A posztmodern marketing elvei és gyakorlata a turizmus piacán - Mátrix és turizmus (Theories and practice of the post-modern marketing on tourism market – Matrix and tourism)

Jelen tanulmány a posztmodern kor fogyasztási tendenciáit és a posztmodern marketing sajátos fejlődését elemzi, elsősorban a turizmus példáján. A szerzők a hazai és a nemzetközi szakirodalom, illetve saját kutatásaik és megfigyeléseik alapján ütköztetik az ismert és elfogadott elveket, elméleteket a gyakorlattal, és felhívják a figyelmet a marketingtevékenység alkalmazkodásának hazai problémáira. A Vezetéstudomány című folyóirat 2008/9. számában rendkívül érdekes tanulmány jelent meg Mitev Ariel Zoltán és Horváth Dóra tollából „A posztmodern marketing rózsaszirmai” címmel. A tanulmány előremutató, érdekfeszítő és minden tekintetben konstruktív, újszerű. Jelen tanulmány szerzőire is nagy hatást gyakorolt a cikk, nagyrészt felsorolt erényei miatt, de egyes esetekben kiegészítést kívánva. Mindenképpen inspirálta a továbblépést, az újabb adalékok megfogalmazását, amire ezúton e tanulmány szerzői kísérletet tettek. A cikk egyben szerves gondolati folytatása a szerzőpáros korábbi közös publikációinak, elsősorban a Marketing & Menedzsment folyóiratban megjelent cikknek. _______ In this article the author will analyze consumption tendencies of post-modern age, mainly using tourism marketing examples. Their analysis has been based on results of their own researches and researches published in Hungarian and international marketing literature. In this article they try to confront different theories of post-modern marketing and they will analyze problems of applicability of these theories in Hungarian marketing problem solving. An extremely interesting article was published in Vezetéstudomány (2008/9), written by Zoltán Mitev Ariel and Dóra Horváth, and this article, by its interesting, innovative and constructive aspect has largely influenced authors of present article to continue the path proposed in the abovementioned article. The article, in the same time, is an organic continuation of the earlier common publications of the authors, e.g. the recent article in Marketing & Menedzsment journal.

Google’s Antitrust Cases Competition Analysis in New Economy Markets

Today, global economic performance largely depends on digital ecosystems. E-commerce, cloud, social media, sharing economy are the main products of the modern innovative economic systems which are constantly raising new regulatory questions. Meanwhile the United States has an unimpeachable dominance in innovation and new technologies, as well as a large and open domestic market, the EU is only recently discovering the importance of empowering the European digital economy and aims to break down its highly fragmented cross-border online economic environment. As global economy is rapidly becoming digital, Europe’s effort to create and invest in common digital market is understandable. The comprehensive investigations launched by the European Commission into the role of social network, search engine, or sharing economy internet platforms, which are new generation technologies dominated by American firms; or the recent decision of the Court of Justice of the European Union declaring that the Commission’s US Safe Harbor Decision is invalid1 might be considered as part of an anti-American protectionist policy. However, these measures could rather be seen as part of a broader trend to foster European enterprises in technology developments.

An analysis of the on-time graduation rate in the two-year program at National Taipei Institute of Technology in Taiwan

Taiwan's technical vocational educational system includes three levels: (1) institutes of technology (two and four year programs), (2) junior colleges (two, three and five year programs), and (3) senior vocational schools. Two-year junior colleges enroll their students through two channels: (1) based on results of the Particular Screening Entrance Examination (PSEE), (2) based on the Joint College Entrance Examination (JCEE). The PSEE has two categories: Category I includes on-time graduates with excellent performance, which means that they are within the top ten of their classes; Category II students include award-winning students in talent contests who have achieved a minimum grade point average of 75%. The JCEE is a regular entrance examination given to any senior vocation school graduate.^ Basic courses have a great impact on the students' academic performance. The purpose of the study was to focus on the effectiveness of teaching mathematics in two-year junior colleges and to analyze and correlate the results of two-year junior college students' performance in calculus and on-time graduation. The target group consisted of 521 students enrolled at National Taipei Institute of Technology in 1993.^ Calculus is a very important course for engineering majors in two-year junior colleges and has a great impact on the students' academic performance. This retrospective study showed that there was a correlation between students' performance in calculus and on-time graduation after two years of study.^ The conclusions of the study urge the Ministry of Education to reform two-year junior college curriculum standards to emphasize basic rudimentary courses. It is recommended that engineering majors receive three hours of calculus per week as the current requirement of only two hours per week is inadequate. The future job market will require a technologically advanced labor force that can be trained in a higher education system. More channels of higher education for two-year junior college graduates should be made available for those wishing to pursue bachelor degrees. Additional work in calculus will not only enhance the opportunities for two-year junior college graduates to continue their pursuit of an advanced academic degree, but also serve them well as they seek career advancement. ^

The applied computer science of economic analyses: Internet prioritization and Internet pricing, and software engineering and software pricing for the mass market

This research examines evolving issues in applied computer science and applies economic and business analyses as well. There are two main areas. The first is internetwork communications as embodied by the Internet. The goal of the research is to devise an efficient pricing, prioritization, and incentivization plan that could be realistically implemented on the existing infrastructure. Criteria include practical and economic efficiency, and proper incentives for both users and providers. Background information on the evolution and functional operation of the Internet is given, and relevant literature is surveyed and analyzed. Economic analysis is performed on the incentive implications of the current pricing structure and organization. The problems are identified, and minimally disruptive solutions are proposed for all levels of implementation to the lowest level protocol. Practical issues are considered and performance analyses are done. The second area of research is mass market software engineering, and how this differs from classical software engineering. Software life-cycle revenues are analyzed and software pricing and timing implications are derived. A profit maximizing methodology is developed to select or defer the development of software features for inclusion in a given release. An iterative model of the stages of the software development process is developed, taking into account new communications capabilities as well as profitability. ^

Using extreme value theory to value stock market returns

Extreme stock price movements are of great concern to both investors and the entire economy. For investors, a single negative return, or a combination of several smaller returns, can possible wipe out so much capital that the firm or portfolio becomes illiquid or insolvent. If enough investors experience this loss, it could shock the entire economy. An example of such a case is the stock market crash of 1987. Furthermore, there has been a lot of recent interest regarding the increasing volatility of stock prices. ^ This study presents an analysis of extreme stock price movements. The data utilized was the daily returns for the Standard and Poor's 500 index from January 3, 1978 to May 31, 2001. Research questions were analyzed using the statistical models provided by extreme value theory. One of the difficulties in examining stock price data is that there is no consensus regarding the correct shape of the distribution function generating the data. An advantage with extreme value theory is that no detailed knowledge of this distribution function is required to apply the asymptotic theory. We focus on the tail of the distribution. ^ Extreme value theory allows us to estimate a tail index, which we use to derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of stock prices. There are three possible limit laws for the maximum: Gumbel (thick-tailed), Fréchet (thin-tailed) or Weibull (no tail). Results indicated that extreme returns during the time period studied follow a Fréchet distribution. Thus, this study finds that extreme value analysis is a valuable tool for examining stock price movements and can be more efficient than the usual variance in measuring risk. ^

Principal component and second generation wavelet analysis of Treasury yield curve evolution

Prices of U.S. Treasury securities vary over time and across maturities. When the market in Treasurys is sufficiently complete and frictionless, these prices may be modeled by a function time and maturity. A cross-section of this function for time held fixed is called the yield curve; the aggregate of these sections is the evolution of the yield curve. This dissertation studies aspects of this evolution. ^ There are two complementary approaches to the study of yield curve evolution here. The first is principal components analysis; the second is wavelet analysis. In both approaches both the time and maturity variables are discretized. In principal components analysis the vectors of yield curve shifts are viewed as observations of a multivariate normal distribution. The resulting covariance matrix is diagonalized; the resulting eigenvalues and eigenvectors (the principal components) are used to draw inferences about the yield curve evolution. ^ In wavelet analysis, the vectors of shifts are resolved into hierarchies of localized fundamental shifts (wavelets) that leave specified global properties invariant (average change and duration change). The hierarchies relate to the degree of localization with movements restricted to a single maturity at the base and general movements at the apex. Second generation wavelet techniques allow better adaptation of the model to economic observables. Statistically, the wavelet approach is inherently nonparametric while the wavelets themselves are better adapted to describing a complete market. ^ Principal components analysis provides information on the dimension of the yield curve process. While there is no clear demarkation between operative factors and noise, the top six principal components pick up 99% of total interest rate variation 95% of the time. An economically justified basis of this process is hard to find; for example a simple linear model will not suffice for the first principal component and the shape of this component is nonstationary. ^ Wavelet analysis works more directly with yield curve observations than principal components analysis. In fact the complete process from bond data to multiresolution is presented, including the dedicated Perl programs and the details of the portfolio metrics and specially adapted wavelet construction. The result is more robust statistics which provide balance to the more fragile principal components analysis. ^

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. ^ In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. ^ The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area. ^

Three essays on the interrelationships among financial restatements, corporate governance, market microstructure and the firm's rate of return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

What makes online grocers work? A case study analysis of factors contributing to online grocery store profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. ^ To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. ^ Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. ^ The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance. ^

Market valuation of environmental performance

This research investigated the general association between corporate environmental performance and the firms’ annual returns independent of any particular environmental event. The association analysis was based on the most recent environmental data for the years 2006, 2007, and 2008. The results indicated that while some environmental variables were significantly associated with firms’ returns, the majority were not. The results also indicated that environmental concerns were more likely to be associated with increase in the firm value than were environmental strengths; however, there were no mean differences between firms whose environmental performance increased as compared with those whose performance deteriorated. Overall, the results provided support for the perspective that environmental strengths require firm expenditures that place additional financial burdens on firms, resulting in lower stock returns.^

Analysis of Housing Partnerships using the Balanced Scorecard framework

Housing Partnerships (HPs) are collaborative arrangements that assist communities in the delivery of affordable housing by combining the strengths of the public and private sectors. They emerged in several states, counties, and cities in the eighties as innovative solutions to the challenges in affordable housing resulting from changing dynamics of delivery and production. ^ My study examines HPs with particular emphasis upon the identification of those factors associated with the successful performance of their mission of affordable housing. I will use the Balanced Scorecard (BSC) framework in this study. The identification of performance factors facilitates a better understanding of how HPs can be successful in achieving their mission. The identification of performance factors is significant in the context of the current economic environment because HPs can be viewed as innovative institutional mechanisms in the provision of affordable housing. ^ The present study uses a mixed methods research approach, drawing on data from the IRS Form 990 tax returns, a survey of the chief executives of HPs, and other secondary sources. The data analysis is framed according to the four perspectives of BSC: the financial, customer, internal business, and learning and growth. Financially, revenue diversification affects the financial health of HPs and overall performance. Although HPs depend on private and government funding, they also depend on service fees to carry out their mission. From a customer perspective, the HPs mainly serve low and moderate income households, although some serve specific groups such as seniors, homeless, veterans, and victims of domestic violence. From an internal business perspective, HPs’ programs are oriented toward affordable housing needs, undertaking not only traditional activities such as construction, loan provision, etc., but also advocacy and educational programs. From an employee and learning growth perspective, the HPs are small in staff size, but undertake a range of activities with the help of volunteers. Every part of the HP is developed to maximize resources, knowledge, and skills in order to assist communities in the delivery of affordable housing and related needs. Overall, housing partnerships have played a key role in affordable housing despite the housing market downturn since 2006. Their expenses on affordable housing activities increased despite the decrease in their revenues.^

A comprehensive study of bankruptcy prediction: Accounting ratios, market variables, and microstructure

Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

Three essays on a longitudinal analysis of business start-ups using the Kauffman Firm Survey

This dissertation focused on the longitudinal analysis of business start-ups using three waves of data from the Kauffman Firm Survey. ^ The first essay used the data from years 2004-2008, and examined the simultaneous relationship between a firm's capital structure, human resource policies, and its impact on the level of innovation. The firm leverage was calculated as, debt divided by total financial resources. Index of employee well-being was determined by a set of nine dichotomous questions asked in the survey. A negative binomial fixed effects model was used to analyze the effect of employee well-being and leverage on the count data of patents and copyrights, which were used as a proxy for innovation. The paper demonstrated that employee well-being positively affects the firm's innovation, while a higher leverage ratio had a negative impact on the innovation. No significant relation was found between leverage and employee well-being.^ The second essay used the data from years 2004-2009, and inquired whether a higher entrepreneurial speed of learning is desirable, and whether there is a linkage between the speed of learning and growth rate of the firm. The change in the speed of learning was measured using a pooled OLS estimator in repeated cross-sections. There was evidence of a declining speed of learning over time, and it was concluded that a higher speed of learning is not necessarily a good thing, because speed of learning is contingent on the entrepreneur's initial knowledge, and the precision of the signals he receives from the market. Also, there was no reason to expect speed of learning to be related to the growth of the firm in one direction over another.^ The third essay used the data from years 2004-2010, and determined the timing of diversification activities by the business start-ups. It captured when a start-up diversified for the first time, and explored the association between an early diversification strategy adopted by a firm, and its survival rate. A semi-parametric Cox proportional hazard model was used to examine the survival pattern. The results demonstrated that firms diversifying at an early stage in their lives show a higher survival rate; however, this effect fades over time.^

Segmenting The Hotel Market

Marketing involves satisfying consumers' needs and wants with products of two types, goods and services. Hotels provide an intangible product, referred to as a service. On the other hand, toothpaste is an example of a product that is a tangible good. The lifeblood of both is marketing. Different as they are, each utilizes market segmentation and positioning. The segmentation movement in the hotel industry is analyzed in the light of marketing principles developed from the consumer goods sector. The analysis suggests that the hotel industry is engaged in a multiple segmentation strategy

Primary Market Research: Its Role In Feaslblllty Studies

Primary market research and sound marketing analysis based on this research can make a significant contribution to the accuracy and usefulness of feasibility studies in planning for travel, leisure, tourism, recreation/entertainment, and hospitality development. The author contends that changes in the marketplace will increase the need for primary marketing research in the future.