Big Data Usage in the Marketing Information System

Data generation, storage capacity, processing power and analytical capacity increase had created a technological phenomenon named big data that could create big impact in research and development. In the marketing field, the use of big data in research can represent a deep dive in consumer understanding. This essay discusses the big data uses in the marketing information system and its contribution for decision-making. It presents a revision of main concepts, the new possibilities of use and a reflection about its limitations.

The leasing operation of research of the office building market in China

The article analysis the external market environment and the situation of requirement and the competitor in market of office building with the same rank and the same type according to market research, the aim is to research the whole processing operation and management, including making the marker orientation, confirming and finding the potential lesse making the rent plan, negotiating and signing the contract.

Research on Countermeasures and Development Status of Red Tourism in Shandong

As a new tourism pattern, red tourism develops rapidly in China. In Shandong, not only the red cultural heritage is rich, but also the red tourism resources are rich, but the development is not very successful now. The paper aims at surveying the status of Shandong red tourism, and analyzes the evaluation of tourists on red tourist attractions by the way of market research. The research indicates that red tourism has the problems including improper publicity, single development model and imperfect infrastructures, for which the paper proposes the suggestions such as multi-channel publicity and multi-mode development. The research results of the paper not only provides scientific basis for developing red tourism in Shandong, but also provides reference for practical management on red tourism.

EXPLORING THE VARIOUS APPROACHES OF A RESEARCH INSTITUTE'S ENTRY INTO THE MARKET

To meet the demands posed by the socialist market economy, to foster the close integration of science & technology with the national economy and thus to promote the development of the forces of production are targets pursued by the current drive of restructuring China’s existing S&T system.For this,the CAS Shenyang Branch has conducted rewarding exploration by diversifying various approaches when moving into the market.As a result,it is not only boosting its own development,but also increasing the strength of the local economy.

Market Disease Pathogens Detection of Imported Fruits in Shanghai

A tremendous amount of imported fresh fruits has been delivered to Shanghai markets, increasing the risk of invasion by harmful plant pathogens. Therefore, it is important to establish an effective detection and supervision system to survey the outbreak of the market diseases of the imported fruits during marketing. The samples were regularly surveyed in different markets to examine varieties, prices, localities, selling conditions, and diseases of the imported fruits from 2004 to 2008. The survey showed that 58 species of 30 different fruits were imported to Shanghai from 16 countries with more expensive price. The larger products were bananas, grapes, apples, and oranges. During the investigation, we found that the imported fruits frequently brought about the relatively serious market diseases. On the basis of morphology and the nuclear internal transcribed spacer （ITS） of ribosomal DNA （rDNA） analysis, 151 isolates of 15 fungi genera, which shown to be pathogenic after the inoculation assay, were finally identified. Among the identified fungi, Alternaria was the most frequent one with the highest detection rate （47.68%）, followed by Penicillium （14.57%） and Fusarium （11.92%）, respectively. Additionally, Pestalotiopsis microspora （detected in grapes Red-Globe coming from the USA） and Botrytis sp. （detected in black-plums coming from the USA） were first reported in China market. The present study summarized the selling situation of the imported fruits in Shanghai markets and constructed a library of the pathogens detected in the imported fruits during the selling period. The results obtained are useful to offer technical parameters for Chinese quarantine in order to prevent an invasion of the foreign harmful micro-organisms.

Statistical Time Series Forecasting Models for Pandemic Prediction

COVID-19 has significantly impacted the growth prediction of a pandemic,and it is critical in determining how to battle and track the disease progression.In this case,COVID-19 data is a time-series dataset that can be projected using different methodologies.Thus,this work aims to gauge the spread of the outbreak severity over time.Furthermore,data analytics and Machine Learning(ML)techniques are employed to gain a broader understanding of virus infections.We have simulated,adjusted,and fitted several statistical time-series forecasting models,linearML models,and nonlinear ML models.Examples of these models are Logistic Regression,Lasso,Ridge,ElasticNet,Huber Regressor,Lasso Lars,Passive Aggressive Regressor,K-Neighbors Regressor,Decision Tree Regressor,Extra Trees Regressor,Support Vector Regressions(SVR),AdaBoost Regressor,Random Forest Regressor,Bagging Regressor,AuoRegression,MovingAverage,Gradient Boosting Regressor,Autoregressive Moving Average(ARMA),Auto-Regressive Integrated Moving Averages(ARIMA),SimpleExpSmoothing,Exponential Smoothing,Holt-Winters,Simple Moving Average,Weighted Moving Average,Croston,and naive Bayes.Furthermore,our suggested methodology includes the development and evaluation of ensemble models built on top of the best-performing statistical and ML-based prediction methods.A third stage in the proposed system is to examine three different implementations to determine which model delivers the best performance.Then,this best method is used for future forecasts,and consequently,we can collect the most accurate and dependable predictions.

Market Knowledge and Stakeholder Considerations for the Biopharmaceutics Sector—Incorporating User Value and Societal Needs in Therapeutic Interventions

Purpose: Many health systems are considered ill-equipped to adequately meet future demand. Although academic entrepreneurs and small and medium-sized enterprises (SMEs) drive health technology innovation, they often suboptimally consider important market and stakeholder requirements. This can result in missed opportunities to improve health system performance, address demand-supply gaps, and achieve financial rewards. Market intelligence can provide crucial information in this regard, but scientifically sourced guidance on how to perform market research for biopharmaceutics is scarce. Our objective was, therefore, to create and provide an easily accessible biopharmaceutics market research toolbox that can be perused by academic entrepreneurs and SMEs to improve the alignment of their developments with stakeholder needs. Design: Guided by market orientation theory, we interviewed senior managers and commercialisation experts from the biopharmaceutics sector. We asked them which information they consider most relevant, and how they collect, analyse and respond to new information to align product features, positioning and stakeholder-relationship management with market needs. Findings: Our innovator toolbox consists of a high-level overview of market intelligence considerations mapped against a novel innovation framework, a stakeholder reasoning and value model, and detailed considerations (checklists) per stakeholder of biopharmaceutics interventions. Originality: We provide here the first market orientation-based overview of market intelligence considerations for the biopharmaceutics sector. Although primarily collated for academic entrepreneurs and SMEs, our innovator toolbox for the biopharmaceutics sector can help all stakeholders better understand their orientation towards markets.

Designing price-contingent vegetable rotation schedules using agent-based simulation

Chinese vegetable production cooperatives supply their members, mostly smallholder farmers, with a rotation schedule for the year. Since vegetable prices are not stable throughout the year, designing a rotation schedule that maximizes expected profits, distributes farmers＇ profits more equitably, maintains the diversity of produce in the market, and reduces the risk of pests and diseases, requires adaptive, price-contingent rotation schedules（here, called ＂self-adaptive adjustment＂）. This study uses an agent-based simulation（ABS） to design self-adaptive rotation schedules that deliver these aims. The selfadaptive adjustment strategy was more profitable for farmers when faced with price volatility, and more equitable as well. This work provides a decision-support tool for managers of Chinese vegetable production cooperatives to provide farmers with more profitable and equitable rotation schedules.