β-Citronellol, an alcoholic monoterpene with inhibitory properties on the contractility of rat trachea

β-Citronellol is an alcoholic monoterpene found in essential oils such Cymbopogon citratus (a plant with antihypertensive properties). β-Citronellol can act against pathogenic microorganisms that affect airways and, in virtue of the popular use of β-citronellol-enriched essential oils in aromatherapy, we assessed its pharmacologic effects on the contractility of rat trachea. Contractions of isolated tracheal rings were recorded isometrically through a force transducer connected to a data-acquisition device. β-Citronellol relaxed sustained contractions induced by acetylcholine or high extracellular potassium, but half-maximal inhibitory concentrations (IC50) for K+-elicited stimuli were smaller than those for cholinergic contractions. It also inhibited contractions induced by electrical field stimulation or sodium orthovanadate with pharmacologic potency equivalent to that seen against acetylcholine-induced contractions. When contractions were evoked by selective recruitment of Ca2+ from the extracellular medium, β-citronellol preferentially inhibited contractions that involved voltage-operated (but not receptor-operated) pathways. β-Citronellol (but not verapamil) inhibited contractions induced by restoration of external Ca2+ levels after depleting internal Ca2+ stores with the concomitant presence of thapsigargin and recurrent challenge with acetylcholine. Treatment of tracheal rings with L-NAME, indomethacin or tetraethylammonium did not change the relaxing effects of β-citronellol. Inhibition of transient receptor potential vanilloid subtype 1 (TRPV1) or transient receptor potential ankyrin 1 (TRPA1) receptors with selective antagonists caused no change in the effects of β-citronellol. In conclusion, β-citronellol exerted inhibitory effects on rat tracheal rings, with predominant effects on contractions that recruit Ca2+ inflow towards the cytosol by voltage-gated pathways, whereas it appears less active against contractions elicited by receptor-operated Ca2+ channels.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

Esimiesten muuttuvat osaamistarpeet media- ja kustannusalan murroksessa

Organisaatioiden toimintaympäristö on muuttunut ratkaisevasti ja muutos jatkuu. Muutok-sen kiihtyvä nopeus, asioiden epävarmuus ja kompleksisuus aiheuttavat uudenlaisia haas-teita työelämälle, osaamistarpeiden ennakoinnille ja tulevaisuuden suunnittelulle. Esi-miesosaaminen vaikuttaa merkittävästi siihen, miten hyvin organisaatioissa pystytään hyö-dyntämään sen muuta inhimillistä pääomaa ja tämä tutkimus osallistuu keskusteluun siitä, millä tavalla esimiesosaamisen tulisi kehittyä, jotta se pystyy vastaamaan käynnissä ole-vaan yhteiskunnalliseen, sosiaaliseen ja teknologiseen muutokseen. Tutkimuksen tavoit-teena on ennakoida digitaalisen murroksen keskellä olevan media- ja kustannusalan orga-nisaation esimiesosaamisessa tarvittavia muutoksia. Tutkimus on luonteeltaan laadullinen ja primääritutkimusaineisto koostuu kohdeorganisaatiossa esimiesten, toimitusjohtajan ja henkilöstöpäällikön haastatteluista. Tutkimuksen mukaan tulevaisuudessa tarvittavat esimiesosaamiset eivät merkittävästi eroa tämän päivän paradigman mukaisista osaamisista. Monien osaamisten merkitys kuitenkin korostuu. Esimiesten ja muiden työntekijöiden osaamisten nähdään lähestyvän toisiaan ja tulevaisuudessa rajat esimiesten ja tiimiläisten osaamistarpeiden välillä vähenevät entises-tään. Esimiestyössä monet osaamistarpeet, kuten esimerkiksi epävarmuuden sietokyky, kuitenkin korostuvat. Esimiehen merkittävänä tehtävänä nähdään jatkossa entistä vah-vemmin vastuunkantaminen työyhteisössä.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

Utilizing analytic modelling process in industrial retail context

Nykypäivän monimutkaisessa ja epävakaassa liiketoimintaympäristössä yritykset, jotka kykenevät muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkittävää kilpailuetua. Ennustavan analytiikan hyödyntäminen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekijöitä, joiden avulla he pystyvät erottumaan kilpailijoistaan. Ennustavan analytiikan hyödyntäminen osana päätöksentekoprosessia mahdollistaa ketterämmän, reaaliaikaisen päätöksenteon. Tämän diplomityön tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-elämän loppukäyttäjän näkökulmasta ja hyödyntää tätä mallinnusprosessia diplomityön tapaustutkimuksen yritykseen. Teoreettista mallia hyödynnettiin asiakkuuksien mallintamisessa sekä tunnistamalla ennakoivia tekijöitä myynnin ennustamiseen. Työ suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Venäjällä ja Balteissa. Tämä tutkimus on määrällinen tapaustutkimus, jossa tärkeimpänä tiedonkeruumenetelmänä käytettiin tapausyrityksen transaktiodataa. Data työhön saatiin yrityksen toiminnanohjausjärjestelmästä.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Trust Embedded Open Innovation: Human-Centricity in the Financial

Globalization and interconnectedness in the worldwide sphere have changed the existing and prevailing modus operandi of organizations around the globe and have challenged existing practices along with the business as usual mindset. There are no rules in terms of creating a competitive advantage and positioning within an unstable, constantly changing and volatile globalized business environment. The financial industry, the locomotive or the flagship industry of global economy, especially, within the aftermath of the financial crisis, has reached a certain point trying to recover and redefine its strategic orientation and positioning within the global business arena. Innovation has always been a trend and a buzzword and by many has been considered as the ultimate answer to any kind of problem. The mantra Innovate or Die has been prevailing in any organizational entity in a, sometimes, ruthless endeavour to develop cutting-edge products and services and capture a landmark position in the market. The emerging shift from a closed to an open innovation paradigm has been considered as new operational mechanism within the management and leadership of the company of the future. To that respect, open innovation has been experiencing a tremendous growth research trajectory by putting forward a new way of exchanging and using surplus knowledge in order to sustain innovation within organizations and in the level of industry. In the abovementioned reality, there seems to be something missing: the human element. This research, by going beyond the traditional narratives for open innovation, aims at making an innovative theoretical and managerial contribution developed and grounded on the on-going discussion regarding the individual and organizational barriers to open innovation within the financial industry. By functioning across disciplines and researching out to primary data, it debunks the myth that open innovation is solely a knowledge inflow and outflow mechanism and sheds light to the understanding on the why and the how organizational open innovation works by enlightening the broader dynamics and underlying principles of this fascinating paradigm. Little attention has been given to the role of the human element, the foundational pre-requisite of trust encapsulated within the precise and fundamental nature of organizing for open innovation, the organizational capabilities, the individual profiles of open innovation leaders, the definition of open innovation in the realms of the financial industry, the strategic intent of the financial industry and the need for nurturing a societal impact for human development. To that respect, this research introduces the trust-embedded approach to open innovation as a new insightful way of organizing for open innovation. It unveils the peculiarities of the corporate and individual spheres that act as a catalyst towards the creation of productive open innovation activities. The incentive of this research captures the fundamental question revolving around the need for financial institutions to recognise the importance for organizing for open innovation. The overarching question is why and how to create a corporate culture of openness in the financial industry, an organizational environment that can help open innovation excel. This research shares novel and cutting edge outcomes and propositions both under the prism of theory and practice. The trust-embedded open innovation paradigm captures the norms and narratives around the way of leading open innovation within the 21st century by cultivating a human-centricity mindset that leads to the creation of human organizations, leaving behind the dehumanization mindset currently prevailing within the financial industry.

Troponin I serum levels predict the need of dialysis in incident sepsis patients with acute kidney injury in the intensive care unit

Abstract Introduction: Sepsis, an extremely prevalent condition in the intensive care unit, is usually associated with organ dysfunction, which can affect heart and kidney. Objective: To determine whether the cardiac dysfunction and the Troponin I forecast the occurrence of acute renal failure in sepsis. Methods: Cardiac dysfunction was assessed by echocardiography and by the serum troponin I levels, and renal impairment by AKIN criteria and the need of dialysis. Twenty-nine patients with incident sepsis without previous cardiac or renal dysfunction were enrolled. Results and Discussion: Patients averaged 75.3 ± 17.3 years old and 55% were male. Median APACHE II severity score at ICU admission was 16 (9.7 - 24.2) and mortality rate in 30 days was 45%. On the fifth day, 59% had ventricular dysfunction. Troponin serum levels on day 1 in the affected patients were 1.02 ± 0.6 ng/mL compared with 0.23 ± 0.18 ng/mL in patients without heart dysfunction (p = 0.01). Eighteen out of 29 patients (62%) underwent renal replacement therapy (RRT) and the percent of patients with ventricular dysfunction who required dialysis was higher (94% vs. 16%, p = 0.0001). Values of troponin at day 1 were used to develop a ROC curve to determine their ability to predict the need of dialysis. The area under the curve was 0.89 and the cutoff value was 0.4 ng/mL. Conclusion: We found that an elevation in serum troponin levels, while guarding a relationship with ventricular dysfunction, can be a precious tool to predict the need for dialysis in sepsis patients.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

Erikoistilanteiden huomiointi päivittäistavarakaupan myymälätäydennyksessä

Päivittäistavarakauppa toimialana vaatii hektisyytensä, volyymien suurten vaihtelujen ja tuotteiden ominaispiirteiden takia nopeaa reagointikykyä toimitusketjun sopeuttamisessa. Tällöin pienikin tarkkuuden parantaminen myyntiennusteessa voi aiheuttaa merkittäviä positiivisia kerrannaisvaikutuksia koko ketjussa. Tässä diplomityössä tutkittiin kahta teemaa: Säätilan ja vähittäismyynnin välistä korrelaatiota, sekä tuotteen kampanjassa olon aiheuttamaa kannibalisointivaikutusta muiden tuotteiden menekkiin. Tutkimus toteutettiin työn tilaajan kannalta merkittäväksi mielletyillä tavararyhmillä historialliseen myynti –, sää- ja kampanjadataan perustuen. Tutkimuksen tuloksena todettiin lämpötilan olevan yksittäinen merkittävin tuotteiden menekkiin vaikuttava sääparametri. Kampanjan aiheuttaman myynnin kannibalisointivaikutuksen havaittiin olevan merkittävintä saman tuotesegmentin sisällä, erityisesti lyhyissä kampanjoissa. Työssä luotiin toimintamallit molempiin tutkittuihin teemoihin ennusteperusteisen tarvesuunnittelujärjestelmän ennustetarkkuuden parantamisen työkaluiksi.

The Dynamic Relationship between Finnish Stock Market and Commodities

Since different stock markets have become more integrated during 2000s, investors need new asset classes in order to gain diversification benefits. Commodities have become popular to invest in and thus it is important to examine whether the investors should use commodities as a part for portfolio diversification. This master’s thesis examines the dynamic relationship between Finnish stock market and commodities. The methodology is based on Vector Autoregressive models (VAR). The long-run relationship between Finnish stock market and commodities is examined with Johansen cointegration while short-run relationship is examined with VAR models and Granger causality test. In addition, impulse response test and forecast error variance decomposition are employed to strengthen the results of short-run relationship. The dynamic relationships might change under different market conditions. Thus, the sample period is divided into two sub-samples in order to reveal whether the dynamic relationship varies under different market conditions. The results show that Finnish stock market has stable long-run relationship with industrial metals, indicating that there would not be diversification benefits among the industrial metals. The long-run relationship between Finnish stock market and energy commodities is not as stable as the long-run relationship between Finnish stock market and industrial metals. Long-run relationship was found in the full sample period and first sub-sample which indicate less room for diversification. However, the long-run relationship disappeared in the second sub-sample which indicates diversification benefits. Long-run relationship between Finnish stock market and agricultural commodities was not found in the full sample period which indicates diversification benefits between the variables. However, long-run relationship was found from both sub-samples. The best diversification benefits would be achieved if investor invested in precious metals. No long-run relationship was found from either sample. In the full sample period OMX Helsinki had short-run relationship with most of the energy commodities and industrial metals and the causality was mostly running from equities to commodities. During the first sub period the number of short-run relationships and causality shrunk but during the crisis period the number of short-run relationships and causality increased. The most notable result found was unidirectional causality from gold to OMX Helsinki during the crisis period.

The Impact of Foreign Direct Investment Inflows on the Economic Growth of Bangladesh. The Roles of Infrastructural Facilities

Foreign direct investment (FDI) inflow has been a key concern for Bangladesh to obtain additional support for the economic development. The Government of Bangladesh continuously competing with other South Asian countries and putting more effort to increase the number of FDI inflows in the country. From the country’s perspective, the constant increasing rate of economic growth shows a positive outcome of FDI inflow. However, the country still not performing up to the mark to pull enough FDI inflows to its potential. Thus, this study discusses about the major determinants and factors affecting FDI inflows in Bangladesh. Among those determinants and factors, infrastructural facility is considered as the most important to affect FDI inflows. FDI inflow is fundamentally depending upon infrastructural facilities to achieve its desire success. Foreign investors take this issue very seriously because based on this they can measure their ease of doing business in the host country. Despite of providing a large market size, due to having weak and lack of infrastructural facilities, Bangladesh is facing trouble in drawing attention of the foreign investors. In order to make the infrastructural facilities happen, it is highly required to organize each of the systems under of it. The body of this study discussed about the weak infrastructures in Bangladesh such as transport and communication, power and energy, education system, and governance services. Improvement in one of these systems cannot provide valuable positive changes on FDI inflows. It requires improvement in all the weak systems to grasp multinational companies and attract foreign investors. On the basis of this research problem, research questions are established. Both qualitative and quantitative methods are used to answer the research questions. Furthermore, several theories have been applied to justify possible scenarios from the research problem. In addition, the history in between Bangladesh, trade liberalization, and FDI inflows is presented briefly.

Forecasting with social media – Using Facebook likes to predict the results of the 2015 Finnish Parliamentary elections

Already one-third of the human population uses social media on a daily basis. The biggest social networking site Facebook has over billion monthly users. As a result, social media services are now recording unprecedented amount of data on human behavior. The phenomenon has certainly caught the attention of scholars, businesses and governments alike. Organizations around the globe are trying to explore new ways to benefit from the massive databases. One emerging field of research is the use of social media in forecasting. The goal is to use data gathered from online services to predict offline phenomena. Predicting the results of elections is a prominent example of forecasting with social media, but regardless of the numerous attempts, no reliable technique has been established. The objective of the research is to analyze how accurately the results of parliament elections can be forecasted using social media. The research examines whether Facebook “likes” can be effectively used for predicting the outcome of the Finnish parliament elections that took place in April 2015. First a tool for gathering data from Facebook was created. Then the data was used to create an electoral forecast. Finally, the forecast was compared with the official results of the elections. The data used in the research was gathered from the Facebook walls of all the candidates that were running for the parliament elections and had a valid Facebook page. The final sample represents 1131 candidates and over 750000 Facebook “likes”. The results indicate that creating a forecast solely based on Facebook “likes” is not accurate. The forecast model predicted very dramatic changes to the Finnish political landscape while the official results of the elections were rather moderate. However, a clear statistical relationship between “likes” and votes was discovered. In conclusion, it is apparent that citizens and other key actors of the society are using social media in an increasing rate. However, the volume of the data does not directly increase the quality of the forecast. In addition, the study faced several other limitations that should be addressed in future research. Nonetheless, discovering the positive correlation between “likes” and votes is valuable information that can be used in future studies. Finally, it is evident that Facebook “likes” are not accurate enough and a meaningful forecast would require additional parameters.

The Impact of Foreign Direct Investment Inflows on the Economic Growth of Bangladesh. The Roles of Infrastructural Facilities

Foreign direct investment (FDI) inflow has been a key concern for Bangladesh to obtain additional support for the economic development. The Government of Bangladesh continuously competing with other South Asian countries and putting more effort to increase the number of FDI inflows in the country. From the country’s perspective, the constant increasing rate of economic growth shows a positive outcome of FDI inflow. However, the country still not performing up to the mark to pull enough FDI inflows to its potential. Thus, this study discusses about the major determinants and factors affecting FDI inflows in Bangladesh. Among those determinants and factors, infrastructural facility is considered as the most important to affect FDI inflows. FDI inflow is fundamentally depending upon infrastructural facilities to achieve its desire success. Foreign investors take this issue very seriously because based on this they can measure their ease of doing business in the host country. Despite of providing a large market size, due to having weak and lack of infrastructural facilities, Bangladesh is facing trouble in drawing attention of the foreign investors. In order to make the infrastructural facilities happen, it is highly required to organize each of the systems under of it. The body of this study discussed about the weak infrastructures in Bangladesh such as transport and communication, power and energy, education system, and governance services. Improvement in one of these systems cannot provide valuable positive changes on FDI inflows. It requires improvement in all the weak systems to grasp multinational companies and attract foreign investors. On the basis of this research problem, research questions are established. Both qualitative and quantitative methods are used to answer the research questions. Furthermore, several theories have been applied to justify possible scenarios from the research problem. In addition, the history in between Bangladesh, trade liberalization, and FDI inflows is presented briefly