∼ a2 that the decision-maker is indifferent between a1 and a2 – a1 ≻ a2 that the decision-maker strictly prefers a1,a2. But really, only need larger or equal than (≽) bc a1 ≻ a2 can be written as follows: a1 ≽ a2 and not a2 ≽ a1 and a1 ∼ a2 can be written as follows: a1 ≽ a2 and a2 ≽ a1. To create the preference function we evaluate under certainty: Φ(ai) = U(xi) – one target criterion/uncertainty: Φ(ai ) = E(U(xij)) – one target criterion, expected benefit. In order to take a decision the first step is to be clear about one owns preference. Preference elicitation can be made through conjoint analysis (questionnaires) or recommender systems (amazon, youtube). (Es como si fuse una matriz y a partir de ahi sacas conclusiones de que opción puede pasar en cada caso)_> sus probabilidades y resultados. Information management as a method: Economic efficient planning, procurement, processing, distribution and allocation of information as a resource for the preparation and support of decisions and the design of the necessary framework conditions. Aims: Optimize use of resource information with focus towards corporate goals. It is both management and technical discipline.
ERP – Enterprise resource planning Company wide application that coordinates important internal processes at operational level. Central database->business processes and functional areas: Finance /Human resources/Production/ Sales & marketing: Business Intelligence Techniques for consolidation, analysis and provision of data for decision support. Used budgeting. An example is the data warehouse (DWH) which consists of a database with reporting and filing functions and then a part where patterns and relationships are revealed. Business analytics then makes decisions on that data. MIS – Management information systems Management information about the company’s performance creating reports in specified intervals or on demand. Offers support in solving structured problems. Is used to detect exceeding of budget and to help to reduce it. DSS – Decision support system Helps management to make decisions by combining data, analytical models and software tools. Can be used to solve semi-structured and unstructured decisions with active involvement of the user. Data based DDS: extracts useful data form operational data and carries out OLAP. Sometimes data mining is used with the aim to discover new relations or data that can help with decision taking/Model-based DDS: calculation or simulation models for the analysis of sensitivities in order to optimize business processes. Components: database/Model bank/tools Examples of use for customers are the online car configurator when buying a car: select model, accessories,.. and helps you make a decision about which car to buy. CMR – Customer relations management The DSS can also be used for CRM to analyze customer data, carry out segmentation of customers and detect patterns. Access the customer data warehouse. Then we carry out relevant analysis: Use statistical analysis to identify the best 25% of the most frequent buyers Determination of a correlation between location and sales frequency Review of new customer segments: Regular customers who do not live near a shop regular customers who live near a shop walking living near a shop Query the database for detailed information on each customer segment. ESS – Executive support system Helps with unstructured problems with focus on senior management information needs. Monitor the company’s performance indicators by using internal and external data. It also gives an external view as it allows to analyze competitors and framework conditions. Decision-Making process: 1. Problem formulation and Research/2. Definition of Alternatives/3. Choice of alternatives/4. Implementation.