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PRICING ANALYTICS WITH R
Price optimization through quantitative methods of analysis allows companies to make informed decisions about effective pricing policy. By using data instead of assumptions, decision makers can determine the "right" price for their product or service in order to attract customers thus increasing sales revenue, profit or profitability. This monograph focuses on certain practical problems related to pricing research and price optimization solutions. Beyond the theoretical perspectives that are ...
Price optimization through quantitative methods of analysis allows companies to make informed decisions about effective pricing policy. By using data instead of assumptions, decision makers can determine the "right" price for their product or service in order to attract customers thus increasing sales revenue, profit or profitability. This monograph focuses on certain practical problems related to pricing research and price optimization solutions. Beyond the theoretical perspectives that are offered by a great number of scientific publications in the field of marketing pricing, this study systematizes concepts, methods and tools for practical implementation in an open source software environment for data analysis, statistical calculations and graphs. The study covers issues related to the fundamental theory of pricing that can be empirically evaluated, such as price awareness, price elasticity, willingness to pay and price response function, price optimization as well as certain issues of price differentiation and customized pricing. Hopefully, the study will be of particular importance to practitioners searching for affordable methods and tools to support optimal pricing decisions.
CONTENTS
Introduction 9
1. On the meaning of pricing analytics 12
1.1. Differentiation of concepts 12
1.2. Why is an analytical approach to pricing important? 15
2. The impact of prices on demand 17
2.1. Price salience and price awareness 18
2.1.1. Evaluation of price salience 18
2.1.2. Evaluation of price awareness 21
2.2. Price elasticity of demand 22
2.2.1. Approaches to estimating price elasticity 26
2.2.2. Data sources for estimating price elasticity 28
2.2.3. Models for estimating price elasticity 38
2.2.4. Choosing an adequate model for estimating price elasticity 41
2.3. Customers’ willingness to pay 48
2.3.1. Assumption for normal distribution of willingness to pay 50
2.3.2. Assumption for uniform distribution of willingness to pay 55
2.3.3. Assumption for logistic distribution of willingness to pay 56
2.4. Estimation of stated willingness to pay 60
2.4.1. The contingent valuation method 62
2.4.2. The Gabor-Granger method 85
2.4.3. The Van Westendorp method (PSM) 95
2.4.4. The Choice-based conjoint analysis (CBC) 107
2.5. Price response function 124
2.5.1. A deterministic approach to evaluating the price response function 127
2.5.2. Estimating price response function by Bootstrapping 134
3. Price optimization 136
3.1. A generic price optimization model 145
3.2. Optimal price with the linear price-response function 146
3.3. Optimal price with the isoelastic price-response function 147
3.4. Optimal price with the logit price-response function 149
4. Customized pricing 153
4.1. Price differentiation 156
4.2. Pricing structures 160
4.3. Optimal customized pricing 164
4.3.1. B2B purchasing decision making process 165
4.3.2. Required data 166
4.3.3. A B2B custom pricing model 166
4.3.4. The prospect theory and framing effects in purchase decision making 169
4.3.5. Prototyping the custom pricing model 173
4.4. Nonlinear pricing 179
4.4.1. Principles of bunde pricing 180
4.4.2. Optimal bundle pricing 183
Conclusion 191
References 192
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A COMBINED APPROACH TO EXAMINING FOREIGN TRADE IN SERVICES
TABLE OF CONTENTS
INTRODUCTION 9
CHAPTER ONE. THEORETICAL AND APPLIED ASPECTS OF INTERNATIONAL TRADE IN SERVICES 13
1. Specifics of international trade in services 13
2. Main factors stimulating international trade in services 16
3. The determinants in the empirical research of trade in services by using the Gravity model 20
4. Classification and reporting of international trade in services 26
CHAPTER TWO. CONCEPTUALIZATION AND APPROBATION OF THE GRAVITY MODEL IN TRADE IN SERVICES ...
TABLE OF CONTENTS
INTRODUCTION 9
CHAPTER ONE. THEORETICAL AND APPLIED ASPECTS OF INTERNATIONAL TRADE IN SERVICES 13
1. Specifics of international trade in services 13
2. Main factors stimulating international trade in services 16
3. The determinants in the empirical research of trade in services by using the Gravity model 20
4. Classification and reporting of international trade in services 26
CHAPTER TWO. CONCEPTUALIZATION AND APPROBATION OF THE GRAVITY MODEL IN TRADE IN SERVICES WITH R 30
1. The gravity model and its application 30
2. Methodology for examining the determinants of international trade 32
2.1. Model specification and parameter estimation method 32
2.2. Sources of information and data processing 36
2.3. Description of the dependent and independent variables 37
3. Assessment of the impact of factors on the export and import of services of Bulgaria, Romania and Croatia 39
3.1. Results of the gravity model of trade in services of Bulgaria 39
3.2. Results of the gravity model of trade in services of Romania 42
3.3. Results of the gravity model of trade in services of Croatia 45
CHAPTER THREE. MONOLATERAL STRUCTURAL ANALYSIS OF TRADE IN SERVICES 49
1. Structural analysis of Bulgaria’s foreign trade 49
2. Structural analysis of Romania's foreign trade 63
3. Structural analysis of Croatia's foreign trade 77
CHAPTER FOUR. ANALYSIS AND EVALUATION OF THE TREND IN TRADE IN SERVICES OF BULGARIA, ROMANIA AND CROATIA (2000 - 2020) 92
1. Index analysis and evaluation of the trend in trade in services based on balance of payments data of Bulgaria, Romania and Croatia (2000 - 2020) 92
1.1. Index analysis methodology of balance of payments positions 92
1.2. Approbation of the methodology for index analysis and evaluation of the trend in trade in services of Bulgaria, Romania and Croatia (2000 - 2020) 97
2. Quality indicators analysis in the dynamics of the balance of services in Bulgaria, Romania and Croatia (2000 - 2020) 121
2.1. Possible indicators for quality assessment in the dynamics of the balance of services 121
2.2. Approbation of quality indicators in the dynamics of the balance of services in Bulgaria, Romania and Croatia (2000 - 2020) 122
CHAPTER FIVE. TRADE INTENSITY ANALYSIS AND ASsessment of FOREIGN TRADE POTENTIAL 128
1. Intensity indicators of trade in services and assessment of foreign trade potential 128
2. Bilateral assessment of export and import potentials 131
3. Analysis of the intensity of import and export of services by partner countries 145
CONCLUSION 156
APPENDICES 158
Appendix 1. Functions of Gravity package 158
Appendix 2. List of countries included in the Gravity model 159
Appendix 3. List of countries with a common official or spoken language included in the Gravity model 160
Appendix 4. Potential for increasing the export / import of services 161
Appendix 5. Growth and the lead–lag relatioship of exports and imports of services by type and countries for the period 2000-2020 based on 2000 162
REFERENCES 164
Abstract
This paper examines issues related to international trade in services and is exclusively empirical. The foreign trade flows of Bulgaria, Romania and Croatia are the object of study and the subject of study - their dynamics and structure for the period 2000-2020. Theoretical and applied aspects of the research involve specifics of international trade in services and the main factors contributing to its growth. The Gravity model is used in order to examine how certain determinants affect the volume of exports and imports with R programming language in RStudio Integrated Development Environment. On the basis of balance of payments data and a set of indicators, the dynamics in the volume and structure of exports and imports is analysed and the potential for expanding trade in services of the three countries is assessed. It is concluded that the market size has a positive effect on trade, while geographical distance negatively affects trade. EU membership contributes to the greatest extent to expanding the trade of Romania, to a lesser extent – of Bulgaria, and almost to no extent – of Croatia.
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MARKET BASKET ANALYSIS USING R
Introduction 9
1. Concept and Tools 13
1.1. Defining the problem 13
1.2. Conceptual framework 15
1.3. Basic concepts 17
1.4. Logical data model 18
1.5. Exploratory analysis of sales transactional data 21
1.6. Transaction-class objects 25
1.7. Descriptive analysis of sales transactional data 27
1.8. Market basket analysis metrics 32
1.9. Association rule mining 40
1.9.1. Identifying common subsets 41
1.9.2. Identifying strong association rules 47
1.10. Visual analysis of ...
Introduction 9
1. Concept and Tools 13
1.1. Defining the problem 13
1.2. Conceptual framework 15
1.3. Basic concepts 17
1.4. Logical data model 18
1.5. Exploratory analysis of sales transactional data 21
1.6. Transaction-class objects 25
1.7. Descriptive analysis of sales transactional data 27
1.8. Market basket analysis metrics 32
1.9. Association rule mining 40
1.9.1. Identifying common subsets 41
1.9.2. Identifying strong association rules 47
1.10. Visual analysis of market basket 51
1.10.1. Visualization of absolute and relative frequency 53
1.10.2. Visualization of market basket analysis metrics 54
1.10.3. Visualization of association rules 60
2. Big Data Market Basket Analysis 69
2.1. Analytical approach 69
2.2. Data 72
2.2.1. Import and conversion 72
2.2.2. Overview of transactions, assortment items and product groups 73
2.3. Big Data exploratory data analysis 74
2.4. Generating rules and making recommendations 81
2.5. Visual analysis and interpretation 89
2.6. Extended market basket analysis taking contribution margin into account 98
Conclusion 105
References 109
The digital transformation of business, the emerging customer-centric business models as well as advanced tools and techniques for analysis imply the need for a marketing culture focused on data and analysis. This monograph explores and presents approaches, algorithms, techniques and procedures for analyzing the market basket with data from sales transactions. Although the statement is based on solid theoretical sources, the main emphasis is placed on the methodology and extraction of patterns from large datasets by using association rules. Guided by the understanding of the leading role of transactional data from sales transactions in mining personalized information and patterns of customer behaviour, our goal is to provide the reader with specific practical guidelines and reproducible operating procedures for market basket analysis with the R programming language. The overall approach of the study is based on specific examples, work instructions, program code and guidelines for interpreting the results in the context of supporting marketing decisions in commercial enterprises.
