Applications of augmented reality for sales in apparel industry in Russia

The sustainable growth of video interactivity technologies on different platforms in the lasts years opens good prospects for augmented reality technology adoption on different markets. In the end of 2011 there was an improvement in technology which allows building the 3D model of human body. Such an improvement could be used in apparel industry. The main goal of the study is to understand the level of acceptance of augmented reality as a technology on the Russian apparel market. For a more accurate investigation, a new model accounting for augmented reality characteristics, as well as for similarities and differences between online and offline customer behavior in apparel industry, was developed. As a result of the survey, the weights of different purchase intention factors for Russian consumer were found, and the information about Russian consumers’ preferences towards the augmented reality features in apparel market, especially in fitting time, real-time interaction and fitting quality peculiarities, was presented.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Development of sales invoicing process in industrial services

The objective of this Master’s thesis is to find ways to streamline the invoicing process of the case company. In order to streamline the process, the bottlenecks and development areas of the present invoicing process needs to be identified. The bottlenecks are based on interviews made to personnel. The thesis also offers solutions to overcome the identified bottlenecks. The problem is the slowness of the invoicing process which should get rid off. The slow invoicing process causes delays in obtaining payments. There are many reasons for the slowness and inefficiency of the invoicing process. One of the biggest reasons is that the information systems are not deployed entirely. It causes additional work for everyone. Practices with the customers affect also to the smooth flow of invoicing. The contracts determine when the customer can be invoiced but also work approvals, missing work orders and customer’s own invoicing basis slow the process. The fastest and cheapest solution is to deploy the systems better and do things correctly. Thus duplicated work would decrease and resources would be saved. The work allocation should be modified and the practices with customer should be influenced too. In the future the meaning of IT should be highlighted and new devices exploited.

Ocorrência de auto-incompatibilidade homomórfica em Mitracarpus longicalyx E. B. Souza & M. F. Sales (Rubiaceae - Spermacoceae)

O estudo da biologia reprodutiva de Mitracarpus longicalyx E.B. Souza & M.F. Sales foi realizado durante os meses de setembro a dezembro de 2004, em Feira de Santana, BA, Brasil. Esta espécie é uma erva anual ocorrente em áreas de caatinga, florescendo de junho a dezembro. As inflorescências são glomérulos com 90 flores em média, que apresentam corola hipocrateriforme, medindo 4-5 mm de comprimento e coloração branca, sendo visitadas e polinizadas por borboletas da espécie Hemiargus hanno hanno (Stoll, 1790) (Lycaenidae). As flores são protândricas, com duração da fase estaminada de três dias e da fase pistilada de cinco dias. Não ocorre sobreposição das duas fases na mesma flor, mas podem ocorrer flores em diferentes fases na mesma inflorescência. Polinizações experimentais indicaram que M. longicalyx é uma espécie auto-incompatível não agamospérmica, com produção natural de frutos elevada (97,8%) na população estudada. A frutificação também foi elevada nas polinizações cruzadas manuais (82,3%), não ocorrendo frutificação nas polinizações manuais geitonogâmicas. Tubos polínicos provenientes de polinizações cruzadas alcançaram o ovário dentro de 24 horas, enquanto que grãos de pólen provenientes de autopolinização não germinaram ou, quando germinaram, não penetraram as papilas estigmáticas. Os resultados indicam que M. longicalyx possui auto-incompatibilidade homomórfica, possivelmente do tipo esporofítica, atuando em adição à protandria no impedimento da autofertilização. Auto-incompatibilidade homomórfica é muito rara nas Rubiaceae, uma família com abundante ocorrência de auto-incompatibilidade heteromórfica.

Benefits of sales force automation to salespeople and to their customers in business-to-business markets

This study applied qualitative case study method for solving what kind of benefits salespeople and their customers perceived to gain when sales reps used a specific sales force automation tool, that defined the values and identified segment that best fit to each customer. The data consisting of four interviews was collected using semi-structured individual method and analyzed with thematic analysis technique. The analysis revealed five salespeople perceived benefits and four customer perceived benefits. Salespeople perceived benefits were improvements in customer knowledge, guidance of sales operations, salesperson-customer relationship building, time management and growing performance. Customer perceived benefits were information transmission, improved customer service, customer-salesperson relationship building and development of operations, which of the last was found as a new previously unrecognized customer benefit.

Integrating Use of Customer Information Throughout Multiple Sales Channels to Create Customer Competence

Customer knowledge management (CKM) practices enable organizations to create customer competence with systematic use of customer information that is integrated throughout the organization. Nonetheless, organizations are not able to fully exploit the vast amount of data available. Previous research on use of customer information is limited especially in a multichannel environment. The aim of this study was to identify the main obstacles for utilizing customer information efficiently across multiple sales channels. The study was conducted as a single case study in order to gain deeper understanding of the research problem. The empirical findings indicate that lack of CKM practices and a common goal are major challenges obstructing effective utilization of customer information. Furthermore, decentralized organizational structure and insufficient analytical skills create obstacles for information sharing and capabilities to process information and create new knowledge. The implications of the study suggest that in order to create customer competence organizations should shift their focus from technology to the organizational factors affecting use of information and implement CKM practices throughout the organization.

Customer orientation of sales personnel: Implications for service quality

Prior customer orientation research has concentrated mainly on studying the economical potential of customer orientation to companies. Service quality research instead has concentrated on emphasizing the evaluation of service quality from the customer’s perspective. This means that the service providers lack important information regarding customer orientation and service quality they would need for managerial purposes such as selecting and training employees. Therefore, there is an emerging need to study how customer orientation and service quality relate to company processes, policies and employees, and this study answers to those calls. The objective of this study was to examine what is the role of sales personnel’s’ customer orientation in quality of service delivery and what features support the development of customer orientation among sales personnel. Also the components customer orientation were studied extensively in order to understand how they relate to service quality. The empiric part of the study was conducted as a qualitative research by interviewing seven sales people from operative, tactical and strategic levels of the case corporation in order to get a broader view for customer orientation. The findings propose that both organizational factors and individual factors are affecting customer orientation construct inseparably. Organizational factors are bundled in this study under standards, support and systems, whereas individual factors are formed of employees’ personal attributes, motivation and self-perceived decision making authority. The findings suggest that in the service delivery process at an operative level, customer orientation appears largely in the employees’ individualistic characteristics. Their social and technical skills and motivation to serve customers are the most identifiable factors for customer orientation and consequently, quality service. However, organizational standards, support and systems are strongly dictating the frames the operative sales people operate in, having an influence on how the employees are experiencing their decision making authority and in the end, customer orientation. When looking at the service delivery process at tactical and strategic levels, customer orientation is affecting mainly in the organizational constructs through setting standards, support and systems. However, tactical and strategic level employees influence the operative level through individual customer orientation components as well. The findings indicate that their emotion and personal interaction skills are affecting the overall service delivery process mainly through supervisor support and motivation of the operative level employees. Based on this study it can be argued that an organization can operate as a facilitator and create certain frames for customer oriented sales behavior through standards, support and systems. However, as the impact of individual customer orientation factors on sales people’s service quality seems decisive, from an organizational perspective it puts pressures on the recruitment.

Forecasting financial weather - can we foresee market sentiment? Spectrum of stock price behavior - NYSE case study

The desire to create a statistical or mathematical model, which would allow predicting the future changes in stock prices, was born many years ago. Economists and mathematicians are trying to solve this task by applying statistical analysis and physical laws, but there are still no satisfactory results. The main reason for this is that a stock exchange is a non-stationary, unstable and complex system, which is influenced by many factors. In this thesis the New York Stock Exchange was considered as the system to be explored. A topological analysis, basic statistical tools and singular value decomposition were conducted for understanding the behavior of the market. Two methods for normalization of initial daily closure prices by Dow Jones and S&P500 were introduced and applied for further analysis. As a result, some unexpected features were identified, such as a shape of distribution of correlation matrix, a bulk of which is shifted to the right hand side with respect to zero. Also non-ergodicity of NYSE was confirmed graphically. It was shown, that singular vectors differ from each other by a constant factor. There are for certain results no clear conclusions from this work, but it creates a good basis for the further analysis of market topology.

A Phase Model for Building a Customer Value Based Sales Tool – Case Mining and Metals Industry

The objective of this research is to observe the state of customer value management in Outotec Oyj, determine the key development areas and develop a phase model with which to guide the development of a customer value based sales tool. The study was conducted with a constructive research approach with the focus of identifying a problem and developing a solution for the problem. As a basis for the study, the current literature involving customer value assessment and solution and customer value selling was studied. The data was collected by conducting 16 interviews in two rounds within the company and it was analyzed by coding openly. First, seven important development areas were identified, out of which the most critical were “Customer value mindset inside the company” and “Coordination of customer value management activities”. Utilizing these seven areas three functionality requirements, “Preparation”, “Outotec’s value creation and communication” and “Documentation” and three development requirements for a customer value sales tool were identified. The study concluded with the formulation of a phase model for building a customer value based sales tool. The model included five steps that were defined as 1) Enable customer value utilization, 2) Connect with the customer, 3) Create customer value, 4) Define tool to facilitate value selling and 5) Develop sales tool. Further practical activities were also recommended as a guide for executing the phase model.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Net working capital estimation model in project business

The objective of this Master’s thesis is to develop a model which estimates net working capital (NWC) monthly in a year period. The study is conducted by a constructive research which uses a case study. The estimation model is designed in the need of one case company which operates in project business. Net working capital components should be linked together by an automatic model and estimated individually, including advanced components of NWC for example POC receivables. Net working capital estimation model of this study contains three parts: output template, input template and calculation model. The output template gets estimate values automatically from the input template and the calculation model. Into the input template estimate values of more stable NWC components are inputted manually. The calculate model gets estimate values for major affecting components automatically from the systems of a company by using a historical data and made plans. As a precondition for the functionality of the estimation calculation is that sales are estimated in one year period because the sales are linked to all NWC components.