A Dynamic Growth Model for Flows of Foreign Direct Investment

In this work, we for the first time study the dynamic flows of the foreign direct investment (FDI) with a dynamic growth theory. We define the FDI flow as a process which transmits throughout a given social system by way of diverse communication channels. In model formulation, seven assumptions are thus proposed and the foreign capital policy of the host country is considered as an external influence; in addition, the investment policy of the investing country is modeled as an internal influence. Classification of influences is mainly according to the operational strategy as well as the consideration of economical/financial factors. The dynamic model of FDI flow is a differential equation which is solved numerically and verified with collected realistic data. Application of the developed model to explore, taking the electronics industry in Taiwan as an example, Taiwanese direct investment (TDI) in China (i.e. FDI flows from Taiwan to China) since 2001 is conducted. Our preliminary results successfully account for the dynamics of FDI flow for different amount of TDI outflows. It is found that the internal influence dominates the growth of TDI flow from Taiwan to China during 2001-2006.Foreign direct investment, dynamic flow theory, growth model, and numerical simulation

Sebaran Dan Peramalan Mahasiswa Baru Pendidikan Matematika Universitas Muhammadiyah Purwokerto Dengan Metode TIME Invariant Fuzzy TIME Series

Penelitian ini bertujuan untuk mengetahui sebaran jumlah mahasiswa Pendidikan Matematika dari tahun 2005 sampai 2015 berdasarkan asal kabupaten dan meramalkan jumlah mahasiswa Pendidikan Matematika. Langkah pertama yang dapat dilakukan yaitu dengan sebaran mahasiswa berdasarkan Kabupaten se-Jawa dan Kabupaten di luar pulau Jawa menggunakan metode Hierarchical Clustering Analysis. Melalui hasil sebaran tersebut akan memberikan gambaran kepada program studi Pendidikan Matematika serta pihak Universitas untuk mengambil kebijakan dan melakukan penajaman pada kabupaten-kabupaten tersebut serta melakukan ekspansi maupun promosi guna meningkatkan jumlah calon mahasiswa baru. Langkah kedua yaitu prediksi jumlah calon mahasiswa baru menggunakan metode Time Invariant Fuzzy Time Series. Dalam hal ini baik program studi Pendidikan Matematika dan Pendidikan Guru SD dan pihak Universitas dapat mengambil kebijakan yang tepat terkait penerimaan mahasiswa baru berdasarkan sebaran dan prediksi tersebut di atas. Pada peramalan pendaftaran dengan 6 himpunan fuzzy, pada tahun 2016-2020 diramalkan jumlah mahasiswa pendidikan matematika dan PGSD Universitas Muhammadiyah Purwokerto sebesar 389, 459, 427, 497, dan 465 mahasiswa, dengan error ramalan 47,5 %

Using Online Search Data to Forecast New Product Sales

This dissertation focuses on online search as a measure of consumer interest. Internet use is at an all-time high in the United States, and according to the Pew Internet & American Life Project, 91% of Internet users use search engines to find information. Consumers' choices of search terms are not well understood. However, we argue that people will focus their searches on terms that are of interest to them. As such, data on the search terms used can provide valuable measures and indicators of consumer interest in a market. This can be particularly valuable to managers in search of tools to gauge potential product interest in a new product launch. In this research, we develop a model of pre-launch search activity. We find search term usage to follow rather predictable patterns in the pre-launch and post-launch periods. As such, we extend our pre-launch search model to link pre-release search behavior to release-week sales - providing a very valuable forecasting tool. We illustrate this approach in the context of motion pictures. Our modeling framework links search activity to sales and incorporates product characteristics. Our results indicate consistent patterns of search over time and systematic relationships between search volume, sales, and product attributes. We extend our model by studying the role of advertising. This allows us to better understand the relationship between advertising and online search activity and also allows us to compare the forecasting performances of each of the two approaches. We find that search data offers significant forecasting power in opening-weekend box-office revenues. We further find that advertising, combined with search data, offers improved forecasting ability

“I will survive”: online streaming and the chart survival of music tracks

Digital streaming has had a profound effect on the commercial music sector and now accounts for 80% of industry revenues in the United States. This study investigates the consumption of music on digital streaming platforms by analyzing the factors affecting the chart survival of individual music tracks. Our data are taken from the Spotify Global Top 200 between January 2017 and January 2020, containing observations on 3,007 unique tracks by 642 artists over 1,087 days. We identify a number of unique consumption traits applicable to online streaming services, which we use to explain variations in chart longevity. We find a positive association between the amount of time a track spends in the chart and the involvement of a major label. We also find that the level of competition from other chart entries, as well as some elements related to the pattern of diffusion, associates significantly with the likelihood of chart survival. The study highlights several important managerial implications for key industry stakeholders

Dynamic model for the multiproduct inventory optimization with multivariate demand

IInventory Policies for the industry are a need to its profitability and to provide adequate service to the clients. The final stage in the internal logistic of the supply chain, the storage and the final disposal, must have a correct planning, but this requires a correct management of the final products demand. New models based on Bayesian techniques are proposed in this thesis in order to do forecasts with few data and for short periods. Also, new Inventory models, and the respective optimization for a type of industry that has a storage center and final supply of its products. The work is divided in two phases. The first phase will provide a better form to forecast, and the second, the form to do optimization, to give to the industry adequate quantities to order, save, and transport to fulfill service to the clients.Resumen: Las políticas de inventario para la industria son una necesidad para su rentabilidad y para proveer un servicio adecuado a los clientes. Es necesario buscar herramientas que faciliten a la industria una buena planeación en la etapa final de la logística interna de la cadena de suministro, tanto en el almacenamiento, como en la disposición final, pero esto requiere un manejo adecuado de la demanda de los productos finales. En ésta Tesis Doctoral se proponen nuevos modelos basados en técnicas bayesianas, con el fin de hacer pronósticos con pocos datos y a corto plazo. También, se proponen Modelos de inventario y su respectiva optimización, para un tipo de industria que tenga un centro de almacenamiento y distribución final de sus productos. El trabajo se divide en dos fases. La primera fase proporcionará una mejor forma de predecir, y la segunda, la forma de hacer la optimización de modelos de inventario multiproducto, para dar a la industria de las cantidades adecuadas para ordenar, guardar y transporte para cumplir con el servicio a los clientes.Doctorad