Eric's Seminar

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Eric's Seminar by Mind Map: Eric's Seminar

1. IS Discipline Identity

1.1. Benbasat & Zmud 2003 Focus on IT Artifact

1.1.1. Avoid exclusion: not include an IT artifact

1.1.2. Avoid inclusion: research that is best left to other disciplines because IT artifact is not key

1.2. Weber 2003 Editor's Comments

1.2.1. Crucial test: if other disciplines have provided theories that account for the phenomena we have identified, we will have done little to contribute to the core of IS

1.2.2. Find phenomena where theory is nonexistent or defficient

2. Electronic Markets

2.1. Market Efficiency & Welfare

2.1.1. Lee 1998 Aucnet Case

2.1.1.1. Electronic marketplaces may not reduce prices due to (1) increase quality (new cars), (2) increase sellers' market power (separation of car transportation cost from auction process, no pressure to sell), and (3) increased buyer externality (more buyers, less search costs, benefit for sellers too).

2.1.1.2. It is a Win-Win for buyers and sellers because of market efficiency

2.1.2. Kambil & van Heck 1998 Framework for exchange organizations based on process-stakeholder analysis (based on Dutch auctions)

2.1.2.1. Basic Trade Process 1. Search – the information gathering and evaluation process undertaken by buyers and sellers to identify opportunities 2. Valuation – price discovery and negotiation 3. Logistics – delivery of actual goods 4. Payment & Settlement – terms and methods of payment 5. Authentication – verify the quality and features of the product offered, the authenticity of the trading parties, and monitor conformance to the contract or agreement

2.1.2.2. Context Processes 6. Communications and computing – infrastructure 7. Product representation – how the product attributes are specified to the buyer and other 3rd parties 8. Legitimation – validate the trade or exchange agreement 9. Influence structures and processes – ratings, systems that enforce obligations or penalties to reduce opportunism risks. 10. Dispute resolution – processes for resolving disputes among parties and structures with decision rights in the event of conflict

2.1.2.3. Propositions 1. Separation of physical & information increases efficiency 2. Information asymmetry is overcome by price discounts or more info available 3. If any stakeholder is worse off, system will fail

2.1.3. Brynjolfsson, Hu & Smith 2003 Product variety & consumer surplus

2.1.3.1. Is is true that increased competition increases consumer surplus (through lower prices)

2.1.3.2. Increased product variety has greater positive impact on consumer surplus

2.1.4. Ghose, Smith & Telang 2006 Product Cannibalization

2.1.4.1. Availability of used products doesn't really cannibalize sales of new products, but rather increase market size

2.1.4.2. Used-book marketplace increases consumer surplus and total social welfare

2.1.4.3. Globally networked IS reduces search costs (Bakos 1997) and enables IT-mediated exchanges (Malone et al 1987)

2.2. Transaction Costs

2.2.1. Malone, Yates & Benjamin 1987 Electronic Markets vs. Hierarchies

2.2.1.1. Factors that favor hierarchies: 1. Coordination costs 2. Asset specificity 3. Complexity of product description

2.2.1.1.1. By reducing coordination costs, IT will lead to overall shift to market over hierarchies

2.2.1.2. The market/hierarchy trade-off is centered in coordination/production costs

2.2.1.2.1. IT will decrease the relative weight of coordination costs vs. production costs

2.2.2. Bakos 1997 Reducing Buyer Search Costs

2.2.2.1. Electronic market place provides information about existence of sellers, their prices and products

2.2.2.1.1. Reduced price hypothesis: lower search costs lead to lower prices

2.2.2.1.2. Net welfare (market efficiency) is increased

2.2.2.2. Benefits to buyers

2.2.2.2.1. 1. Lower prices due to competition among sellers 2. Allocational efficiencies from better purchase-preference fit 3. Lower search costs (despite greater number of inquiries) 4. Consumers' who wouldn't buy now do, thanks to lower search costs

2.2.2.3. Sellers' strategies

2.2.2.3.1. 1. Provide more product information (rather than price information) to convince users to purchase 2. Make products hard to compare vis-a-vis 3. Pursue product differentiation

2.2.3. Chellapa, Sin & Siddarth (WP) Price Dispersion (in airline ticket prices)

2.2.3.1. Vendor's price format remains an important source of price dispersion in both online and offline channels even after accounting for market factors and ticket characteristics

2.3. Uncertainty

2.3.1. Koppius, van Heck & Wolter 2004 (flowers) Defficiencies in product represetation lead to price discounts

2.3.1.1. Alternate explanation to price reduction in online markets

2.3.2. Overby & Jap 2009 Electronic vs. Offline Channels (cars)

2.3.2.1. Low quality uncertainty & rare --> electronic High quality uncertainty & plentiful --> physical Electronic channels led to discounts for products of high quality uncertainty, but not for those of low quality uncertainty

2.3.2.1.1. Alternate explanation to price reduction in online markets

2.3.3. Akerlof 1970 Market for Lemons

2.3.3.1. Low-quality goods can drive out high-quality goods in the presence of information asymmetry, leading to a market for "lemons"

2.3.3.1.1. Information Asymetry (def): The seller knows more about the product than the buyer

2.3.3.1.2. Buyers expect to pay for "average quality", and sellers have incentive to offer "below average quality" to increase profits

2.3.4. Jin & Kato 2007 Dividing Online & Online (baseball cards)

2.3.4.1. Empirical evidence on how buyers and sellers adapt to deal with the trade-off between search cost savings and information quality

2.3.4.2. Adverse selection may be reduced via:

2.3.4.2.1. 1. Search or experience

2.3.4.2.2. 2. Intermediaries

2.3.4.3. Market segmentation

2.3.4.3.1. High or low product quality (low quality uncertainty) is traded online

2.3.4.3.2. Medium product quality (high quality uncertainty) is traded offline

2.3.5. Dewan & Hsu 2004 Adverse Selection (Online stamp auctions)

2.3.5.1. Quality uncertainty induces adverse selection costs => sellers must offer adverse selection discount to compensate for uncertainty

2.3.5.1.1. Learn this by comparing online stamps market with intermediary services vs. eBay

2.3.5.2. Reputation mechanisms have positive (significant but modest) effect on price and probability of transaction taking place

2.3.6. Kazumori & McMillan 2005 Model sellers choice of Online vs. Live auctioning

2.3.6.1. Tradeoff: lower transaction costs online vs. more rent left to bidders online (due to winner's course, buyers bid lower)

2.3.6.2. Determinant of decision is not expected price, but dispersion of valuation

2.3.6.2.1. Dispersion can be reduced if buyers see item for themselves

2.3.6.2.2. A high-value item can be successfully sold online if the bidder's estimates of that value are tightly bunched (low variance)

2.4. Reputation Mechanisms

2.4.1. Dellarocas 2006 Reputation Mechanisms

2.4.1.1. Objective of reputation mechanisms: Enable efficient transactions in communities where cooperation is compromised by post-contractual opportunism (moral hazard) and information asymmetries (adverse selection)

2.4.1.2. Reputation Mechanisms play sanctioning (i.e. eBay) and signaling (i.e. AMZ) role

2.4.2. Dellarocas & Wood 2008 Reporting Bias (silence)

2.4.2.1. Reporting Bias: traders may selectively choose to report certain types of outcomes and not other (i.e. mostly positive)

2.4.2.2. Bias can be corrected for by considering transactions in which either party decided to remain silent

2.5. Other Stuff

2.5.1. Pinker, Seidmann & Vakrat 2003 Managing Online Auctions

2.5.1.1. Research Avenues: 1. Behavior of online auction participants 2. Optimal design of online auctions 3. Integration of auctions for firms' operation 4. Analysis of auction data

2.5.1.2. Impact of IT on auctions 1. Reduce search costs (Bakos 1997) 2. More participants (buyers & sellers) 3. Ability to perform complex processes 4. Easy data collection 5. Asynchronous participation

3. Theory in IS

3.1. Gregor 2006 Nature of Theory in IS

3.1.1. Theories have (1) constructs, (2) propositions and relationships, and (3) relationships must be falsifiable

3.1.2. Types of theory: analysis, explanation, prediction, explanation-prediction (EP), design and action

3.2. DeSanctis & Poole 1994 AST

3.2.1. The technology structure and the structure of social action both describe how/if adoption/adaptation takes place

3.2.1.1. Technologies have features (functionalities) and spirit (goals)

3.2.1.2. Organizations have tasks, organizational structures

3.2.1.3. New structures emerge as technology is embraced

3.2.2. Jones & Karsten 2008 Review Gidden's 1984 Structuration Theory, which is a base of AST

3.3. Goodhue & Thompson 1995 TTF + Individual Performance = Technology-to-Performance Chain (TPC)

3.3.1. For positive impact a technology must:

3.3.1.1. Be used <= and intention drives usage

3.3.1.1.1. Use is not always voluntary

3.3.1.1.2. Utilization does not necessarily drive performance

3.3.1.2. Have fit with task it is intented

3.3.1.2.1. TTF is the degree to which a technology assists an individual in performing her portfolio of tasks. It is correspondence between requirements, individual abilities, and tech functionalities.

3.4. Davis, Bagozzi & Warshaw 1989 User Acceptance of Computer Technology

3.4.1. Fishbein & Ajzen 1975 TRA

3.4.1.1. Beliefs--> Attitutdes --> Intentions --> Action

3.4.2. Davis 1986 TAM

3.4.2.1. PU

3.4.2.2. PEOU

3.5. Venkatesh, Morris, Davis & Davis 2003 UTAUT - Unified Theory of Acceptance & Use of Technology

3.5.1. 1. Performance Expectancy (PU) 2. Effort expectancy (PEOU) 3. Social influence ... all drive behavioral intention

3.5.1.1. All 4 drive Use behavior

3.5.2. 4. Facilitating conditions (technical & organizational infrastructures)

3.6. Overby 2008 Process Virtualization Theory (PVT)

3.6.1. Definition of Process Virtualization

3.6.1.1. Process: a set of steps to achieve an objective

3.6.1.2. Physical Process: involves physical interaction between people or between people & objects

3.6.1.3. Virtual process: physical interaction is removed

3.6.2. Virtualizability measures: 1. Adoption 2. Quality of process outcomes

3.6.3. Main negative effects to virtualizability

3.6.3.1. 1. Sensory requirements 2. Relationship requirements 3. Synchronism requirements 4. Identification & Control requirements

3.6.4. Moderators of main effects (all positive moderators that enhance main effects)

3.6.4.1. 1. Representation 2. Reach (participation across time & space) 3. Monitoring capability

3.6.5. This theory is different from prior theory

3.6.5.1. Virt. vs. Innovation Diffusion: These constructs are characteristics of a process, innov diff refers to innovation characteristics (relative advantage, ovservability, complexity, etc)

3.6.5.2. Virt. vs. Media Richness: Media richness refers to person-to-person communication. Virt theory applies to both communication and other processes like trade

3.6.6. Overby & Kosynski 2008 PVT in the context of IS

3.6.6.1. Virtualization is core to IS discipline: 1. electronic commerce studies 2. distance learning studies 3. online community studies 4. virtual team studies --> Are all unique topics to IS

3.6.6.2. PVT relates to TTF in explaining what tasks can be virtualized, but is is more general than TTF becuase it addresses other issues (i.e. economics)

4. Education & Research

4.1. Dhar & Sundararajan 2007 Tech Centric, Bus Centric IT Invariants

4.1.1. Technology centric 1. Unique characteristics of digital goods 2. Network effects in IT-based business 3. Human behavior/interaction in IT-mediated space

4.1.2. Business centric 1. IT transforms industry & society 2. Investment in IT is critical 3. Usage of data for decision-making

4.1.3. Invariant aspects of IT 1. Digital representation of information 2. Sustained growth of computing power 3. Increase in complexity and usefulness via modularity

4.2. Distance Learning (1998-2004)

4.2.1. Salomon & Perkins 1998 Individual & Social Aspects of Learning

4.2.1.1. Learning involves: 1. Situative, participation-oriented social aspects 2. Cognitive, acquisition-oriented individual aspects

4.2.2. Piccoli, Ahmad & Ives 2001 Effectiveness of web-based learning (Virtual Learning Environments)

4.2.2.1. Learner control (def): degree of discretion that students can exert over the pace, sequence, and content of instruction in a learning environment

4.2.2.2. There is no clear improvement or decline in educational effectiveness by the introduction of distance learning technologies

4.2.2.3. VLE (in terms of learner control) leads to higher reported computer self-efficacy, but also to less satisfaction with learning process

4.2.3. Allen et al 2004 Effectiveness of distance learning

4.2.3.1. Meta-analysis to compare literature on distance learning

4.2.3.2. Distance education (def): a course in which the expectation is that the student and instructor will not be physically copresent in the same location

4.2.3.3. Result: distance education technologies do not necessarily create less effective learning environment and, in some instances, may increase effectiveness

5. Interpersonal Communication & Task Completion

5.1. Daft, Lengel & Trevino 1987 Media Richness Theory

5.1.1. Media Richness (def): The ability of information to change understanding within a time interval. Face-to-face is richest.

5.1.1.1. Criteria for richness: 1. Feedback 2. Multiple cues (voice, video, text) 3. Language variety (range of meanings; numbers vs. text) 4. Personal focus

5.1.2. Performance increases when managers match media richness with task equivocality.

5.1.2.1. Use richer media for equivocal tasks (where there are multiple and possible conflicting interpretations to the available information)

5.1.2.2. Use lean media for non-equivocal tasks

5.1.3. Uncertainty can be dealt with more information, equivocality can only be dealt with richness

5.1.4. Dennis & Kinney 1998 Testing MRT

5.1.4.1. prior studies analyzed media choice, but not actual outcome performance

5.1.4.2. Rationale: MRT was proposed for communication tasks, and this study focused on decision making tasks. MRT might only be suitable for simpler communication tasks.

5.2. Carlson & Zmud 1999 Channel Expansion Theory

5.2.1. Channel expansion theory is a theory of media perceptions that explains what factors drive user perceptions of user media

5.2.1.1. Dependent variable is "perceptions of channel"

5.2.2. Find that experiences, rather than plain channel usage, drive richness perceptions

5.2.2.1. 1. Experiences with the channel 2. Experiences with messaging topic 3. Experiences with organizational context 4. Experience with co-participants

5.2.3. Can explain failure of MRT: managers chose media because they developed richness through experiences, rather than richness being inherent en media. Experiences drive richness.

5.3. Heninger, Dennis & Hilmer 2006 Individual Cognition & Dual-Task Interference

5.3.1. Dual-task (def): (1) contributing to the discussion and (2) processing new information received from discussion

5.3.2. Dual-task interference actually reduces the capability of information processing and consequently the performances of the decision making process

6. Online Communities & Trust

6.1. Jarvenpaa & Leidner 1999 Trust in Global Virtual Teams

6.1.1. Virtual Team (def): 1. temporary (no common past nor future) 2. culturally diverse 3. geographical dispersed 4. electronic communication

6.1.1.1. Pros: flexibility, responsiveness, lower costs, dynamic

6.1.1.2. Cons: low commitment, role overload, role ambiguity, absenteeism

6.1.2. Handy 1995 "Trust needs touch"

6.1.2.1. McGarth 1991 Time, Interaction, Performance (TIP) Technology inhibits modes and thus performance

6.1.2.2. MRT (Daft 1987) & Social Presence (Short et al 1976) Technology eliminates cues needed

6.1.2.3. Walther (1996, 1997) Social information processing theory Technology makes communication slower

6.1.2.4. SIDE (Social Identification/Deidentification) Technology->less cues-> more stereotypes-> deidentification

6.1.3. Swift trust (def): de-emphasizes interpersonal dimensions & is based initially on broad categorical structures and later on action

6.1.4. Trust, despite swift (based on structure and temporal), can exist in teams purely built on electronic networks

6.2. Ma & Agarwal 2007 Identity Verification & Contribution

6.2.1. Study uses Identity-based view to understand how the use of IT-based features in community are related to knowledge contribution

6.2.2. There is a positive relationship between perceived identify verification and knowledge contribution and satisfaction

6.2.2.1. Identity is related to extrinsic beneifts (recognition & economic rewards)

6.2.2.2. But not related to intrinsic benefits (sense of self-worth, social norms, social affiliation)

6.2.3. Perceived identify is improved by virtual co-presence, persistent labeling, self-presentation and deep profiling

6.3. Wasko & Faraj 2005 Social Capital (, individual motivations) and Knowledge Contribution

6.3.1. Based on theories of collective action: individual motivations and social capital

6.3.2. Social Capital (def): resources embedded in a social structure that are accessed and/or mobilized in purposive action

6.3.3. Drivers of Contribution 1. Individual Motivations (reputation & joy of helping) 2. Structural Capital (centrality) 3. Cognitive Capital (self-related expertise & tenure in the field) 4. Relational Capital (commitment & reciprocity)

6.4. Mesch & Talmud 2006 Role of Multiplexity & Duration

6.4.1. Relate offline and online relationships

6.4.2. Closeness to a friend is function of: 1. Social similarity 2. Content & activity multiplexity 3. Duration of relationships

6.4.3. Social association perspective shows how quality of relationships come from social statuses and not the communication channels

7. Global Disaggregation of Business Processes

7.1. Apte & Mason 1995 Disaggregation of Information-Intensive Services What activities should be disaggregated?

7.1.1. Pros of Disaggregation: 1. Cost reduction 2. Access to large pool of personnel 3. Faster cycle time for design & dev 4. Access to large growing market

7.1.2. Cons of Disaggregation: 1. Difficulties in communication and coordination 2. Potential violation of IPR (intellectuual property rights) 3. Lack of control on quality & schedule 4. Political & government concerns 5. Cultural diversity 6. Unstable economic, political & social environments

7.1.3. Activities likelier to disaggregate: 1. High in information intensity 2. Low in customer contact need 3. Low in physical presence need

7.1.4. As in outsourcing, consider "strategic importance" and "organization's relative efficiency in performing activity"

7.2. Mithas & Whitaker 2007 Is the world flat or spiky? What drives occupation disaggregation?

7.2.1. Drivers of occupation disaggregation: 1. Codifiability 2. Standardizability 3. Modularizability

7.2.2. Effects are moderated by skills: higher needed skills mitigate convenience of disaggregation

7.2.2.1. The inclusion of skills extends Apte & Mason's work

7.2.2.2. Find that high-skill and information intensive jobs have actually experience employment growth, rather than suffered from disaggregation => there's is still spikiness

8. Business Value of IT (1996-2001)

8.1. Brynjolfsson & Hitt 1996 Paradox Lost

8.1.1. Computer capital and IT staff have a positive effect on output contribution

8.1.2. The net benefit of IT spending is positive

8.2. Bharadway, Bharadwaj & Kosynski 1999 IT's effects by Tobin's Q

8.2.1. Tobin's Q better captures long-run and intangible benefits of IT

8.2.2. Variation in Tobin's Q can be explained by IT expenditure

8.3. Bharadway 2000 RBV: IT Capabilities & Performance

8.3.1. IT Capabilities: 1. IT infrastructure 2. Human IT skills 3. IT-enabled intangibles

8.3.2. IT capabilities can explain performance

8.3.2.1. After finding matched control group via firm size (sales), performance is measured by reduction in costs and/or increase in profits

8.4. Duliba, Kauffman & Lucas 2001 Appropriating Value from IT

8.4.1. Airline ownership of reservations system is related to their performance

8.4.2. Just having a system is not enough for competitive advantage (it is imitable), but converting it in a specialized asset is good