So the trend either can be upward or downward. This technique produces non linear curved lines where the data rises or falls, not at a steady rate, but at a higher rate. Instead of a straight line pointing diagonally up, the graph will show a curved line where the last point in later years is higher than the first year, if the trend is upward.
In this analysis, the line is curved line to show data values rising or falling initially, and then showing a point where the trend increase or decrease stops rising or falling. One can identify a seasonality pattern when fluctuations repeat over fixed periods of time and are therefore predictable and where those patterns do not extend beyond a one year period. Seasonality may be caused by factors like weather, vacation, and holidays. It usually consists of periodic, repetitive, and generally regular and predictable patterns.
Seasonality can repeat on a weekly, monthly or quarterly basis. This type of analysis reveals fluctuations in a time series.
These fluctuations are short in duration, erratic in nature and follow no regularity in the occurrence pattern. A stationary time series is one with statistical properties such as mean, where variances are all constant over time. Methods that provide information on trends and their effects are divided into primary and secondary research. The primary research is first-hand research into trends, using the following methods:. The secondary search uses available information. There are a large number of trend reports for the most diverse industries, which can be used as a source and basis for trend determination.
In the course of primary research, it is also advisable to first determine the available trends by means of a secondary research.
This can also provide the basis for first-hand trend-setting. Answering the questions mentioned above will result in trends, significant changes in the future and also fields of innovation. In order to obtain structured results, a systematic process must be applied:. The findings from trend research are important information for current and future business decisions.
The knowledge of trends and possible future developments flows into strategic innovation management, where future search fields are derived, which in turn can be found in the roadmap.
But it is not only the innovation strategy that is built on this; the future information is also relevant for the development of the corporate strategy itself. And last but not least, trend information is important for all corporate decisions, not only for innovation.
Because all decisions always have to do with the future. It is therefore also important to spread this information very widely throughout the company and to initiate a discussion about it.
In this way, the employees deal with the trends, which initiates a creative process that delivers ideas suitable for the future. Dealing with trends and the future is one of the most important innovation tasks.
It provides the basis for the development of the innovation strategy and future orientation, from which the search fields and the roadmap are derived. If you don't have solid information here, a company can be surprised by a disruption overnight.
Another disaster would be a wrong basic orientation, for example focusing on a wrong customer need that will no longer exist in the morning. This shows that trend research is an important success factor in innovation management. Born and raised in Vienna. We would be pleased to advise you on a possible cooperation to make your innovation management future-proof. Category: Innovation strategy. Definition of trend A trend is an assumed development in the future that will have a long-term and lasting effect on and change something.
Trend management Since trends are very multidimensional, a high degree of attention is paid to them. The management of trends includes: Identification of trends - "Which trends are there or will there be in the future? And which of these are relevant to us? What impact can a trend have in general?
Trend research and identification of relevant trends You can't travel to the future to know how it will turn out. Systematics for identifying trends Systematics in trend research is not a high science.
For example, sex differences in high school contribute little between 0. However, these results, combined with those from Table 2 , do not mean that sex differences before age 19 were small. As we have seen in Figure 4 , the differences are large, especially at age The results simply mean that the large sex differences observed in high school years are absorbed by sex differences in the educational process of college and graduate years. The exercise alternately substitutes one set of males' transition rates at a given age while keeping everything else intact.
Two series of exit and entry rates are displayed in Figures 5 and 6. An interesting result is that the exit rate for females trails that for males closely except at age A larger and more consistent gender gap, however, is observed for the entry rate after age Unfortunately, past research has not paid attention to this problem.
For example, my results contradict Berryman's , p. For males, I have found that the rate of migration into the pool is around 4 percent, compared to less than 2 percent for women.
As small as they may seem, cumulatively these figures are very significant given that only 2 percent of females and 5 percent of males obtain bachelor's and master's degrees in science by age 32 see Table 1.
Education affects occupation, but only in nondeterministic ways. At the master's level, the percentages are better, 27 percent for females and 54 percent for males. In Table 5 , I present simulated occupational distributions at age 32 under four different conditions.
The exercise alternately substitutes males' educational distribution at a given age while keeping everything else intact. Within each panel of Table 5 , two lines represent two sets of transition rates from educational states to occupational states, one for females and one for males. Thus, the first line of Panel A and the second line of Panel B are simulated distributions respectively for females and males using gender-specific information. That is, for a 1,member female cohort following the age-specific transition rates observed for our data, only The comparable number is The proposed approach consists of constructing a synthetic cohort from different longitudinal surveys and modeling the career process as a Markov process as the cohort ages or matures.
Generally speaking, for any given cohort, the proportion of people remaining in the pool decreases with age. College and graduate years account for most of the sex differences in the proportion attaining science degrees by early adulthood. NOTE: Main entries are row percentages, i. As Elder recognizes, the concept of career has been generalized to the concept of trajectory in the literature on life course.
This is akin to Quetelet's notion of the "average man," or the "social man. One major difference between what I propose here and conventional multistate life tables is that age is used here as a truly discrete variable actually school age whereas it is usually used as a continuous variable in multistate life tables. Using age as a discrete variable is legitimate in the present case given that transitions in school take discrete jumps annually grade or class.
The follow-up was a nonrandom subsample with full coverage of college graduates. Other sample members who were retained with certainty included Hispanics, teachers and potential teachers, and persons who were divorced, widowed or separated from their spouses, or never-married parents. This problem is handled by weighing observations by the inverse of the probability of being included. Biological age is actually an approximation, translated from school age as shown in Table 1.
Social science fields are excluded from this study. The detailed codes and titles are available upon request. There are other possible flows such as jumping from not being in college to having a master's degree that are observed in Tables A1 and A2 due to lack of data between two observation periods. Since the sample sizes are large for all transition matrices, sampling errors are ignored in the analysis. Unless, of course, it can be shown that at least one of the measures is gender-biased.
Midpoints of transition intervals are used for the horizontal axis age in Figures 5 and 6. NOTE: Main entries are row proportions. Cells omitted and marked with "--" are structural zeros. Bartholomew, D. Stochastic Models for Social Processes, 2nd edition. London: Wiley.
Berryman, S. Who Will Do Science? A special Report, the Rockefeller Foundation. Brown, D. Brooks and Associates eds. Career Choice and Development, 2nd edition. San Francisco: Jossey-Bass Publishers. Elder, G. Perspectives on the Life Course. Elder, Jr. Freeman, R. Ginzberg, E. Ginsburg, S. Axelrad, and J. New York: Columbia University Press. Huff, R. Washington, D. Printing Office. Hoem, J. Scandinavian Actuarial Journal, Land, K.
Hough, Jr. Data from Recent School Years. Journal of the American Statistical Association, Malitz, G. A Classification of Instructional Programs. Namboodiri, K. Life Table Techniques and their Applications. Orlando, FL: Academic Press. National Science Board. Undergraduate Science, Mathematics and Engineering Education.
Quetelet, L. A Treatise on Man and the Development of his Faculties, a facsimile reproduction of the English translation of Ryder, N.
American Sociological Review, Sewell, W. Haller, and A. Tuma, N. Social Dynamics: Models and Methods. San Francisco: Academic Press. Xie, Y. The Process of Becoming a Scientist. Unpublished Dissertation, University of Wisconsin. The study of human capital is a crucial issue in the attempt to develop regional strategies that increase the potential capabilities of the less favored regions in regard to their own social and economic progression.
However, the knowledge of the problem has been hampered by its relevance, its intrinsic complexity, and its multifaceted nature. One reason for this is that the subject does not depend on a single area of policymaking but rather deals with several: education, employment, and economic policy, as well as the influence of scientific and technological policy on economic and social development.
A second reason for the difficulty in treating this issue lies in the diversity, as well as in the complexity, of the indicators needed to afford an exact diagnosis of the problem for further action. In some cases the indicators are too broad to tune up appropriate reflections. All of these shortcomings have a particular significance when one attempts to understand the realities hidden under the realm of science and technology in relation to the less developed regions of Europe.
We cannot forget that these regions possess characteristics of industrialized countries and, as such, are part of global projects [i. In this study we will cover some of the key topics related to educational and employment policies, albeit in a general way, and later delve into the science and technology issues concerning human resources and their implications on socioeconomic development. The European countries share, to a great extent, an educational tradition modeled by the deep processes of great historical-cultural events, such as romanticism, Christianization, and the incorporation of realism.
The present educational guide is the result of a combination of four main approaches:. The inheritor of medieval tradition that promotes the transmission of the classical idea of culture. The approach that sees the encyclopedic view and defends the diffusion of all available knowledge. The polytechnic approach that emphasizes the transfer of skills useful for the economy and productivity. The pragmatic approach that supports the idea of the preparation of the individual to cope with the problems of ordinary life.
Broadly speaking, the European curriculum has been built within a framework of knowledge based on the disciplines, where progress is continuously being incorporated, without taking into account the global approach of looking inside the psycho-pedagogy focal point.
Along these lines, the idea of an everlasting educational crisis is present. This is due to the nature of the educational process itself, in which it is necessary to find adequate interplay between the information transmitter the teacher and the receiver the pupil , together with the essential universality of the contents being taught.
It is worth noting, paradoxically, that in a moving field like education, the application of conservative policies appear to give better results than that of innovative policies.
This implies that the evolution trend in educational affairs follows a vicious circle. In spite of the strong momentum given to education in the late s in western Europe, it is generally believed, at the present time, that European education does not fulfill the requirements raised by economic, cultural, technical, and societal needs.
This controversial issue has opened up a debate between teaching staff and public administrators about the resources deemed necessary to reach the appropriate targets. In the developed countries, education is not a first priority as it has to contend with other highly relevant issues like unemployment, the incorporation of young people into the labor force, social protection, and environmental preservation.
Consequently, the public expenditure rate on education has been decreasing in most countries see Figure 1. However, be reminded that the data, as previously mentioned, is too general and, by the lack of disaggregation level, does not allow conclusions with a good degree of acuteness for analyzing regional disequilibria.
In any case, the data shown reveal that public expenditure is smaller in countries with less development and a greater heterogeneity, and present a clear-cut geographical distribution between a highly developed north and a less developed south. Therefore, the expenditure per capita, as illustrated in Table 1 , confirms this trend: the positions at the bottom of the table are held by countries with less developed regions. Against this background the change in educational pat.
The EC Commission is aware of the need and has undertaken some steps to follow in higher education and professional training, but, at the same time, it has been looking to adapt the diverse educational systems into a common ground in order to facilitate the free circulation of skilled personnel. The economic implications of educational policies are also being recognized. Big, multinational enterprises and owner-operated organizations have expressed their views on the need for a greater number of scientists, engineers, and technicians.
This demand resists the diminishing interest of young Europeans to study in the scientific and technical domains. Therefore, there exists a social debate about the main trend to be followed in the educational process as a whole and in relation to the apparent conflict between classical culture and that oriented toward empirical and practical goals.
The debate has extended to secondary schools. In the developed western European countries, this training is strongly related to well-reputed professional skills and, therefore, asks for a separation of a more general primary school.
A major part of the blooming of the manufacturing industry in the German and Dutch regions lies in their asset of a highly skilled human capital. The situation is yet different in southern European countries, in spite of their efforts during the last few years to correct it. It seems that there are still important differences in the educational profiles of developed and less developed countries. The main differences stem from the resources earmarked, the qualifications of the teaching staff, the suitability of the facilities, the characteristics of the secondary school and its relationship with professional training, and the connection of education with the labor market.
The schooling rates of young Europeans at two ages in the EC countries are shown in Figure 2. It is worth mentioning that the differences remain current at the present time and are being distinguished by a situation of general crisis of public support to educational policies.
The forecast is, therefore, negative, in the sense that the differences are likely to remain the same or get worse. The adjustment of this trend cannot stand by single declarations of intent alone, but requires a real strategic policy with the availability of resources and appropriate goals.
On the other hand, to afford adequate response to the great variety of pressing demands, the educational system needs an important effort of flexibility and versatility.
This implies, as in many other areas of the public arena, a better bond between expanding the social and economic agents and the pervading regional and local responsibilities decentralization. It is, therefore, essential to foster the participation of these agents owners, trade unions, and regional and urban authorities in designing, launching, and steering the educational policies, mainly in professional training and higher education.
One cannot forget the high rate of unemployment for the young labor force in the less developed regions of Europe. Spain, for instance, had 50 percent of its population unemployed in the mids. Although this rate decreased during the last half of the decade, the values are still very high. Using a biological analogy, it seems to us very pertinent to favor this selection of the population by putting it in touch with the adequate environment i.
In other words, it is necessary for the socioeconomic forces to play a role in helping administrators define educational policies. Alternatively, it is not possible to tackle the problem of heterogeneity by having a recourse to a blind, common, general force, or mechanism, for selection.
Similar considerations can be applied to the employment situation. The evolution of the labor force in developed countries is characterized by the following trends:. A substantial increase in the percentage of highly skilled and white collar personnel. In some countries these professionals account for 60 percent of the active population.
A decrease, or stagnation, in the percentage of workers addressed to the primary or tertiary sectors farming and services. A remarkable reduction in the percentage of manual workers not related to agriculture , showing figures below 30 percent. Therefore, developed societies appear to be, to a great extent, middle-class societies in which there is a continuous decrease in the number of manual workers in industry and services.
However, it is not clear whether the evolution from the less developed condition to the developed one is going to follow a gradual pattern or experience more abrupt changes derived from the availability of new technologies.
The latter is already being seen in developing countries like those in Asia. So, the data indicate that in the evolution process there is no substantial increase in the percentage of industrial workers. It is noteworthy to highlight the rise in the number of qualified professionals, administrative personnel, traders, and dealers.
This pattern denotes an evolutionary trend from developing countries to that of western developed countries before reaching a labor force profile of industrialized countries. Again, this raises the conflict of world globalization with the singularities of every region. In this conflict, the market influences the international situation through the forceful behavior of multinational firms.
The wrestling of this mode of action with regional specifications and disequilibria is a key issue of reflection that pervades this paper.
In this section, we will overview some macro-structural variables that may influence innovation in EC Objective 1 Regions. As a whole, the European Community's demographic evolution of the s will remain stable at a figure of some million people.
For the period , an estimated decline of percent is expected. With respect to the figure, in absolute figures, a decrease of 12 million people is foreseen.
However, differences among regions are, and will likely be for a long time, outstanding. During the present decade, the recessive demographic trend will consolidate firmly in most northern countries—Germany, Luxembourg, Belgium, and Denmark. It is presumed that prospective new member states of the EC will belong to this category.
For three southern countries—Greece, Italy, and Portugal—a major change in population figures is not expected until the year On the other hand, France, the Netherlands, Spain, and the United Kingdom will likely undergo a moderate population increase, reaching demographic stability in the year , whereas later evolution will invert this trend back to the figures in the year Ireland is expected to have a positive demographic growth at least until Demographic trends will have a marked influence on labor markets.
The EC labor force, as a whole, will slightly increase by 0. This figure conceals the quick increase in many of the less favored regions—Ireland, Spain, Portugal, and Southern Italy—with a much more moderate growth, even a decrease, in the labor force in other member states. This does not, however, take into account the impact of immigration from countries outside the community. In absolute figures the increase in the community's labor force, based on its own demographic evolution, will only rise to 1.
This results from a 2 million increase in southern regions and a 0. From to , employment in the community grew at an annual rate of 1. Each member state registered an increase in employment between and , with great variability among them. For instance, the less favored regions in southern Spain and Portugal, to a lesser extent, enjoyed important increases in their employment figures. By sectors, the s saw the continuation of former trends of employment drift from industry to tertiary activities services.
From to , the employment percentage in the tertiary sector in the community rose from 55 to 59 percent, while industrial employment decreased from 35 to 33 percent. Although the community passed through a phase of positive employment growth, it is not at all clear if this growth was evenly distributed at the regional NUTS II level to be of any help in reducing the differences in unemployment and activity rates between more and less favored regions of the EC.
Data show that the EC unemployment rate has decreased since but still ranked at about 8. Among the factors that hinder job creation, especially in southern countries, are positive demographic growth, increased access of women to the labor market, and cyclic variation in activity, indicators combined with secular trends in the reduction of nonspecialized jobs.
On the one hand, there are 12 central regions with unemployment rates of less than 3 percent, while on the other hand 19 regions registered unemployment rates higher than 15 percent. All figures refer to Italy provides a special case. In , it had the greatest inner regional disparities among all member states; some northern and central regions, such as Emilia-Romagna and Lombardy, showed unemployment rates less than 5 percent while most of the Mezzogiorno region suffered rates higher than 20 percent.
Differences among the EC regions, with respect to income per capita, is very acute. In the income per capita of the 10 most advanced regions was 3 times higher than that of the 10 less favored regions. These differences have remained stable since even though less favored countries achieved rates of economic growth higher than the community average and raised expectations of economic convergence.
At the regional level, the average figure for the 25 less favored regions increased slightly with respect to the average EC GDP per capita. Nevertheless, there has been no progress among 10 less favored regions mainly in Greece and Portugal since the mids. Besides these disparities, there are others with regard to productivity. In a slight trend of reduction of these disparities began among member states due to the improvement of the relative productivity in Portugal and Ireland.
However, this trend stopped after Generally speaking, income per capita and unemployment differences reflect inter-regional disparities in productivity and competitiveness.
Less productive and competitive regions face problems of generating higher and more evenly distributed income and of job creation. A lack of local infrastructures, mainly suitable in regions with more central and advanced ones, and a lack of a skilled workforce are crucial factors that hinder advances in economic competitiveness.
The problem of a lack of a skilled labor force is common to all regions within the EC. However, the causes differ according to their degree of development. In the more favored regions, fair economic conditions during the last decade have resulted in an imbalance between the competencies and costs demanded by firms and what the educational systems were able to supply. An additional problem is the re-skilling needed by an aged labor force in declining industrial areas.
In less favored regions the lack of skilled personnel is due to the absence of modern and appropriate education and training facilities; the lack of cooperation of potential employers; rigid and outdated curricula; the lack of specialized and updated teaching staff; a very low degree of participation of active economic agents union, firms, regional economic boards, etc.
Lack of entrepreneurial skills and the absence of up-skilling training opportunities for the employed and unemployed are also problems widely present in these regions. From the current views of economic policy analysis, it seems evident that more and more innovation and investment in science and technology are key components for improving the competitive positions of societies.
The idea that technology is an endogenous product for economic wealth, as well as the suspicion that a science-technology system acts as a feedback mechanism fostering social and economic progress far beyond its initial value, is gaining strong support. Science, technology, and technological innovations are all abstract concepts that cannot be measured in a direct way.
Although it might be interesting from a global point of view to treat science and technology activity as a defined subunit of economic performance, it is indeed difficult to correlate the factors influencing science and technology as inputs with economic outputs.
They are usually expressed as a percentage of GDP allotted to these activities and as a number of full-time equivalent researchers per unit of active population.
In-depth analysis reveals limitations in the applicability of these indicators with regard to specificities and subtleties of microenvironments in order to afford policies from a disaggregated point of view. On the one hand, these indicators are too broad to allow the detection of the quality of the political measures undertaken on their basis.
All these difficulties are absolutely relevant for the purpose of this study, and so pervade it. Therefore, one of the conclusions of this study will ask for better homogenization of indicators in terms of regional distribution and for an improvement in the type of indicators measuring human resources, both in absolute terms and in connection with education and employment.
This information may allow the identification of the real potential in science and technology in less developed countries and regions, thus providing better insight for a comparison of these potentials with those of developed countries. By doing so, we are following similar demands of science policymakers who are increasingly asking for new science and technology indicators J. In other words, we deem essential the disposition of data measuring disequilibria, as well as the relative strengths and weaknesses needed to promote political measures for science and technology other than those traditionally applied from the developed countries.
A similar conclusion has been drawn by others. See Padzerka as cited by J. Holbrook in Science and Public Policy, Vol. For instance, Ireland is devoting between 0. Italy is allocating more than 1 percent to these activities, whereas Spain, Portugal, and Greece have traditionally lagged behind. However, these three countries are making efforts to correct this trend at different rates. See Figure 3. Regional Accountability of Spain, Base, Series.
One region, Madrid, possesses a level convergent with that of the EC average 2 percent of GDP , while none of the other regions reach 1 percent.
The inequitable model is also sustained by Italy but with a distinct shape.
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