Management Theory Review: May 2016

May 31, 2016

May 17, 2016

The Management of Information Systems - Dickson and Wetherbe - Book Information

Gary W. Dickinson and James C. Wetherbe
1985 Book
McGraw Hill Book Company

Part I. Introduction
Ch. 1 The MIS Executive

Part 2. MIS Organization

Ch. 2 The Organizational Use of Computers
3 Organizing and Staffing the MIS Function

Part 3. Managing MIS Personnel
4. Contingency Management and the MIS Function
5. Achieving Job Productivity and Satisfaction

Part 4. MIS Planning and Control
6. Strategic Planning for MIS
7. Management Assessment and Evaluation of MIS

Part 5. Key Technology Trends and Implications
8. Database Management Systems
9. Decision Support Systems
10. Data Communication Systems
11. Distributed Data Processing
12. Advanced Office Systems
13. Robotics and MIS

Part 6. Managing MIS Development
14. Systems Analysis and Design Strategies and Procedures
15. Software Development
16. Implementation

Part 7. Management of Production and Computer Operations
17. Computer Capacity Planning
18. Hardware and Software Acquisition
19. Computer Operations Management

MISM Course at CMU, Pittsburgh

Master of Information Systems Management (MISM) program was developed from the ground up as a blended business-technology program. Through our program, students will develop better planning, management and technical abilities that focus on the application of technology to create business value.

Quantitative management and technology: Our information systems courses offer a unique blend of technology, management, and strategy.

Information Systems Management (MISM) - 16-Month Track
Unlike our competition, the Master of Information Systems Management (MISM) program was developed from the ground-up as a blended business-technology program. Through our program, you'll develop better planning, management and technical abilities necessary for leading a thriving organization in today's complex, digital world.

The MISM degree requires you to demonstrate proficiency in technology management, IT Strategy, and fundamental business skills.

MISM Course Requirements
The required courses are designed to build core competencies in integrating technology management with business expertise with courses ranging from Economic for IT to Object Oriented Programming in Java. As a student in the MISM program, you also have the flexibility to choose from a range of challenging elective courses designed to help you excel in an increasingly digital world.

Important Points from the Chapters

Ch. 1 The MIS Executive

The emergence of business and management information systems (MIS) in organizations has created an intense demand for well-trained, capable information systems managers to plan, organize, direct and control the powerful technology of computer-based information systems.

The topics presented in the book provide a managerial, organizational, behavioral, and technical treatment of MIS management.

MIS executives must blend management, business, technical, and interpersonal relations.

Ch. 2 The Organizational Use of Computers

Ch 4. Contingency Management and the MIS Function

The basic foundation of the contingency theory is that the effectiveness of a management approach is contingent upon the organizational environment in which it is applied. This abandons the concept that there is a "best way" to manage in all environments.

IS function is divided into three important functions: Systems development, production, technical services.

Ch 5. Achieving Job Productivity and Satisfaction

The most highly regarded of motivational theories are as follows:

Maslow's need hierarchy - A.G. Maslow 1943
Reinforcement - B.F. Skinner 1953
Attribution theory - F. Heider 1958
Herzberg's dual factory theory - F. Herzberg 1959
Expectancy theory - V. Vroom 1964
Goal Setting - E.A. Locke 1976

Practical Guidelines

1. Efforts to increase motivation must first focus on the employee's needs (Maslow, Herzberg)

2. work assignments and goals should be realistic and clearly defined; rewards for performance should be practical and fulfill the motivational needs of the employee (Locke, Vroom).

3. Consequences or outcomes of good performance must approximate the expectations of the employee (Skinner, Heider)

Positive versus Negative Control of Behavior

Behavioral Management Tasks

Communicating
Imitation
Shaping
Reinforcement (Scheduling)

Ch. 6. Strategic Planning for MIS

A four stage model of MIS planning consisting of strategic planning, organization information requirements analysis, resource planning and allocation, and project planning is discussed in this chapter.

The challenges of MIS planning are:

1. Alignment of the MIS plan with the overall strategies and objectives of the organization.
2. Design of an information system structure or architecture for the organization.
3. Allocation of information system development and operations resources among competing applications.
4. Completing information system projects on time and on schedule.

Information Systems Management in the Big Data Era - Lake and Drake - 2014 - Book Information

https://books.google.co.in/books?id=absoBgAAQBAJ

http://www.springer.com/us/book/9783319135021

Authors: Lake, Peter, Drake, Robert
Publisher Springer

Table of Contents

1 Introducing Big Data .............................................................................. 1
1.1 What the Reader Will Learn......................................................... 1
1.2 Big Data: So What Is All the Fuss About?................................... 1
1.2.1 Defining “Big Data”...................................................... 2
1.2.2 Big Data: Behind the Hype ........................................... 3
1.2.3 Google and a Case of the Flu........................................ 6
1.3 Big Data: The Backlash Begins ................................................... 6
1.3.1 Big Data Catches a Cold............................................... 6
1.3.2 It’s My Data – So What’s in It for Me?......................... 8
1.3.3 Bucking the Backlash – The Hype Cycle ..................... 9
1.4 A Model for Big Data .................................................................. 11
1.4.1 Strategy ......................................................................... 12
1.4.2 Structure........................................................................ 13
1.4.3 Style .............................................................................. 13
1.4.4 Staff............................................................................... 13
1.4.5 Statistical Thinking ....................................................... 14
1.4.6 Synthesis....................................................................... 14
1.4.7 Systems......................................................................... 15
1.4.8 Sources.......................................................................... 15
1.4.9 Security ......................................................................... 16
1.5 Summary ...................................................................................... 16
1.6 Review Questions......................................................................... 16
1.7 Group Work/Research Activity .................................................... 17
1.7.1 Discussion Topic 1 ........................................................ 17
1.7.2 Discussion Topic 2 ........................................................ 17
References................................................................................................. 17

2 Strategy .................................................................................................... 19
2.1 What the Reader Will Learn......................................................... 19
2.2 Introduction.................................................................................. 19
2.3 What is Strategy? ......................................................................... 20
2.4 Strategy and ‘Big Data’................................................................ 22
2.5 Strategic Analysis......................................................................... 26
2.5.1 Analysing the Business Environment ........................... 26
2.5.2 Strategic Capability – The Value Chain ........................ 32
2.5.3 The SWOT ‘Analysis’................................................... 38
2.6 Strategic Choice ........................................................................... 43
2.6.1 Introduction................................................................... 43
2.6.2 Type, Direction and Criteria
of Strategic Development.............................................. 44
2.6.3 Aligning Business and IT/IS Strategy........................... 47
2.7 Summary ...................................................................................... 51
2.8 Review Questions......................................................................... 51
2.9 Group Work Research Activities.................................................. 51
2.9.1 Discussion Topic 1 ........................................................ 51
2.9.2 Discussion Topic 2 ........................................................ 51
References................................................................................................. 52

3 Structure .................................................................................................. 53
3.1 What the Reader Will Learn......................................................... 53
3.2 Introduction.................................................................................. 53
3.3 What Is ‘Structure’? ..................................................................... 55
3.3.1 What Do We Mean by ‘Structure’?............................... 55
3.4 Formal Structures......................................................................... 56
3.4.1 The “Organisational Chart”: What Does
It Tell Us?...................................................................... 56
3.4.2 Structure, Systems and Processes................................. 61
3.4.3 Formal Structure: What Does This Mean
for Big Data?................................................................. 65
3.4.4 Information Politics ...................................................... 66
3.5 Organisational Culture: The Informal Structure .......................... 69
3.5.1 What Do We Mean by ‘Culture’? ................................. 69
3.5.2 Culture and Leadership................................................. 69
3.5.3 The “Cultural Web”....................................................... 71
3.6 Summary ...................................................................................... 78
3.7 Review Questions......................................................................... 78
3.8 Group Work/Research Activity .................................................... 78
3.8.1 Discussion Topic 1 ........................................................ 78
3.8.2 Discussion Topic 2 ........................................................ 79
References................................................................................................. 79

4 Style .......................................................................................................... 81
4.1 What the Reader Will Learn......................................................... 81
4.2 Introduction.................................................................................. 81
4.3 Management in the Big Data Era................................................. 82
4.3.1 Management or Leadership?......................................... 82
4.3.2 What Is ‘Management’?................................................ 83
4.3.3 Styles of Management................................................... 86
4.3.4 Sources of Managerial Power ....................................... 87
4.4 The Challenges of Big Data (the Four Ds)................................... 90
4.4.1 Data Literacy................................................................. 90
4.4.2 Domain Knowledge ...................................................... 92
4.4.3 Decision-Making........................................................... 93
4.4.4 Data Scientists............................................................... 96
4.4.5 The Leadership Imperative ........................................... 98
4.5 Summary ...................................................................................... 99
4.6 Review Questions......................................................................... 100
4.7 Group Work/Research Activity .................................................... 100
4.7.1 Discussion Topic 1 ........................................................ 100
4.7.2 Discussion Topic 2 ........................................................ 100
References................................................................................................. 100

5 Staff .......................................................................................................... 103
5.1 What the Reader Will Learn......................................................... 103
5.2 Introduction.................................................................................. 103
5.3 Data Scientists: The Myth of the ‘Super Quant’.......................... 104
5.3.1 What’s in a Name? ........................................................ 104
5.3.2 Data “Science” and Data “Scientists”........................... 105
5.3.3 We’ve Been Here Before…........................................... 110
5.4 It Takes a Team…......................................................................... 111
5.4.1 What Do We Mean by “a Team”?................................. 111
5.4.2 Building High-Performance Teams .............................. 113
5.5 Team Building as an Organisational Competency ....................... 117
5.6 Summary ...................................................................................... 121
5.7 Review Questions......................................................................... 121
5.8 Group Work/Research Activity .................................................... 122
5.8.1 Discussion Topic 1 ........................................................ 122
5.8.2 Discussion Topic 2 ........................................................ 122
References................................................................................................. 122

6 Statistical Thinking................................................................................. 125
6.1 What the Reader Will Learn......................................................... 125
6.2 Introduction: Statistics Without Mathematics.............................. 125
6.3 Does “Big Data” Mean “Big Knowledge”? ................................. 126
6.3.1 The DIKW Hierarchy ................................................... 127
6.3.2 The Agent-in-the-World................................................ 128
6.4 Statistical Thinking – Introducing System 1 and System 2 ......... 129
6.4.1 Short Circuiting Rationality.......................................... 132
6.5 Causality, Correlation and Conclusions....................................... 133
6.6 Randomness, Uncertainty and the Search for Meaning............... 135
6.6.1 Sampling, Probability and the Law
of Small Numbers......................................................... 137
6.7 Biases, Heuristics and Their Implications for Judgement............ 138
6.7.1 Non-heuristic Biases..................................................... 142
6.8 Summary ...................................................................................... 144
6.9 Review Questions......................................................................... 144
6.10 Group Work Research Activities.................................................. 145
6.10.1 Discussion Topic 1 – The Linda Problem..................... 145
6.10.2 Discussion Topic 2 – The Birthday Paradox................. 145
References................................................................................................. 146

7 Synthesis................................................................................................... 147
7.1 What the Reader Will Learn......................................................... 147
7.2 From Strategy to Successful Information Systems...................... 147
7.2.1 The Role of the Chief Information Officer (CIO)......... 148
7.2.2 Management of IS Projects........................................... 149
7.3 Creating Requirements That Lead to Successful
Information Systems.................................................................... 151
7.4 Stakeholder Buy-In ...................................................................... 154
7.5 How Do We Measure Success...................................................... 155
7.6 Managing Change ........................................................................ 156
7.7 Cost Benefits and Total Cost of Ownership ................................. 158
7.7.1 Open Source.................................................................. 158
7.7.2 Off the Shelf vs Bespoke .............................................. 159
7.7.3 Gauging Benefits........................................................... 160
7.8 Insourcing or Outsourcing?.......................................................... 161
7.9 The Effect of Cloud...................................................................... 163
7.10 Implementing ‘Big Data’.............................................................. 164
7.11 Summary ...................................................................................... 165
7.12 Review Questions......................................................................... 166
7.13 Group Work Research Activities.................................................. 166
7.13.1 Discussion Topic 1 ........................................................ 166
7.13.2 Discussion Topic 2 ........................................................ 166
References................................................................................................. 166

8 Systems..................................................................................................... 169
8.1 What the Reader Will Learn......................................................... 169
8.2 What Does Big Data Mean for Information Systems?................. 169
8.3 Data Storage and Database Management Systems...................... 170
8.3.1 Database Management Systems.................................... 172
8.3.2 Key-Value Databases .................................................... 173
8.3.3 Online Transactional Processing (OLTP) ..................... 173
8.3.4 Decision Support Systems (DSS) ................................. 175
8.3.5 Column-Based Databases ............................................. 176
8.3.6 In Memory Systems...................................................... 176
8.4 What a DBA Worries About......................................................... 177
8.4.1 Scalability ..................................................................... 177
8.4.2 Performance .................................................................. 178
8.4.3 Availability.................................................................... 179
8.4.4 Data Migration.............................................................. 179
8.4.5 Not All Systems Are Data Intensive ............................. 182
8.4.6 And There Is More to Data than Storage ...................... 183
8.5 Open Source................................................................................. 183
8.6 Application Packages................................................................... 184
8.6.1 Open Source vs Vendor Supplied?................................ 186
8.7 The Cloud and Big Data............................................................... 187
8.8 Hadoop and NoSQL..................................................................... 189
8.9 Summary ...................................................................................... 190
8.10 Review Questions......................................................................... 190
8.11 Group Work Research Activities.................................................. 191
8.11.1 Discussion Topic 1 ........................................................ 191
8.11.2 Discussion Topic 2 ........................................................ 191
References................................................................................................. 191

9 Sources..................................................................................................... 193
9.1 What the Reader Will Learn......................................................... 193
9.2 Data Sources for Data – Both Big and Small............................... 193
9.3 The Four Vs – Understanding What Makes Data Big Data ......... 194
9.4 Categories of Data........................................................................ 196
9.4.1 Classification by Purpose.............................................. 196
9.4.2 Data Type Classification and Serialisation
Alternatives................................................................... 198
9.5 Data Quality ................................................................................. 202
9.5.1 Extract, Transform and Load (ETL) ............................. 205
9.6 Meta Data..................................................................................... 206
9.6.1 Internet of Things (IoT) ................................................ 206
9.7 Data Ownership............................................................................ 209
9.8 Crowdsourcing ............................................................................. 210
9.9 Summary ...................................................................................... 212
9.10 Review Questions......................................................................... 212
9.11 Group Work Research Activities.................................................. 212
9.11.1 Discussion Topic 1 ........................................................ 213
9.11.2 Discussion Topic 2 ........................................................ 213
References................................................................................................. 213

10 IS Security................................................................................................ 215
10.1 What the Reader Will Learn......................................................... 215
10.2 What This Chapter Could Contain but Doesn’t ........................... 215
10.3 Understanding the Risks .............................................................. 216
10.3.1 What Is the Scale of the Problem?................................ 216
10.4 Privacy, Ethics and Governance ................................................... 218
10.4.1 The Ethical Dimension of Security............................... 218
10.4.2 Data Protection.............................................................. 221
10.5 Securing Systems......................................................................... 224
10.5.1 Hacking......................................................................... 224
10.5.2 Denial of Service........................................................... 225
10.5.3 Denial of Service Defence Mechanisms....................... 226
10.5.4 Viruses and Worms and Trojan Horses
(Often Collectively Referred to as Malware)................ 227
10.5.5 Spyware......................................................................... 228
10.5.6 Defences Against Malicious Attacks ............................ 228
10.6 Securing Data............................................................................... 230
10.6.1 Application Access Control .......................................... 233
10.6.2 Physical Security........................................................... 234
10.6.3 Malicious Insiders and Careless Employees................. 235
10.7 Does Big Data Make for More Vulnerability? ............................. 235
10.8 Summary ...................................................................................... 235
10.9 Review Questions......................................................................... 236
10.10 Group Work Research Activities.................................................. 236
10.10.1 Discussion Topic 1 ........................................................ 236
10.10.2 Discussion Topic 2 ........................................................ 236
References................................................................................................. 237

11 Technical Insights.................................................................................... 239
11.1 What the Reader Will Learn......................................................... 239
11.2 What You Will Need for This Chapter ......................................... 239
11.3 Hands-on with Hadoop ................................................................ 240
11.3.1 The Sandbox ................................................................. 240
11.3.2 Hive............................................................................... 248
11.3.3 Pig ................................................................................. 251
11.3.4 Sharing Your Data with the Outside World................... 256
11.3.5 Visualization ................................................................. 258
11.3.6 Life Is Usually More Complicated!.............................. 261
11.4 Hadoop Is Not the Only NoSQL Game in Town!........................ 262
11.5 Summary ...................................................................................... 263
11.6 Review Questions......................................................................... 263
11.7 Extending the Tutorial Activities.................................................. 263
11.7.1 Extra Question 1 ........................................................... 263
11.7.2 Extra Question 2 ........................................................... 264
11.7.3 Extra Question 3 ........................................................... 264
11.8 Hints for the Extra Questions....................................................... 264
11.9 Answer for Extra Questions......................................................... 264
11.9.1 Question 1 ..................................................................... 264
11.9.2 Question 2 ..................................................................... 265
11.9.3 Question 3 ..................................................................... 265
Reference .................................................................................................. 266

12 The Future of IS in the Era of Big Data................................................ 267
12.1 What the Reader Will Learn......................................................... 267
12.2 The Difficulty of Future Gazing with IT...................................... 267
12.3 The Doubts................................................................................... 268
12.4 The Future of Information Systems (IS)...................................... 269
12.4.1 Making Decisions About Technology........................... 271
12.5 So What Will Happen in the Future? ........................................... 275
12.5.1 The Future for Big Data................................................ 275
12.5.2 Ethics of Big Data......................................................... 279
12.5.3 Big Data and Business Intelligence .............................. 280
12.5.4 The Future for Data Scientists ...................................... 281
12.5.5 The Future for IS Management..................................... 282
12.5.6 Keeping Your Eye on the Game .................................... 285
12.6 Summary ...................................................................................... 286
12.7 Review Questions......................................................................... 286
12.8 Group Work Research Activities.................................................. 287
12.8.1 Discussion Topic 1 ........................................................ 287
12.8.2 Discussion Topic 2 ........................................................ 287
References................................................................................................. 287
Index................................................................................................................. 289

http://www.springer.com/us/book/9783319135021

Big Data System Development
2015 Presentation by Chen et al.
https://sse.uni-due.de/bigdse15/BIGDSE2015-Chen_et_al.pdf

Addressing the Software Engineering Challenges of Big Data
POSTED ON OCTOBER 21, 2013 BY IAN GORTON IN ARCHITECTURE
https://insights.sei.cmu.edu/sei_blog/2013/10/addressing-the-software-engineering-challenges-of-big-data.html

Article - McKinsey Quarterly October 2011
Are you ready for the era of ‘big data’?
By Brad Brown, Michael Chui, and James Manyika
http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/are-you-ready-for-the-era-of-big-data

May 14, 2016

May 3rd Week - MBA Management Knowledge Management Revision

Introduction to Organizational Behavior

Third Week 15 May to 19 May

Environmental context: Information Technology and Globalization
Environmental context: Diversity and Ethics

Organizational Context: Design and Culture
Organizational Context:: Reward Systems

Perception and Attribution
Personality and Attitudes

Motivational Needs and Processes
Positive Psychology Approach to OB

Communication
Decision Making

May - Management Knowledge Revision

May 3, 2016

Relevant Information and Decision Making - Marketing Decisions - Review Notes

Many marketing decision models use accounting information

Illustrative Decisions

The special sales order

_________________

_________________
Rutgers Accounting Web

Deletion or addition of products, services, or departments

Optimal use of limited resources

Pricing decisions

Target costing - Price derived new product target cost

Updated 3 May 2016, 8 Dec 2011

Relevant Information and Decision Making - Production Decisions - Review Notes

Many production decision models require accounting information.

Management accounting is branch of accounting wherein accountants provide data that helps in taking specific management decisions. Management has various subject based approaches and quantitative management decision making approach requires cost data for taking decisions using various optimization models. Revenue data is also required for management decision making. Decision making is future oriented and hence requires estimates of various costs and revenues for the future periods. But estimates of costs and revenues cannot be made and verified (for their accuracy) unless accounting system provides actual historical costs and revenues. Historical cost details provided by the accounting system can be modified for volume data and price expectations and estimates can be made more easily and accurately by operation personnel. Management cost objective related accounting work involves going through ledger data and summarizing the data that accurately reflects the cost elements that go into the cost objective in various transactions done by various departments of the organization.

Some of the decision models requiring cost data are:

1. Product mix determination: Requires revenue estimates and cost estimates to give profit estimates for each of the products considered for product mix determination.

2. Economic order quantity model (Purchase)

Simple economic order quantity formula is given by EOQ = SQRT (2AS/I)
where A = annual demand in units, S = order cost for each order issue and receipt and I = Inventory carrying cost per unit per annum.

To implement this model inventory control manager requires the estimates of ordering cost and inventory carrying cost.

3. Economic Order quantity model (Production)

The model is similar to purchase model. But now S is set up cost for the machine. To implement this model production planner or controller needs the estimate of set up cost for each machine. Management accountants have to take the set up cost for machine of each machine as cost objective and find out the set up cost.

4. Quality Cost

Quality cost model argues companies are incurring less cost in designing quality and preventing defects and are spending more in repairing defects and related losses. Management accountants have to take these cost ideas as cost objectives and prepare a statement showing cost of designing quality, cost of preventing defects and cost of actual defective parts. This data is going motivate the company management to increase investments in designing for quality and preventive devices or systems.

Product Line Decision - Keep it or Drop it
________________

________________
Mean That

One Time Special Order Decision

________________

________________
Brian Routh TheAccountingDr

Decision Making & Relevant Information: Make-or-Buy,

_________________

Brian Routh TheAccountingDr

Originally posted at
http://knol.google.com/k/narayana-rao/cost-based-management-decision-making/2utb2lsm2k7a/2084

Updated 3 May 2016, 12 May 2015
First posted 8 Dec 2012

Relevant Information and Decision Making - HR and Other Functions

Accounting information is used in HR function decision making.

Human resource accounting is now a well developed field in management accounting.

Human resource management decision like investing in training are done through quantitative cost benefit models and accounting provides cost related inputs to these decision models in human resource management.

Human Resources Accounting
_________________

_________________
NIMTx

Updated 3 May 2016

May 2nd Week - MBA Management Knowledge Management Revision

Second Week 8 May to 12 May 2016

Managerial Accounting or Management Accounting - Review Notes
Relevant Information and Decision Making - Marketing Decisions

Relevant Information and Decision Making - Production
Relevant Information and Decision Making - HR

The Master Budget - Accounting Information
Flexible Budgets and Variance Analysis - Review Notes

Responsibility Accounting for Management Control
Accounting Information for Management Control in Divisionalized Companies

Capital Budgeting - Accounting and Cost Information

Introduction to Organizational Behavior

May 2, 2016

Cost Information for Transfer Pricing

The "transfer price" is the amount charged by one segment of an organization for a product or service that it supplies to another segment of the same organization. The economic reason for charging transfer prices is
to be able to evaluate the performance of the group entities concerned. By charging prices for goods and services transferred within a group, managers of group entities are able to make the best possible decision as to whether to buy or sell goods and services inside or outside the group. About half of the major groups in the world transfer goods and services internally on the basis of a cost-oriented system. Some MNEs use only variable costs, other full costs, and still other use full costs plus a profit mark up (cost-plus method). Some use standard costs, other actual costs.

When there is a competitive open market for the products or services transferred internally, an alternative method is to use the market price as a transfer price. The market price may be derived from published price lists for similar products and services (external market price) or it may be the price charged by a group entity to its external customers (internal market price). Sometimes, the transfer may take place in an earlier stage of production instead of as marketable unit. In this case, by subtracting costs and a reasonable profit of the last internal stage from market price, tansfer price can be determined.

Apart from the cost-based methods and transfer prices based on open market prices, a third way is negotiation among group entities like independent parties. The transfer price resulting from such
negotiations is equally acceptable from a business economics point of view.

THE ARM'S LENGTH PRINCIPLE

Prices set for transactions between group entities should - for tax purposes - be derived from prices which would have been applied by unrelated parties in similar transactions under similar conditions in the open market.

This is the so-called "dealing at arm's length" principle, which is the international standard for transfer pricing matters.

PRACTICE AMONG MNEs

In 1992 the International Bureau of Fiscal Documentation sent a questionnaire on the use of transfer pricing methods to about 150 large MNEs in 20 countries.
Seventy answers from 12 countries provided useful information.
Main sectors of activity were: oil and chemicals, electronics, finance, forestry, metals, pharmaceuticals, retailing and textiles.

Per country the following pattern appears:
Belgium:
Germany:
large majority uses cost-plus/resale price,
goods and services: if CUP is available it is used, but nevertheless the majority applies cost-plus or
resale price;
intangibles: majority applies CUP.

CUP: Comparable Uncontrolled Price

Netherlands;
goods and services: almost all use cost plus or
resale price;
intangibles: great majority use cost-plus/resale
price, some CUP or mixed methods.

Sweden: majority applies CUP.
Switzerland:
large majority use cost-plus/resale price,

U.K. : goods: some CUP, other cost-plus/resale minus;
services: cost-plus;
intangibles: CUP.

U.S.A.:
goods and services: a clear majority applies costplus/resale
price;
intangibles: equally divided over CUP, cost-plus
and other methods.

The surevey reveals a clear dominance of the cost-plus and resale price methods in the case of goods and services. CUP is better represented with respect to intangibles. Some respondents indicated that internal CUPs were used: prices charged by group members to non-related clients.

Reference
http://archivo.cepal.org/pdfs/1995/S9500513.pdf

Updated 2 May 2016, 8 Dec 2011

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