This section proposes that for re-entrant DMMs, returning to markets similar to their home market may mean that less time is necessary to unlearn pre-established routines or adapt to changes that may have occurred in the host environment. DMMs may also (re)enter non-developed market environments that may have undergone a series of institutional transitions during the time-out period, yet this may also mean that some of the intangible resources lost upon exit (i.e. business relationships, distribution partnerships) may be harder to recover in institutionally idiosyncratic environments than they would be when returning to developed host markets. DMMs are likely to be early re-entrants when returning to markets more institutionally similar to their home markets, i.e. DMMs are more likely to be early re-entrants into developed host markets. In regards to EMMs’ re-entry timing, since pioneering is probably not an option for most of these firms, particularly when entering or re-entering developed markets, EMMs are expected to follow a gradual expansion process as they learn about foreign markets and benefit from being market followers (Isobe et al., 2000; Da Rocha et al., 2012). Isobe et al. (2000) added that international expansion depends not only on the ability of firms to innovate and exploit technological advantages (i.e. DMMs); noting that being able to identify the institutional idiosyncrasies in host markets and secure strong relationships with local communities is increasingly viewed as a source of competitive advantage and an important motivation for early market entry in emerging market environments (see also Da Rocha et al., 2012; Henisz, 2003). EMMs are expected to possess such advantages when entering other emerging markets (Isobe et al., 2000; Da Rocha et al., 2012; Yang et al., 2009) and this may also apply to EMM re-entrants. In fact, for re-entrants this contention may be even more valid as re-entrant EMMs manage the uncertainties associated with re-entry following the previously failed attempt to perform in the host market, in which case, a more risk-averse attitude would be to wait longer prior to re-entering markets that are governed by potentially different institutional rules and norms as compared to the home market.
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A lack of information pertaining to the determinants of capacity utilisation is an important constraint on our analysis. The difficulty in measuring capacity utilisation is indicated as a cause of this constraint (see Shaikh & Moudud, 2004; Saikia, 2012). Despite this difficulty, findings in this area showed that the existence of unused and/or underutilized capacity is the main incentive that stimulates many firms to begin exporting (see Ahmed et al., 2006; Greenaway & Kneller, 2007; Julian & Ali, 2009), that is most firms across sectors and countries operate with a slack or spare capacity. Following the description of the firm heterogeneity phenomenon and participation in foreign market proposed by Melitz (2003) where firm’s export entry and exit are determined by the interplay of two factors: firm level variation in productivity, and sunk cost, a shift in competitive market structure should bring in a decline in underutilization of capacity and yet capacity constraint for some smaller firms due to economies of scale and fixed costs associated with exporting activities. In this study’s context, the maximisation of underutilized capacity is expected to occur from an increasing exposure in foreign markets. Firm level export intensity is expected to contribute significantly and positively to firm capacity utilisation which is demonstrated in less capacity underutilization.
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Firm size (SIZE), has been associated with firms possessing more resources to commit to foreign markets; we measure firm size as the value of total assets, with a logarithm transformation at the time of (t-1) re-entry (Gao and Pan, 2010). Since older firms are more likely to show signs of inertia that may prevent them from changing their operation mode patterns (Guillén, 2002), firm age (AGE) was computed as the number of years from when the firm had been founded up to one year prior to re- entry. Some scholars (e.g., Hutzschenreuter et al., 2007) suggest that management can alter the direction of an MNE’s international path or re-shape it altogether, thus MGMT-CHG measures whether the CEO has changed up to three years prior to re-entry. MNEs which have maintained close ties with host markets by operating there via other businesses may be more confident with their host market operations and perhaps more likely to increase commitment. Hence, we documented whether a firm has been present in the host market through a different division in the same/different sector (ALREADY_PRESENT) at the time of re-entry. Since organisational forgetfulness (Rumelt, 1995) reduces the effectiveness of prior experience, we also control for the duration of the time-out period (TIME-OUT), i.e. the number of years between exit and re-entry.
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Although expanding foreign markets provide opportunities for all firms (as H1b above suggests), for small firms this is something of a mixed blessing. Smaller firms and those further from the productivity frontier are less likely to be able to compete effectively with the increased competition that is likely to accompany increased foreign demand. Such marginal firms may find themselves squeezed out of export markets as their (relative) productivity levels fall relative to the average, as new, more capital-intensive and more productive entrants move into the market. Similarly, smaller and less productive firms are more likely than larger, more capital-intensive and more productive enterprises to exit export markets when domestic demand rises. Such firms are more likely to be ‘opportunistic’ exporters: for them exporting is often a marginal exercise, and one which is easily reversed when domestic demand conditions improve relative to export markets. Precisely such a scenario is outlined by Crick (2003), and demonstrated for British new technology-based firms by Love and Ganotakis (2013). And in their analysis of Chilean firms, Blum et al. (2013) find that intermittent exporters tend to have lower capital intensity, possibly related to their lower productivity. By contrast, larger and more productive firms are less likely to be adversely affected by increased demand in expanding export markets, and are also more able to cope with increased production in times of rising domestic demand without the need to switch out of export markets, an option which may be more difficult for smaller firms and those further from the productivity frontier. In addition, larger and more capital-intensive firms may suffer from a degree of inertia or sclerotic thinking as well as having longer-term planning horizons than their smaller, more nimble counterparts, making them less reactive to short-term changes in demand conditions. This leads to our next hypothesis:
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For five incubatees, exit from the incubator was not into a permanent investment mode, but rather was a withdrawal from having a presence on the ground in China. C6, a UK local government office, withdrew from the market because, during a reduction in public sector budgets, its international activities came under scrutiny and a presence in China could no longer be justified. C10, a firm of consulting engineers, was also affected by the global slow down. The resultant change in strategy was to withdraw from the Chinese market completely and focus on other markets. In a similar vein, C24 found itself commercially over-stretched and had to pull back from China to concentrate on existing and newly acquired operations elsewhere. C13 was a consortium of four firms focusing on the airports sector, which received UK government funding as part of an export promotion programme. When this funding came to an end, two of its number left the China market and two remained active via existing operations. Finally, C17, a university, wished to terminate the relationship with an employee who was not performing, and decided to leave the scheme whilst continuing to coordinate its partnerships with Chinese universities from the UK.
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Our data are from various registers maintained by Statistics Finland. The primary data source is a panel data on manufacturing plants based on the Longitudinal Data of Plants in Manufacturing (LDPM), which is available for the period 1974-2005. The LDPM data include information, for example, on plant-level employment, working hours, value added, production, exports, foreign ownership, investments, capital stock and wages. In addition, there is information on industry and region of the plant and the number of plants in the firm. The age information of the plant can be supplemented from the Business Register. There is a break in the LDPM data set between the years 1994-1995, when size threshold for plants increased from 5 to 20 persons (actually, plants belonging to firms with at least 20 employees). Our estimation sample consists of manufacturing plants that reach the 20 employees threshold for the first time during the period 1980-2005. In fact, this group may include both new and continuing establishments that have already been in operation with less than 20 employees. As a result, it is important to control for the age of these plants. In the duration analysis we pool multiple cohorts of new plants over the period 1980-2005.
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Entry barriers; Economic, procedural, regulatory, or technological factors that obstruct or restrict entry of new firms into an industry or market. Such barriers may take the form of (1) clear product differentiation, necessitating heavy advertising expenditure to introduce new products, (2) economies of scale, necessitating heavy investment in large plants to achieve competitive pricing, (3) restricted access to distribution channels, (4) collusion on pricing and other restrictive trade practices (such as full-line forcing) by the producers or suppliers, (5) well established brands, or (6) fierce competition. Barriers to exit, paradoxically, also serve as barriers to entry because they make it difficult to cut one's losses and run. This is called barriers to competition, entry barriers, or market entry barriers. The barriers that concern Bolletje the most are point three and four, the other barriers are not problematic for Bolletje. Profit remittance barriers; restrictions on the repatriation earnings. Bolletje wants to be able to repatriate its earnings from foreign markets.
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Although expanding foreign markets provide opportunities for all firms (as H1b above suggests), for small firms this is something of a mixed blessing. Smaller firms and those further from the productiv- ity frontier are less likely to be able to compete effectively with the increased competition that is likely to accompany increased foreign demand. Such marginal firms may find themselves squeezed out of export markets as their (relative) productivity levels fall relative to the average, as new, more capital- intensive and more productive entrants move into the market. Similarly, smaller and less productive firms are more likely than larger, more capital- intensive and more productive enterprises to exit export markets when domestic demand rises. Such firms are more likely to be ‘opportunistic’ exporters: for them exporting is often a marginal exercise, and one which is easily reversed when domestic demand conditions improve relative to export markets. Pre- cisely such a scenario is outlined by Crick (2003), and demonstrated for British new technology-based firms by Love and Ganotakis (2013). And in their analysis of Chilean firms, Blum et al. (2013) find that intermittent exporters tend to have lower capital intensity, possibly related to their lower productiv- ity. By contrast, larger and more productive firms are less likely to be adversely affected by increased demand in expanding export markets, and are also more able to cope with increased production in times of rising domestic demand without the need to switch out of export markets, an option which may be more difficult for smaller firms and those further from the productivity frontier. In addition, larger and more capital-intensive firms may suffer from a degree of inertia or sclerotic thinking as well as having longer-term planning horizons than their smaller, more nimble counterparts, making them less reactive to short-term changes in demand con- ditions. This leads to our next hypothesis:
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Since we focus on domestic competitive pressure as the main determinant of the multinational’s entry decision, our work is related to the large literature on innovation and market structure. Various papers have analyzed the link between a …rm’s incentives to innovate and the intensity of competition. There are dif- ferent measures for the intensity of competition. According to Arrow (1962), the main determinant is the number of …rms in a given industry and competi- tion is more intense the higher the number of …rms. Aghion, Harris and Vickers (1995) emphasize the mode of competition, rather than the number of …rms, They argue that Cournot competition is less intense than Bertrand competition, since Cournot competition normally leads to lower output and higher prices than Bertrand competition. Boone (2000) de…nes a number of axioms that a good measure of market competition must satisfy. He lists the switch from Cournot to Bertrand competition and a reduction in travel costs on a Hotelling Beach as well-known examples of such parameterizations of competition.
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Foreign market entry modes, culture, communication, and the relation that exists among these three topics are all relevant for this research. The study’s ultimate goal is to provide ESPS with a new kind of model that it can both use to enter the German market and transform into a more general model when it wants to enter other foreign markets. To provide such a model business, this research also widely discusses modelling. With regard to communication, channels and customer relationships are more important than the other building blocks of the business model canvas developed by Osterwalder and Pigneur (2010). Channels and customer relationships can also be related to culture, as has been shown in the literature review presented above. Culture is further divided into the different perspectives mentioned by Hofstede (1980). To eventually translate the literature and information into a model for ESPS, it is necessary to know more about ESPS. What does ESPS stands for? What value can it deliver and what is its ultimate goal? Barney’s (1991) VRIO framework is investigated and explained to gain these insights. The framework provides the most information about ESPS’s actual business. The theory also clarifies the main components of a business that will generate success and eventually sustainability. To apply the VRIO framework and adapt the theory to ESPS, internal interviews are conducted using questions that explore these four components of the business. The results reveal more about the company’s vision for entering a foreign market such as the German market. What will its competitive advantage be compared to its competitors in the German market? What could eventually create a sustainable competitive advantage and by that a successful factor for entering this foreign market? All of this information stems from academic papers that have been found using Google Scholar. The information has been analysed utilizing the literature review method developed
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In table 7 we present estimates from two other models concerning the full sample of data in which we aggregate over NAICS industries to see if our findings hold more generally and whether an alternative econometric specification might lead to different results. Specifically, we consider a count model in the spirit of Keller and Levinson (2002) who investigated the number of new foreign- owned plants as a function of abatement costs to determine the effect of environmental-related compliance costs on the location of foreign direct investments. Some theoretical justification of this model can be found in the application of Becker and Henderson (2000) who consider a supply and demand relationship concerning new plant “births” in a given area to better understand how the status of attainment and nonattainment of air quality standards (which perhaps induces differences the stringency of regulation) affect new firms’ location decisions. In column (1), we show that when estimating a model involving the number of TRI-reporting entrants via PPML, the sign and significance of all covariates is largely unchanged. That is also true if we consider a Tobit model in which the dependent variable is the number of entrants that report to the TRI, as presented in column (2). In general, the higher the percent of nonwhite residents, the higher the expected number of TRI entrants in a tract. Agglomeration effects are important for TRI reporters, but not for other TRI-like firms and the results here align with the conditional logit results. 21
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From 1989 to 1996 the research area labelled entrepreneurial internationalization emerged. It deals with entrepreneurship that crosses national borders; incorporating aspects of venture type, internationalization, networks and social capital, organizational issues, and entrepreneurship (Jones et al., 2011, p. 635). A vital element in this sense is explaining why, how, and through what means (capabilities) organizations become engaged in cross-border business. Venture type explores the characteristics of an organi- zation that enables it to compete internationally (Jones et al., 2011, p. 636), while inter- nationalization examines the patterns and processes of international expansion, and diversity of firm’s mode of entry, as well as the influences and outcomes of international- ization (Jones et al., 2011, p. 638). Networks and social capital focus on how the firm’s network ties influence foreign market entry and entry modes, while research covering organizational issues and entrepreneurship incorporate studies on organizational per- formance, orientation, knowledge and capabilities from an entrepreneurial international- ization perspective, and international corporate entrepreneurship (Jones et al., 2011, p. 640).
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We present the main results from estimating a hazard model using Equation (4) in two tables. Table 2 presents the model without the control variable, AllRet, while the model in Table 3 includes AllRet. Each table has four specifications (Models 1 to 4), depending on the chosen set of control variables. We include six variables – MktRet, MktVol, Female, Age, Burst, and DurAway – and the aforementioned fixed effects throughout the specification, while experience measures other than returns – InvSiz, ZeroTrd, SglStock, and Nokia – are considered in order. The coefficients of our main variable (IniRet) − being reported in terms of the odds ratios − are consistently positive and statistically significant, irrespective of controlling for other experience measures and accounting for the fixed effects of investment size, exit time, and zip code. The economic magnitude of the coefficients is interpreted as one unit increase in IniRet leading to an increase in the estimated odds of re-entry by 1.44 to 1.68 times. For the investor who has the sample average of re-entry probability (36.57%), this impact amounts to more than 16 percentage points increase in re-entry rate.
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One of our goals in this paper is to explain the observed lack of size dependence in mutual fund performance. Our assumption about the competitive nature of the market, i.e. that funds must remain competitive, leads to a natural definition of performance; the return on investment for a mutual fund investor. This return is defined as the change in net asset value (NAV) of the mutual fund and is reported monthly in the data set 15 . Similarly, we define skill (α) as the excess returns above a benchmark, the S&P 500 index for instance. This definition of skill differs from the approach used by some researchers, such as Fama and French (2010). They investigate skill by decomposing the returns using three factor (Fama and French, 1993) and four factor (Carhart, 1997) models. It is hard to believe that most investors use such metrics to compare fund performances and it is even harder to believe that investors can actually reproduce the market performance defined by these models. It is much more reasonable to assume that an investor compares the fund’s performance to
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The rationale for the bank to penetrate the Gambia market was myriad and numerous but core reasons according to the management that responded to this field interview is that the bank wants to expand its revenue by diversifying its investment after confronted by internal competition, regardless of the size of the country.As the Gambia is considered as a tourist hub and one of the most peaceful countries on the continent of Africa which also recently discovered oil resources and because this promising wealth the bank decided to penetrate to the market.Another important motive highlighted by the management of the bank is that the Federation of West African Chambers of Commerce and Industry has incentives financial institution to expand their business operation in other to facilitate the process Africa integration so that customers and clientele can be served by this institution wheresoever they are residing.
The study of volatility is of concern to investors, regulators and policy makers for many reasons. Financial market volatility can have a wide repercussion on the economy because of the link between financial market uncertainty and public confidence. Market estimates of volatility are used as an indicator of the vulnerability of financial markets. Excessive volatility weakens the usefulness of stock prices as signal about the true intrinsic value of the firm. It is expected that extreme volatility in equity market could hinder the functioning of the financial system and lead to the introduction of structural and regulatory changes (Joshi and Pandya, 2008). One of the changes adopted by many emerging economies in Latin America and Asia is the opening the market for foreign investors.
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topological information of the camera network. They employ the entry/exit models to correlate objects’ transition time between the related camera FOVs. [Makris04] used a node to represent each entry/exit zone in the resulted graph, while [Kim09] used a node to represent each pair of entry/exit zones in the graph model. The constructed model works on multi-camera tracking and does not rely on correspondence between trajectories. Makris et al. stated that correlation is inappropriate for multi-model distribution. In other words, these models are not appropriate for high traffic places where the moving objects have a substantial variation in speed.
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This work extends niche overlap theory by identifying a setting characterized by well-defined niches in which a specialized organizational form has emerged and grown rapidly. This specialist also possesses a competitive advantage over generalists within this market since it behaves like a focused factory and enjoys significantly lower operating costs as a result. By manipulating patient-level datasets from the state of Florida, we were able to measure competition, market demand, and firm entry/exit with a higher level of precision than previous studies in this area. Both the characteristics of this market and the availability of this detailed data make this an ideal setting to test these theories from the literature on macro-organizational behavior. Yet this setting is also interesting from the perspective of health services research because surgery centers represent just one example of specialized providers that have caused a variety of services to migrate away from the general hospital.
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Zone section consist of a controller LPC2148 with ARM7 core, this zone section consist of different kind of zones. Each zone is having one entry and one exit, Infrared transmitter (torch) and Infrared receiver(photo diode) are connected at the entry and exit point, this IR transmitter and IR receiver should be in line of sight so whenever an obstacle occurs between this transmitter and receiver it will make the respective pin of the micro controller low and micro controller will send a message to the robot through the RF transmitter once a message is received by the robot it will slow down the speed with the help of motors placed at the back wheels of the car. One LCD is interfaced with LPC2148 controller. UART0 of this Micro controller is connected with PC followed by Web cam, to
Panel A reports descriptive statistics at the account level for all investors in our database as well as the primary sample used for our main analyses. Panel B presents summary statistics for the panel data of our primary sample about all explanatory variables used in our main regressions. Panel C presents the correlation matrix for the main explanatory variables with the statistically significant (at the 1% level) numbers in gray. IniRet, the main explanatory variable of interest, is the return in the first month of investing. I(IniRet < 0) is a dummy variable that equals 1 if IniRet < 0, and 0 otherwise. Likewise, I(IniRet ≥ 0) is a dummy variable that equals 1 if IniRet ≥ 0. AllRet is the value-weighted average of monthly returns during the entire period of investing between entry and exit, RecRet is the return in the last month of investing, and RealRet is the return during the actual period of investing. Saliency is an absolute difference between the initial return and the average return for the duration of investing, divided by the absolute value of average returns. Vicinity is a dummy variable that equals 1 if an investor resides in the same municipality where the company’s headquarters is located. InvSiz is investment size, defined as the log of average portfolio holdings. ZeroTrd is a dummy variable that equals 1 if the investor does not trade between initial purchases and exiting the market, and 0 otherwise. SglStock is a dummy variable that equals 1 if the investor only owns one stock. Nokia is a dummy variable equal to 1 if an investor initiates investment by purchasing Nokia stock . MktRet and MktVol are the monthly return and volatility (standard deviation of daily returns) on the Finnish stock market (OMX Helsinki Index). Age is investor age (in years) at the beginning of sample. Minor is a dummy variable that equals 1 if the account holder is below 16 years of age. Old is a dummy variable that equals 1 if investor is older than 50. InvSiz_H is a dummy variable that equals 1 if InvSiz is greater than the sample median. Helsinki is a dummy variable that equals 1 if an investor resides in Helsinki. Burst is a dummy variable, defined as 1 if the time is after the dotcom bubble burst (April 2000). DurAway is a discrete time variable defined as the number of months for which the investor is absent from the stock market. IVol and ISkew are the initial stock’s idiosyncratic volatility and skewness, respectively. Stock market returns a month before-, on-, after the entry month is Mkt_bf, Mkt_entry, and Mkt_af, respectively. Ret_entry is the past 3-month return of the initial stock, and Value is the indicator of the initial stock being a value stock (i.e., the book-to-market ratio is higher than the sample median). Option is a dummy variable that equals to 1 if an investor ever traded an option during our sample period. There are 276,470 investor- months (9,435 investors) in our primary sample.
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