title: Evaluating and improving demand forecast practices for B2B and B2C sectors
metadata.name: dc.contributor.advisor
metadata.value: Smirnova, Maria M.
metadata.lang: -
metadata.name: dc.contributor.advisor
metadata.value: Hallikas, Jukka
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Emelyanova, Anna
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2014-03-22T09:46:55Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2014-03-22T09:46:55Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2011
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/893
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1)	What are the main differences and similarities in demand planning between B2B and B2C sectors? 2)	How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: English
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: Master in Information Technologies and Innovation Management, Graduate School of   Management, Saint Petersburg State University
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: supply chain management
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: demand techniques
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: demand information sharing
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: demand forecasting
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: demand practices in B2B and B2C sector
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Evaluating and improving demand forecast practices for B2B and B2C sectors
metadata.lang: en_GB
metadata.name: dc.title.alternative
metadata.value: Подходы к оценке и совершенствованию методов прогнозирования спроса в промышленном и потребительском секторах
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Thesis
metadata.lang: en_GB
metadata.name: dc.contributor.altauthor
metadata.value: Емельянова, А.
metadata.lang: -
resources.filename: Emelyanova_Advisor's Reference.doc
resources.url: https://dspace.spbu.ru/bitstream/11701/893/1/Emelyanova_Advisor%27s%20Reference.doc
resources.format: Microsoft Word
resources.size: 45 kB
resources.filename: Emelyanova_Referee's Review.doc
resources.url: https://dspace.spbu.ru/bitstream/11701/893/2/Emelyanova_Referee%27s%20Review.doc
resources.format: Microsoft Word
resources.size: 44,5 kB