Artículos de revistas: "MARKET RESEARCH TECHNIQUES"

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Birn, Robin J. "Market research techniques in publishing". Learned Publishing 2, n.º 3 (1 de enero de 1989): 125–28. http://dx.doi.org/10.1002/leap/20047.

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Wilton, Vivien y Keith Greenhoff. "Integration of sensory techniques into market research". Food Quality and Preference 1, n.º 1 (enero de 1988): 33–35. http://dx.doi.org/10.1016/0950-3293(88)90006-7.

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Wilson, Suzanne G. "Market Research Techniques-A Synopsis for CE Providers". Journal of Continuing Education in Nursing 23, n.º 4 (julio de 1992): 182–83. http://dx.doi.org/10.3928/0022-0124-19920701-11.

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Dzikevičius, Audrius y Svetlana Šaranda. "SMOOTHING TECHNIQUES FOR MARKET FLUCTUATION SIGNALS". Business: Theory and Practice 12, n.º 1 (10 de marzo de 2011): 63–74. http://dx.doi.org/10.3846/btp.2011.07.

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The financial crisis of 2008–2009 caused lots of discussions between Academia and as a result researches on financial crisis and bubble prediction possibilities appeared. Academia shows its growing interest in the issue during the last decade. The majority of researches made are based on different forms of forecast used. Some of previous studies claim that the trend of the stock market can be forecasted using moving average method. After the finance market crashed, a need to forecast further possible bubbles arises. As the economics of the Baltic States is very sensitive to such bubbles it is very important to forecast preliminary the trends of the finance markets ant to plan the right actions in order to temper such bubble influence on the national economics. Although economic theory is opposite to the technical analysis theory which is the main tool for traders in stock markets it is used widely. This paper examines whether a proper technical analysis rule such as Exponential Moving Average (EMA) has a predictive power on stock markets in the Baltic States. The method is applied to OMX Baltic Benchmark Index and industrial indexes as they are more or less sensitive to the main index fluctuations. The results were compared using systematic error (mean square error, the mean absolute deviation, mean forecast error, the mean absolute percentage error) and tracking signal evaluation, CAPM method and appropriate period of EMA finding for each market forecast. A graphical analysis was used in order to determine whether EMA can forecast the main trends of the stock market fluctuations. The conclusions made during the research suggest new research issues and new hypotheses for its further testing.

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Boddy, Clive R. "Projective techniques in Taiwan and Asia‐Pacific market research". Qualitative Market Research: An International Journal 10, n.º 1 (23 de enero de 2007): 48–62. http://dx.doi.org/10.1108/13522750710720396.

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Chopra, Ritika y Gagan Deep Sharma. "Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda". Journal of Risk and Financial Management 14, n.º 11 (4 de noviembre de 2021): 526. http://dx.doi.org/10.3390/jrfm14110526.

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The stock market is characterized by extreme fluctuations, non-linearity, and shifts in internal and external environmental variables. Artificial intelligence (AI) techniques can detect such non-linearity, resulting in much-improved forecast results. This paper reviews 148 studies utilizing neural and hybrid-neuro techniques to predict stock markets, categorized based on 43 auto-coded themes obtained using NVivo 12 software. We group the surveyed articles based on two major categories, namely, study characteristics and model characteristics, where ‘study characteristics’ are further categorized as the stock market covered, input data, and nature of the study; and ‘model characteristics’ are classified as data pre-processing, artificial intelligence technique, training algorithm, and performance measure. Our findings highlight that AI techniques can be used successfully to study and analyze stock market activity. We conclude by establishing a research agenda for potential financial market analysts, artificial intelligence, and soft computing scholarship.

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Abbasi, Behjat y Mohammad Hamed Khan Mohammadi. "Effect of strategic management accounting techniques on market share changes in firms in Tehran Stock Exchange market". Problems and Perspectives in Management 14, n.º 3 (15 de septiembre de 2016): 325–31. http://dx.doi.org/10.21511/ppm.14(3-si).2016.04.

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Increasing market share is one of the main challenges of organizations nowadays, in order to guarantee profitability and survival of the organization. Market share index in an indicator of success/failure. The aim of the present study is to investigate the effect of strategic management accounting techniques effect on market share changes in Tehran stock market companies. This is a descriptive research in which information are in collected via secondary data and inspecting financial statements. The purpose is to investigate the relationship between variables of the study and then find their correlation. Results of the study suggested that market added value, net present value, profitability index and investment return rate are among those accounting strategic techniques that have significant effect on markets market share, but economical added valued doesn’t have a significant effect on markets share changes. Keywords: market added value (MAV), economic value added, net present value, profitability index, investment return rate, market share changes. JEL Classification: G14, G30, M31, M41

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Patel, Jay, Siddhanth Jain y U. M. Prakash. "Multivariate Index Relationship Exploration Using Advanced Machine Learning Techniques". International Journal for Research in Applied Science and Engineering Technology 11, n.º 4 (30 de abril de 2023): 3775–85. http://dx.doi.org/10.22214/ijraset.2023.51011.

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Abstract: Stock market forecasts have always attracted the attention of many analysts and researchers. Popular theory suggests that stock markets are inherently straightforward, and trying to predict them is a trivial matter. It is a difficult problem in itself. The market behaves like a voting machine in the short term, but in the long term it behaves like a pair of scales. Therefore, there is room to predict market movements over a longer period of time. Applying machine learning techniques and other algorithms to stock price analysis and forecasting is a promising area. This white paper begins with a brief overview of the stock market and a taxonomy of stock market forecasting methods. We then highlight some research findings on resource analysis and forecasting. We discuss technical, fundamental, short- term and long-term approaches to equity analysis. Finally, we present some challenges and research opportunities in this area.

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Shah, Dev, Haruna Isah y Farhana Zulkernine. "Stock Market Analysis: A Review and Taxonomy of Prediction Techniques". International Journal of Financial Studies 7, n.º 2 (27 de mayo de 2019): 26. http://dx.doi.org/10.3390/ijfs7020026.

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Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them. Predicting stock prices is a challenging problem in itself because of the number of variables which are involved. In the short term, the market behaves like a voting machine but in the longer term, it acts like a weighing machine and hence there is scope for predicting the market movements for a longer timeframe. Application of machine learning techniques and other algorithms for stock price analysis and forecasting is an area that shows great promise. In this paper, we first provide a concise review of stock markets and taxonomy of stock market prediction methods. We then focus on some of the research achievements in stock analysis and prediction. We discuss technical, fundamental, short- and long-term approaches used for stock analysis. Finally, we present some challenges and research opportunities in this field.

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10

Wilson, Suzanne G. "Brief: Market Research Techniques-A Synopsis for Continuing Education Providers". Journal of Continuing Education in Nursing 21, n.º 5 (septiembre de 1990): 224–26. http://dx.doi.org/10.3928/0022-0124-19900901-11.

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Regale, Jason. "Market Research Matters: Tools and Techniques for Aligning Your Business". Quality Management Journal 9, n.º 1 (enero de 2002): 92–94. http://dx.doi.org/10.1080/10686967.2002.11919000.

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Witell, Lars, Per Kristensson, Anders Gustafsson y Martin Löfgren. "Idea generation: customer co‐creation versus traditional market research techniques". Journal of Service Management 22, n.º 2 (26 de abril de 2011): 140–59. http://dx.doi.org/10.1108/09564231111124190.

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Dutka, Solomon y Lester R. Frankel. "Misuses and Abuses of Statistical Techniques in Market Research Surveys". CHANCE 3, n.º 4 (septiembre de 1990): 18–23. http://dx.doi.org/10.1080/09332480.1990.11882390.

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Andi Ayu Frihatni. "The Existence of Modern Mini Markets amidst Traditional Retail Market". International Journal of Science, Technology & Management 1, n.º 3 (30 de septiembre de 2020): 244–50. http://dx.doi.org/10.46729/ijstm.v1i3.57.

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This research aims at discussing the existence of modern mini market consisting amidst traditional retail market. I t was conducted at Parepare, South Sulawesi, Indonesia. Modern mini market in this research consisted of the Alfamart, Indomaret, and Alfamidi. The data analysis used in this study used a quantitative approach. The data analysis techniques in this study use descriptive statistics and simple regression as well as paired t-test. The result of this research found that the existence of modern mini market has no effects on the going concern of traditional retail market.

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Nath, Om y Swapan Shakhari. "Stock Market Prediction Techniques: A Literature Review". International Journal for Research in Applied Science and Engineering Technology 11, n.º 1 (31 de enero de 2023): 1793–800. http://dx.doi.org/10.22214/ijraset.2023.48931.

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Abstract: This literature review summarizes the existing research on the use of machine learning for stock market prediction. The review covers studies from various sources such as journals, conference proceedings, and theses. The methods used for stock market prediction using machine learning include decision trees, support vector machines, artificial neural networks, and time-series analysis. The review also highlights the advantages and limitations of these methods, as well as their applications in the stock market. The findings of the review indicate that machine learning has the potential to provide valuable insights into the stock market, but there is still room for improvement in terms of accuracy and robustness. The review concludes by suggesting future directions for research in this field

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Gudiño Pérez, Patricia y Arturo Sánchez Martínez. "Market Research in Mexico: Anthropological Studies and Innovations in Qualitative Techniques". Gestión y Estrategia 30 (1 de julio de 2006): 75–86. http://dx.doi.org/10.24275/uam/azc/dcsh/gye/2006n30/gudino.

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Gaul, Wolfgang y Christian Homburg. "The use of data analysis techniques by German market research agencies". Journal of Business Research 17, n.º 1 (agosto de 1988): 67–79. http://dx.doi.org/10.1016/0148-2963(88)90024-0.

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Turcaș, Florin, Florin Cornel Dumiter y Marius Boiță. "Econophysics Techniques and Their Applications on the Stock Market". Mathematics 10, n.º 6 (8 de marzo de 2022): 860. http://dx.doi.org/10.3390/math10060860.

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Exact sciences have achieved many results, validated in practice. Although their application in economics is difficult due to the human factor involved, the lack of conservation laws, and experimental difficulties, it must be highlighted that the consistent bibliography gathered in recent years in this field encourages the econophysics approach. The objective of this article is to validate and/or define a few stock strategies, based on known results from mathematics, physics, and chemistry. The scope of this research demonstrates that statistics (in portfolio theory), geometry (in technical analysis), or financial mathematics can be used in the capital market. Many of the exact science results corresponded to strategies applicable to investors. Unlike the material world, financial markets have additional components that must be considered: human psychology, sociology at the firm level, and behavioral unpredictability. The findings obtained in this research enable the enormous vastness of the exact science results that can be a fertile source for new investment strategies. This article concludes that in order for mathematical theories to be applied to the stock market, it is essential that the start-up conditions (initial assumptions) are validated in the market.

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ASHOUR, Mohammed Lutfı. "TRIANGULATION AS A POWERFUL METHODOLOGICAL RESEARCH TECHNIQUE IN TECHNOLOGY-BASED SERVICES". Business & Management Studies: An International Journal 6, n.º 1 (25 de abril de 2018): 193–208. http://dx.doi.org/10.15295/bmij.v6i1.209.

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This research is an attempt to idntfiy triangulation techniques that helps in overcoming constraints facing researchers within service markets based on high technology. Because of the high contact customer-telecommunication services providers (TSP) relationship, its reliability on the advanced rapid technology, and its short life cycle, telecommunication services are classified as a highly complex services market. In addition to the predominant characteristics of service, TSPs` marketing activities are directed at people (not goods), a matter that causes considerable difficulties in conducting research in telecommunication markets and also cusses challenges regarding finding acceptance. Hence, the pluralist perspective of triangulation, gives more attention on matching between various methodological techniques and difficulties in researching in such complicated markets. Moreover, triangulation as a methodological approach provides alternative techniques that may enable overcoming bias, eclecticism or other researching problematic issues. The purpose of this article is to explore the difficulties that pose a threat with respect to the validity and credibility of research output within high-tech services and the appropriate methodological research techniques the researcher can utilize to overcome these obstacles.

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Deshpande, Rucha, Divyank Lunkad, Madhura Kunjir y Samiksha Ingle. "Stock Price Prediction and Analysis using Machine Learning Techniques". International Journal for Research in Applied Science and Engineering Technology 10, n.º 5 (31 de mayo de 2022): 2092–98. http://dx.doi.org/10.22214/ijraset.2022.42747.

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Abstract: Stock market is one of the most sought-after investment options today. Investing in the stock market has the potential to multiply people's money in a short period of time, but it also carries many risks. To be successful in the stock market, it is necessary to conduct extensive research about the market and the forces influencing it. This examination involves a review of historical stock prices as well as real-time market developments. When deciding the position in the market, investors need to make an informed choice. Market-related information may be obtained from a variety of sources, including news articles, stock research websites, apps, and television channels. However, stock movement prediction by taking into consideration the elements influencing it would undoubtedly assist investors in making sound decisions. The research area of stock movement prediction has seen numerous advancements throughout the years. In the domain of machine learning, various methods of stock price prediction have been introduced. In this paper, we have discussed different approaches to stock movement prediction based on diverse factors and technical indicators. We also propose a method for detecting market trends, which is a critical aspect in maintaining long-term market positions. Keywords: Machine Learning, Stock Market, Prediction, Classification, Technical Indicators, Trend prediction

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Boddy, Clive. "Projective Techniques in Market Research: Valueless Subjectivity or Insightful Reality? A Look at the Evidence for the Usefulness, Reliability and Validity of Projective Techniques in Market Research". International Journal of Market Research 47, n.º 3 (mayo de 2005): 239–54. http://dx.doi.org/10.1177/147078530504700304.

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Madan, Christopher R. "Neuromarketing: the next step in market research?" Eureka 1, n.º 1 (9 de marzo de 2010): 34–42. http://dx.doi.org/10.29173/eureka7786.

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Neuromarketing is an emerging interdisciplinary field connecting psychology and neuroscience with economics. The goal of neuromarketing is to study how the brain is physiologically affected by advertising and marketing strategies. In order to evaluate the effectiveness of these strategies, brain activity resulting from viewing an advertisement is monitored and measured using neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Neuromarketing studies usually measure preference between products in terms of brand familiarity or product preference. In traditional marketing studies, measures such as the product preference for a particular advertisement is sometimes difficult to measure, as a viewer may hold a cognitive bias. However, brand familiarity and product preference have been correlated with neural activity. The field of neuromarketing is still viewed with caution from consumer protection groups as well as many academics due to the possible ethical implications of designing advertisements to intentionally cause specific neurological effects.

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Garrett, Alexander y Cara Wrigley. "Navigating market opportunity: traditional market research and deep customer insight methods". Qualitative Market Research: An International Journal 22, n.º 3 (10 de junio de 2019): 456–71. http://dx.doi.org/10.1108/qmr-05-2017-0091.

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PurposeThis paper aims to explore the use of a design process of inquiry that incorporates both deep customer insight (DCI) and traditional market research (TMR) in an ill-defined, complex current market opportunity to generate new business opportunities for firm-based innovation.Design/methodology/approachThe paper reports on an empirical research case study conducted within a multi-national insurance agency looking at the shift in mobility in Australia. Data were collected across seven distinct research phases, all of which used TMR and DCI techniques for joint comparison.FindingsThe findings revealed that TMR and DCI methodologies developed both contradictory and complementary research outcomes. These outcomes saw rise to newly generated novel business model concepts for market entry opportunity from the case study firm.Research limitations/implicationsThe theoretical outcome of this study is the design thinking DCI framework providing guidance on appropriate implementation of research methods to respond to complex market opportunity.Practical implicationsDCI methods used in conjunction with TMR can provide early stage market opportunity assessment for firms seeking to innovate from a customer perspective.Originality/valueThis is the first paper to apply a design approach, combining TMR and DCI methods to a complex market opportunity rather than a tangible problem. In addition, it also contributes to the emerging field of DCI methodologies by providing a practical examination of their use in the field.

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Sable, Rachna, Shivani Goel y Pradeep Chatterjee. "Techniques for Stock Market Prediction: A Review". International Journal on Recent and Innovation Trends in Computing and Communication 11, n.º 5s (5 de junio de 2023): 381–402. http://dx.doi.org/10.17762/ijritcc.v11i5s.7056.

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Stock market forecasting has long been viewed as a vital real-life topic in economics world. There are many challenges in stock market prediction systems such as the Efficient Market Hypothesis (EMH), Nonlinearity, complex, diverse datasets, and parameter optimization. A stock's value on the stock market fluctuates due to many factors like previous trends of the stock, the current news, twitter feeds, any online customer feedbacks etc. In this paper, the literature is critically analysed on approaches used for stock market prediction in terms of stock datasets, features used, evaluation metrics used, statistical, machine learning and deep learning techniques along with the directions for the future. The focus of this review is on trend and value prediction for stocks. Overall, 68 research papers have been considered for review from years 1998-2023. From the review, Indian stock market datasets are found to be most frequently used datasets. Evaluation metrics used commonly are accuracy and Mean Absolute Percentage Error. ARIMA is reported as the most used frequently statistical technique for stick market prediction. Long-Short Term Memory and Support Vector Machine are the commonly used algorithms in stock market prediction. The advantages and disadvantages of frequently used evaluation metrics, machine learning, deep learning and statistical approaches are also included in this survey.

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Siering, Michael, Benjamin Clapham, Oliver Engel y Peter Gomber. "A Taxonomy of Financial Market Manipulations: Establishing Trust and Market Integrity in the Financialized Economy through Automated Fraud Detection". Journal of Information Technology 32, n.º 3 (septiembre de 2017): 251–69. http://dx.doi.org/10.1057/s41265-016-0029-z.

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Financial market manipulations represent a major threat to trust and market integrity in capital markets. Manipulations contribute to mispricing, market imperfections and an increase in transaction costs for market participants and in costs of capital for issuers. Manipulations are facilitated by increased transaction velocity, speculative trading and abusive usage of new trading technologies, i.e., they are directly linked to financial sector changes that drive financialization. Research at the intersection of financialization and IS might support regulatory authorities and market operators in improving market surveillance and helping to detect fraudulent activities. However, confusing terminology is prevalent on financial markets with respect to different manipulation techniques and their characteristics, which hampers efficient fraud detection. Furthermore, recognizing manipulations is challenging given the large number of information sources and the vast number of trades occurring not least because of high-frequency traders. Therefore, automated market surveillance tools require a comprehensive taxonomy of financial market manipulations as a basis for appropriate configuration. Based on a cluster analysis of SEC litigation releases, a review of the latest market abuse regulation and academic studies, we develop a taxonomy of manipulations that structures and details existing manipulation techniques and reveals how these techniques differ along several dimensions. In a case study, we show how the taxonomy can be utilized to guide the development of appropriate decision support systems for fraud detection.

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Gruca, Thomas S. y Joyce E. Berg. "PUBLIC INFORMATION BIAS AND PREDICTION MARKET ACCURACY". Journal of Prediction Markets 1, n.º 3 (14 de diciembre de 2012): 219–31. http://dx.doi.org/10.5750/jpm.v1i3.430.

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How do prediction markets achieve high levels of accuracy? We propose that, in some situations, traders in prediction markets improve upon publicly available information. Specifically, when there is a known bias in publicly available information, markets provide an incentive for traders to “de-bias” this information. In such a situation, a prediction market will provide a more accurate forecast than the public information available to traders. We test our conjecture using real-money prediction markets for seven local elections in the United States. We find that the prediction market forecasts are significantly more accurate than those generated using the pre-election polls.Previous versions of this paper were presented at the Workshop on The Growth of Gambling and Prediction Markets, the ISBM Conference on Prediction Markets in Marketing: Issues, Challenges and Research Opportunities, the DIMACS Workshop on Markets as Predictive Devices, and the 17th Annual AMA Advanced Research Techniques Forum. The authors thank the participants for their insights which have helped improve this research

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Al-Baiquni, BJ. "Analysis of Market Structure-Conduct-Performance of Gurame Fish (Osphonemus gouramy) in Kediri Regency". Economic and Social of Fisheries and Marine Journal 006, n.º 02 (30 de abril de 2019): 134–48. http://dx.doi.org/10.21776/ub.ecsofim.2019.006.02.02.

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The role of marketing institutions is important for conducting marketing activities, so that research has a purpose for: 1) knowing the market structure of gurame fish, 2) describing the behavior of gurame fish marketing institutions, 3) knowing the performance of marketing institutions for gurame fish in Kediri Regency. Type of research is descriptive using analysis of structure, conduct, and performance. Sampling techniques using purposive sampling and snowball sampling techniques, data collection techniques by observation, direct interviews and documentation. The results of the study are based on market structure that is influenced by the number of sellers and buyers, barriers to entry and exit markets, and market information indicating that the formed market structure is oligopoly; There are still many marketing agency behaviors that harm several parties in marketing such as accounts payable, and other fraudulent practices; The marketing of gurame fish in Kediri Regecy cannot be said to be efficient because of the uneven distribution of marketing margins, costs, and profits of each institution, as well as the high margin value, costs, and profits from one of the marketing institutions, large-scale collectors.

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Greenland, Steven J., Ian A. Combe y Andrew M. Farrell. "Stakeholder Preference and Stated vs Derived Importance Satisfaction Research". International Journal of Market Research 58, n.º 1 (enero de 2016): 35–55. http://dx.doi.org/10.2501/ijmr-2016-005.

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This paper presents a case study that reveals how stakeholders in the research process, by recommending specific data collection and analytical techniques, exert significant ‘hidden’ influence on the decisions made on the basis of market research findings. While disagreements among stakeholders regarding research design are likely, the possibility that strategies adopted by companies are dependent upon stakeholder research preferences has not been adequately addressed in the literature. Two widely used quantitative customer satisfaction evaluation approaches, involving stated and derived importance, are compared within a real-life market research setting at an international bank. The comparative analysis informs an ongoing debate surrounding the applicability of explicit and implicit importance measures, and demonstrates how recommendations are dependent upon the methodological and analytical techniques selected. The findings, therefore, have significant implications for importance-based satisfaction market research planning, and highlight the need to consider the impact of stakeholder preferences on research outcomes.

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Nanda, Dennis Ulfan y Khusnul Fikriyah. "Perilaku Pedagang Pasar Bandar Kecamatan Mojoroto Kota Kediri Dalam Prespektif Prinsip Dasar Pasar Islami". Jurnal Ilmiah Ekonomi Islam 6, n.º 3 (2 de noviembre de 2020): 588. http://dx.doi.org/10.29040/jiei.v6i3.1364.

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Buying and selling activities are one of the community’s needs as facilities and infrastructure of daily needs. Here, the market as one of the tools where there is buying and selling interaction. The marketing environment can change and be uncertain and provide not only opportunities but also threats. The Bandar market is a traditional market that sells the needs for essential materials at an affordable price for the community. The purpose of this research is to determine the behaviour of traders and compliance with the basic principles of Islamic markets. This type of research uses descriptive qualitative research. Data collection techniques using observation, interview, and documentation. The conclusion of this research is the traders’ behaviour in the Bandar market which already tolerable and precise even though the city market is essentially a conventional market, and traders in the Bandar market already apply the principle of Ar-Ridhla, healthy competition, honesty, openness, and justice properly. Keywords : Traditional market, behavior of traders, basic principles of islamic market

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Khizhnyak, A. N. y Y. Y. Maksimova. "Cognitive techniques in the innovation economy". Izvestiya MGTU MAMI 7, n.º 1-5 (10 de septiembre de 2013): 264–68. http://dx.doi.org/10.17816/2074-0530-67928.

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Changing market demands is the reason to find new research methods for the timely update of the potential demand for adoption of the most appropriate marketing decisions, which is especially important in production of innovations. One of these methods are the repertory grids that enable customers to identify unconscious needs for goods, new items, and allow manufacturers to market products that will be in demand, thereby ensuring profitability, profitability and competitiveness in innovation economy.

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Lee, Ching-Sung, Yen-Cheng Chen, Pei-Ling Tsui, Cheng-Wei Che y Ming-Chen Chiang. "Application of Fuzzy Delphi Technique Approach in Sustainable Inheritance of Rural Cooking Techniques and Innovative Business Strategies Modeling". Agriculture 11, n.º 10 (26 de septiembre de 2021): 924. http://dx.doi.org/10.3390/agriculture11100924.

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Transformation and sustainable development must be undertaken in accordance with the trends of the times, which presents challenges to rural areas worldwide. In addition to preserving rural food specialties and presenting them in new ways to attract consumers, these areas must link farmers’ production, processing, sales, and management. It is imperative to sustainably pass on rural foods and theircooking techniques and integrate them into innovative business strategies so that delicious rural foods can be sold on the consumer market, boosting rural economies and their development. The main objective of this research was to conduct indicator modeling and empirical analysis for the sustainable inheritance of Taiwan’s rural cooking techniques and the development of innovative marketing strategies. The Fuzzy Delphi Technique was used as the main research method to select agricultural experts and rural household economy organizations for indicator modeling and empirical analysis. The results of the research indicate that agricultural experts believe that market operation is the primary developmental focus of cultural inheritance and innovation, whereas household economy organizations believe that education, training, promotion, and development are the primary developmental focuses. The greatest contribution and innovation of this research are the findings that culinary education and training, organized by the farmers’ association, can sustainably pass on traditional rural cooking techniques, and the process of incorporating local ingredients into commercial gourmet food should also consider aspects of the economic and marketing strategies of market operation, facilitating the sustainable inheritance of unique, traditional, local, and rural food culture.

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Ramsey, Elaine, Patrick Ibbotson y Patrick McCole. "Application of Projective Techniques in an E-business Research Context: A Response to ‘Projective Techniques in Market Research -Valueless Subjectivity or Insightful Reality?’". International Journal of Market Research 48, n.º 5 (septiembre de 2006): 551–73. http://dx.doi.org/10.1177/147078530604800506.

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Sansavini, S. "Towards a Sustainable Fruit Industry in Europe: Research and Strategies". HortScience 30, n.º 4 (julio de 1995): 806F—806. http://dx.doi.org/10.21273/hortsci.30.4.806f.

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The European Union's fruit industry is currently beset by marked surplus output, formidable market competition from non-EU countries, and strong consumer demanded for enhanced quality. This latter issue is particularly complex because it involves not only the fruit's genetic, esthetic, sensory, and taste characters, but also pre- and postharvest produce management practices and their impact on the environment and human health. The main thrust of the response to the challenges posed by these quality factors is integrated fruit production (IFP), a policy sustainable crop growing that the EU can support financially. Research has been directly involved in IFP and the directions in which it is moving. It has developed the first EU guidelines (OILB-ISHS), which initially covered pome crops and were later extended to cover all fruits, and the field, harvest, handling, storage, and market monitoring and quality-control techniques needed to implement them. These methods include biological and integrated disease and pest control, the introduction of plant material resistant to biotic and abiotic stresses, the development of field management practices to enhance plant defense and cropping-control mechanisms, the use of energy-saving irrigation and nutrient input techniques, the modeling of plantations, training systems and tree-bearing control, and advanced fruit storage, packaging, and transport methods. The updated advances in these areas are reported and discussed.

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Fajarwati, Eka. "STRATEGI PERMODALAN PEDANGAN PASAR SOPONYONO DI KECAMATAN RUNGKUT KOTA SURABAYA". MANAJERIAL 4, n.º 1 (23 de marzo de 2018): 69. http://dx.doi.org/10.30587/manajerial.v4i1.308.

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The market is generally divided into two, namely traditional markets and modern markets. Traditional market is a market that has a simple buying and selling activities, there is a bargain with a means of payment in the form of cash. In addition, the market is not only a place for the community in meeting the daily needs, but also the center of the community's economic drive. Traditional market is an important channel in the distribution process of agribusiness products as big as food product of daily necessities. The competition of traditional markets and modern markets is getting tighter. The government is trying to assist the development of traditional markets in order to compete with modern markets by planning the revitalization and fostering of market management so that not only physical improvements are made but also services and market management mangement. Related to this problem is capital strategy applied by traditional market trader Soponyono in face of tight competition with modern market. This research method is descriptive study by using qualitative approach. Data collection techniques through (1) indepth interview, in-depth interviews until the data obtained is considered sufficient and (2) observation that is observing the learning process undertaken. The process of data analysis using capital strategy theory. The selection of this theory is based on the object of research that is Soponyono Surabaya Market so that it can know more deeply about the capital process of Soponyono market traders related to the problem of competition with modern market Based on the result of research known that capital strategy of traditional traders in facing modern market through banking funding, Private capital and BKM and BMT. Obstacles from the cooperation of management of Taman Remaja Surabaya by City Government

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Rogers, Helen, Norbert Baricz y Kulwant S. Pawar. "3D printing services: classification, supply chain implications and research agenda". International Journal of Physical Distribution & Logistics Management 46, n.º 10 (7 de noviembre de 2016): 886–907. http://dx.doi.org/10.1108/ijpdlm-07-2016-0210.

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Purpose The purpose of this paper is to identify and classify the available types of 3D printing services, with the scope of determining the potential implications that such services could have on the supply chains of manufacturing firms and creating a research agenda for future studies. Design/methodology/approach The authors review the current literature on the potential supply chain impacts of 3D printing and evaluate the 3D printing services provided by 404 firms in selected European markets. Findings The results show that 3D printing services form a rapidly evolving industry, with new service providers entering the market on a regular basis. Evidence from the European markets investigated suggests that services can be classified into three distinct categories: generative, facilitative and selective services. Research limitations/implications This paper represents an attempt to take stock of a fast-moving and potentially paradigm-shifting market. The implications are dynamic as new applications, business models and techniques are continually being developed. Further studies are required to substantiate the findings. Practical implications Three categories of 3D printing services that could significantly impact supply chain configurations of the future are proposed. Several issues specific to 3D printing services raised in the research agenda require further scrutiny and substantiation before services can reach their full potential. Originality/value This paper provides an overview of the growing 3D printing services industry, highlighting how the market might change as additive manufacturing technology matures.

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Somanathan, Arjun Remadevi y Suprabha Kudigrama Rama. "A Bibliometric Review of Stock Market Prediction: Perspective of Emerging Markets". Applied Computer Systems 25, n.º 2 (1 de diciembre de 2020): 77–86. http://dx.doi.org/10.2478/acss-2020-0010.

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Abstract The objective of the paper is to identify predictive models in stock market prediction focusing on a scenario of the emerging markets. An exploratory analysis and conceptual modelling based on the extant literature during 1933 to 2020 have been used in the study. The databases of Web of Science, Scopus, and JSTOR ensure the reliability of the literature. Bibliometrics and scientometric techniques have been applied to the retrieved articles to create a conceptual framework by mapping interlinks and limitations in past studies. Focus of research is hybrid models that integrate big data, social media, and real-time streaming data. Key finding is that actual phenomena affecting stock market sectors are diverse and, hence, limited in generalization. The future research must focus on models empirically validated within the emerging markets. Such an approach will offer an insight to analysts and researchers, policymakers or regulators.

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Irmawanty, Irmawanty, Dian Safitri, Wira Yustika Rukman y Haerul Syam. "Organic waste processing and its application to potato plants through hydroponic techniques". JPBIO (Jurnal Pendidikan Biologi) 6, n.º 1 (29 de abril de 2021): 84–95. http://dx.doi.org/10.31932/jpbio.v6i1.1040.

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The Kalimbu market is one of the traditional markets in South Sulawesi with a very high buying and selling activity. The organic waste that is mostly generated from the activities at the Kalimbu Market is leftover vegetables and fruit. Vegetable and fruit waste provides a big advantage if it is managed properly, which is converted into liquid organic fertilizer through a fermentation process. The liquid organic fertilizers produced can help farmers overcome the high price of synthetic fertilizers and save the earth from pollution. The method used to determine the effect of types of organic waste (vegetable waste and fruit waste) on the physical and chemical quality of solid and liquid organic fertilizers used a randomized block design. Whereas the application of solid and liquid organic fertilizers to the production and nutritional content of potato plants used a treatment consisting of P0: basic fertilizer + without liquid organic fertilizer and P1: basic fertilizer + liquid organic fertilizer. The results of research on the manufacture of liquid organic fertilizer from Kalimbu market waste with vegetable and fruit samples also showed that the two samples required different storage times for composting. Plants treated with liquid organic fertilizer from the Kalimbu market waste have better stem growth, leaf number, and stem number.Keywords: Waste, organic, fermentation, hydroponic

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Tkaczynski, Aaron y Sharyn Rundle-Thiele. "Event Market Segmentation: A Review Update and Research Agenda". Event Management 24, n.º 2 (7 de abril de 2020): 277–95. http://dx.doi.org/10.3727/152599519x15506259855913.

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Segmenting target audiences can deliver increases in audiences attending events. An examination of segmentation research progress in the field is needed to assess the extent that researchers are capitalizing on available opportunities. Following the Tkaczynski and Rundle-Thiele framework, this article reviews 90 segmentation articles published from 2010 onwards to examine attendee profiling practices and to assess research practice change over time. Nine research issues have been proposed, which are subsequently discussed. Findings indicate an increase in geographic reach (e. g., Africa and Europe) and a continued dominant focus on on-site self-administered surveys as the data collection method. Both sample sizes and application of multivariate data analysis techniques have increased, and studies are largely employing the same segmentation bases and variables across the two research reviews. Recommendations for future research such as a need for larger sample sizes to warrant segmentation and a greater focus on external validation of segments are outlined.

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Mansukhbhai, Panchal Amitkumar y Dr Jayeshkumar Madhubhai Patel. "Role of soft computing techniques in predicting stock market direction". Artificial Intelligence Research 1, n.º 2 (17 de septiembre de 2012): 198. http://dx.doi.org/10.5430/air.v1n2p198.

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The stock market is a complex and dynamic system with noisy, non-stationary and chaotic data series. Prediction of a financial market is more challenging due to chaos and uncertainty of the system. Soft computing techniques are progressively gaining presence in the financial world. Compared to traditional techniques to predict the market direction, soft computing is gaining the advantage of accuracy and speed. However the input data selection is the major issue in soft computing. The aim of this paper is to explain the potential day by day research contribution of soft computing to solve complex problem such as stock market direction prediction. This study paper synthesizes five reference papers and explains how soft computing is gaining the popularity in the field of financial market. The selection of papers are based on various models wich are processing different input parameters for predicting the direction of stock market.

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Fitriani, Eka Dwi y Bayu Nuswantara. "Pengaruh Faktor Sosial Ekonomi Terhadap Loyalitas Konsumen Di Pasar Tradisional Ampel Kabupaten Boyolali". SEPA: Jurnal Sosial Ekonomi Pertanian dan Agribisnis 15, n.º 1 (1 de noviembre de 2018): 91. http://dx.doi.org/10.20961/sepa.v15i1.25058.

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This study examines socioeconomic factors on consumer loyalty in choosing to shop at the traditional Ampel market in Boyolali Regency. In order for traditional markets to survive and develop in the competitive business world in competing for consumers, it must be able to understand it’s consumers. Many factors can influence consumer loyalty in choosing to shop in traditional markets. In this study the factors that are thought to influence are product prices, product quality, merchant service, product location and market days. The type of research used is a survey with 50 sampling using incidental sampling. The type of data used is primary data and secondary data. Data collection techniques using questionnaires and data analysis techniques used multiple linear regression. Instrument test results show all valid and reliable. Multiple linear regression test shows Y = -9,199 + 0.510 X1 + 0.460 X2 - 0.192 X3 + 0.708 X4 + 0.551 X5. It is shows that product price variables, product quality, market location and market day have a positive effect on consumer loyalty.

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Usmani, Shazia y Jawwad A. Shamsi. "News sensitive stock market prediction: literature review and suggestions". PeerJ Computer Science 7 (4 de mayo de 2021): e490. http://dx.doi.org/10.7717/peerj-cs.490.

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Stock market prediction is a challenging task as it requires deep insights for extraction of news events, analysis of historic data, and impact of news events on stock price trends. The challenge is further exacerbated due to the high volatility of stock price trends. However, a detailed overview that discusses the overall context of stock prediction is elusive in literature. To address this research gap, this paper presents a detailed survey. All key terms and phases of generic stock prediction methodology along with challenges, are described. A detailed literature review that covers data preprocessing techniques, feature extraction techniques, prediction techniques, and future directions is presented for news sensitive stock prediction. This work investigates the significance of using structured text features rather than unstructured and shallow text features. It also discusses the use of opinion extraction techniques. In addition, it emphasizes the use of domain knowledge with both approaches of textual feature extraction. Furthermore, it highlights the significance of deep neural network based prediction techniques to capture the hidden relationship between textual and numerical data. This survey is significant and novel as it elaborates a comprehensive framework for stock market prediction and highlights the strengths and weaknesses of existing approaches. It presents a wide range of open issues and research directions that are beneficial for the research community.

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Gupta, Sanjay Kumar, Sudeep Gorai y M. S. Nain. "Perceptual Mapping for Agricultural Marketing Research: Concept and Methodologies". Journal of Extension Systems 37, n.º 1 (2021): 62–66. http://dx.doi.org/10.48165/jes.2021.37109.

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In the agriculture the focus was more on the production of commodity than marketing of it. In the wake of the focus on doubling the income of farmers one of the strategies can be the direct marketing of the produce. It may be possible through the market research, which previously had been in use at very nominal rate, but at present we have systematic market research technique and methodology for market positioning and for the formulation of suitable strategies for the farmers. One of the suitable and systematic marketing research techniques is perceptual mapping. Perceptual maps are often used in marketing to visually study relations between two or more attributes the process of making perceptual map is perceptual mapping. However, in many perceptual maps published in the recent literature it remains unclear what is being shown and how the relations between the points in the map can be interpreted or even what a point represents. The term perceptual map refers to plots obtained by a series of different techniques, such as principal component analysis, (multiple) correspondence analysis, and multidimensional scaling, each needing specific requirements for producing the map and interpreting it. Some of the major flaws of published perceptual maps are omission of reference to the techniques that produced the map, non-unit shape parameters for the map, and unclear labelling of the points. To facilitate this, a small set of simple icons that indicate the rules for correctly interpreting the map. We present several examples, point out flaws and show how to produce better maps.

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43

Douglas, Bob. "Healthcare market research examined. Relevant, rigorous and highly regulated". Reviews in Health Care 2, n.º 4 (5 de septiembre de 2011): 205. http://dx.doi.org/10.7175/rhc.6424205-208.

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[The abstract of this article is not available. Here are the first sentences of the article. The full text is freely available upon registration]Market research is invariably confused with marketing – but, in fact, the two disciplines are very different. Put in its simplest terms, marketing is about promotion whilst market research is about understanding. Accordingly, data collected for market research purposes are used in a completely different way to that gathered for marketing, with research practices heavily regulated to ensure high ethical standards.Let’s begin with a definition of what, exactly, market research is. According to the ICC/ESOMAR International Code 2007 (a definition also adopted by the European Pharmaceutical Market Research Association), it is: «the systematic gathering and interpretation of information about individuals or organisations using the statistical and analytical methods and techniques of the applied social sciences to gain insight or support decision-making. The identity of respondents will not be revealed to the user of the information without explicit consent and no sales approach will be made to them as a direct result of their having provided information».

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Douglas, Bob. "Healthcare market research examined. Relevant, rigorous and highly regulated". Reviews in Health Care 2, n.º 4 (5 de septiembre de 2011): 205–8. http://dx.doi.org/10.7175/rhc.v2i4.64.

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[The abstract of this article is not available. Here are the first sentences of the article. The full text is freely available upon registration]Market research is invariably confused with marketing – but, in fact, the two disciplines are very different. Put in its simplest terms, marketing is about promotion whilst market research is about understanding. Accordingly, data collected for market research purposes are used in a completely different way to that gathered for marketing, with research practices heavily regulated to ensure high ethical standards.Let’s begin with a definition of what, exactly, market research is. According to the ICC/ESOMAR International Code 2007 (a definition also adopted by the European Pharmaceutical Market Research Association), it is: «the systematic gathering and interpretation of information about individuals or organisations using the statistical and analytical methods and techniques of the applied social sciences to gain insight or support decision-making. The identity of respondents will not be revealed to the user of the information without explicit consent and no sales approach will be made to them as a direct result of their having provided information».

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Liu, Yang, Qi Liu, Hongke Zhao, Zhen Pan y Chuanren Liu. "Adaptive Quantitative Trading: An Imitative Deep Reinforcement Learning Approach". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 02 (3 de abril de 2020): 2128–35. http://dx.doi.org/10.1609/aaai.v34i02.5587.

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In recent years, considerable efforts have been devoted to developing AI techniques for finance research and applications. For instance, AI techniques (e.g., machine learning) can help traders in quantitative trading (QT) by automating two tasks: market condition recognition and trading strategies execution. However, existing methods in QT face challenges such as representing noisy high-frequent financial data and finding the balance between exploration and exploitation of the trading agent with AI techniques. To address the challenges, we propose an adaptive trading model, namely iRDPG, to automatically develop QT strategies by an intelligent trading agent. Our model is enhanced by deep reinforcement learning (DRL) and imitation learning techniques. Specifically, considering the noisy financial data, we formulate the QT process as a Partially Observable Markov Decision Process (POMDP). Also, we introduce imitation learning to leverage classical trading strategies useful to balance between exploration and exploitation. For better simulation, we train our trading agent in the real financial market using minute-frequent data. Experimental results demonstrate that our model can extract robust market features and be adaptive in different markets.

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46

Medlock, R. S. "Recent Advances in Industrial Measurement Techniques". Measurement and Control 20, n.º 3 (abril de 1987): 6–13. http://dx.doi.org/10.1177/002029408702000301.

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The paper identifies ten market areas for sensors and then concentrates on the special characteristics, requirements and technologies of the industrial sector with its market purchases of US$2.8 Billion annually. The particular characteristics of this market are variety and a relatively long gestation period between the breadboard and the fully accepted and engineered product. The treatment of the subject and the definition of the word ‘recent’ in the title is related in the first half of the paper towards the fully engineered quantity production end of sensor development rather than on original research work much of which never reaches industrial usage. Some twenty examples, selected by the author, of interesting recent developments are briefly described. These were chosen on the basis of their technical interest and innovatory measurement principles rather than on their industrial importance. The latter part of the paper deals with potentially important technologies likely to influence sensor developments of the future such as Langmuir-Blodgett films and to mention in passing our Prime Minister's erstwhile scientific contribution to this topic.

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McClure, Kirk. "Implementation of Linkage Programs: The Planner's Role in Real Estate Market Research and Regulation". Journal of Planning Education and Research 8, n.º 1 (octubre de 1988): 45–52. http://dx.doi.org/10.1177/0739456x8800800112.

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The study of real estate development has become an integral part of planning education as planners draw upon the techniques of real estate investment analysis to control land use. The application of these techniques has been expanded by linking new commercial development to noncommercial development that serves public goals. Fees charged against new commercial development are used to fund social programs, such as the production of low income housing. To make these linkage programs work, planners must possess skills in both individual real estate project analysis and market-wide regulation. It is argued here that this second area, market regulation, has not received adequate attention in planning curricula.

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Soenjoto, Wening Purbatin Palupi y Septiyan Hudan Fuadi. "Kapitalisasi Isu Syariah Terhadap Pergerakan Ekonomi Di Pasar Nasional Dan Global". Journal of Sharia Economics 2, n.º 1 (5 de junio de 2020): 16–28. http://dx.doi.org/10.35896/jse.v2i1.85.

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This study aims to determine the effect of the capitalization of sharia issues on economic movements in national and global markets and try to answer the problem formulation, namely: first, it can describe capitalization of sharia issues that are starting to develop in sharia economic movements in national and global markets. Second: can describe the process of negotiation (interaction) carried out by producers who use sharia issues in trade. Third: can find the implications of the meaning of the results of research and solutions that can add studies related to sharia issues in the economy in national and global markets so that it can be further investigated by subsequent researchers. The method used in this study is a qualitative method with descriptive analysis. Research subjects are informants who provide research data through interviews, surveys and documentation with triangulation data processing techniques to obtain valid research results. Based on the results of the study, it was concluded that the capitalization of sharia issues could affect national and global market movements Keywords: Capitalization, Sharia Issues, Sharia Economy, National Market, Global Market

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Greig, I. "The Application of a New Generation of Consumer Research Techniques to Predicting and Maximising Market Share in the Fibre Market". Journal of the Textile Institute 85, n.º 2 (enero de 1994): 231–43. http://dx.doi.org/10.1080/00405009408659023.

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Lai Cao Mai, Phuong. "Corruption and stock market development in EAP countries". Investment Management and Financial Innovations 17, n.º 2 (1 de julio de 2020): 266–76. http://dx.doi.org/10.21511/imfi.17(2).2020.21.

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Using macroeconomic factors as control variables, this paper examines the impact of corruption on the development of the stock market in East Asia and the Pacific (EAP) from 2008 to 2018. The research model uses GMM techniques to estimate panel data on two sub-sets of data, including five developed markets and seven emerging markets, and a dataset of both market groups. The market capitalization and the stock transaction value relative to GDP represent the development of the stock market, and the corruption control index represents the corruption factor. The empirical results found that corruption has a positive impact on the EAP stock market capitalization with the entire sample data set, which positively affects both size of the market capitalization value and value of stock transactions in underdeveloped markets. However, it is not statistically significant in explaining the development of developed stock markets. Besides, macroeconomic factors such as inflation, interest rates, savings, and credit affect some stock markets at EAP. Compared to previous studies, the article’s results found that corruption affects stock market capitalization and has a positive impact on stock liquidity in underdeveloped stock markets. Corruption affects more underdeveloped stock markets than developed stock markets. This may be due to the implicit relationship of economic benefits between large enterprises and officials in underdeveloped markets.

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