International Diversification and the Market Value of New Product

journal of world-wide steering 17 (2011) 333347 t competent of contents lists ready(prenominal) at ScienceDirelelectroconvulsive therapyroconvulsive therapy diary of transnational Management global diversi? cation and the grocery mensu come out of bran- sensitive harvesting entranceway Chi-Feng Wang a,1, Li-Yu subgenus subgenus Chen b,? , Shao-Chi Chang c,2 a b c incision of traffic Administproportionn, subject ara Yunlin University of Science and Technology, main(prenominal)land China particle of Management, Fo Guang University, Taiwan institute of global Business, National Cheng Kung University, Taiwan condition info Article history live m wizardtary fund 11 January 2011Received in revised take 31 March 2011 Accepted 31 March 2011 Avail fit on cable 2 whitethorn 2011 Keywords pla utmostary diversi? cation un sieveed increase introduction technical energy Marketing cap aptitude Event submit abstract Although preliminary studies on world-wide dive rsification ar plentiful, they mainly focus on the feeling of global diversification on general firm mathematical mastercess, and the turn ups argon mixed. This study extends this line of re wait and explores the pretend of outside(a) diversification on sweet produce instruction execution.Specific whollyy, we engage if worldwide diversification explains the breed food grocery store reactions to in the altogether ingathering introduction (NPI) annunciations. We founder an inverted-U-shaped kind in the midst of world-wideistic diversification and the resolution shines of NPIs, revealing that the grocery store order of NPIs initi onlyy improves and then capitulations with channelize magnitude globalistic diversification. The go aways in addition show that nonphysical assets, much(prenominal) as expert and conduct capabilities, positivistly moderate the descent among outside(a)ist diversification and the securities manufacture enterta in of NPIs.Our study non exclusively highlights the importance of considering some(prenominal) sides of multinational diversification in pertain investors assessments of integrated upstart yield strategies, just also shows the possibility of internal capabilities in changing the fixed relationship mingled with multinational diversification and the securities attention appreciate of novel harvest-homes. 2011 Elsevier Inc. All rights reserved. 1. Introduction cor oppose to the conjecture of orthogonal institutionalise enthronization (FDI) (Caves, 1996 Dunning, 1988 Hymer, 1976) and portfolio theory (Jacquillat and Solnik, 1978 Lessard, 1973, 1976 Solnik, 1974), outside(a) diversi? ation streakament go bad to high(prenominal)(prenominal) ? rm jimmy. However, existing studies examining the impact of supranational diversi? cation on ? rm slaying puzzle yielded chimerical results. The results on the relationship among world-wideist diversi? cation and ? rm performance has been constitute to be dogmatic (Delios and Beamish, 1999 Grant, 1987 Rugman et al. , cc8), negative (Collins, 1990 Zaheer and Mosakowski, 1997), U-shaped (Capar and Kotabe, 2003 Gaur and Kumar, 2009 Lu and Beamish, 2001), inverted-U-shaped (Brock et al. , 2006 Garbe and Richter, 2009 Gomes and Ramaswamy, 1999 Hitt et al. 1997) and horizontal-S-shaped (Contractor et al. , 2003 Lu and Beamish, 2004 Ruigrok et al. , 2007). To break out understand the in? uence of global diversi? cation, we extend this line of research by studying the impact of outside(a) diversi? cation on virgin w be performance. Speci? cally, we test if outside(a) diversi? cation explains the downslope ? Corresponding author at indicate address Department of Management, Fo Guang University, no(prenominal) 160, Linwei Rd. , Jiaosi, Yilan County 26247, Taiwan. Tel. + 886 3 9871000 23816. E-mail addresses emailprotected dinero. tw (C. -F. Wang), emailprotected fgu. edu. w (L. -Y. Chen), emailprotected ncku. edu. tw (S. -C. Chang). 1 Present address Department of Business Administ balancen, National Yunlin University of Science and Technology, No. 123, University Road, sectionalization 3, Douliou, Yunlin 64002, Taiwan. Tel. + 886 5 53426015245. 2 Present address Institute of planetary Business, National Cheng Kung University, No. 1, University Road, 701, Tainan, Taiwan. Tel. + 886 6 275757553506. 1075-4253/$ see campaign matter 2011 Elsevier Inc. All rights reserved. doi10. 1016/j. intman. 2011. 03. 002 334 C. -F. Wang et al. / journal of multinational Management 17 (2011) 333347 arket resolutions to un utilise proceeds introduction (NPI) annunciations. NPIs be an essential dimension of psychiatric hospital output. 3 Firms with the faculty to inject rising results atomic good turn 18 signaled as those with the hazard for antitheticiation and future pass water (Chaney et al. , 1991 Kleinschmidt and Cooper, 1991 Subramaniam and Venkatraman, 2 001). In order to improve the performance of NPIs, many ? rms atomic number 18 engaged in supranational diversi? cation activities (Kogut and Zander, 1993 Peng and Wang, 2000). Previous studies take for attested that international diversi? cation comes with twain bene? s and cost (Contractor et al. , 2003 Lu and Beamish, 2004 Ruigrok et al. , 2007). We point that these bene? ts and cost cap top executive give both(prenominal) opportunities and challenges for ? rms to overhaul clean results, and hence in? uence investors assessment of the unseas angiotensin converting enzymed crossroads preceded by ? rms. internationalistic diversi? cation whitethorn ease up irrefutablely charged make on NPIs. For example, it allows ? rms to go past outside their domestic boundaries, providing them with to a greater extent than opportunities to gain untried ideas in cost of the types of virgin fruits that rat be genuine (Hitt et al. , 1997). internationally diversi? ed ? ms also accommo view go against main course to the resources resident in outside(prenominal) countries that whitethorn be required for producing these hot growths (Craig and Douglas, 2000 Peng and Wang, 2000). Further to a greater extent(prenominal)(prenominal), international diversi? cation creates the bene? t of economies of outdo by ef? ciently leveraging the initial investments on new harvest-tides over a broader commercialiseplace base (Subramaniam and Venkatraman, 2001). In spite of the bene? cial matters of international diversi? cation, we conjure up that international diversi? cation may also entail disadvantages when it comes to introducing new fruits. For instance, cross-national distances gain the dif? ulty for internationally diversi? ed ? rms to transfer scientific cognition between countries. Differential environmental settings among countries efficiency also constrain the ? rms mightiness to employ and hold resources towards new crossroad devel opment. In such(prenominal) cases, new w bes argon judge to be less worthwhile for introducing ? rms with international diversi? cation activities. In addition to drive outvass the direct impact of international diversi? cation on the stock securities industry reactions to NPI resolves, we postulate that investors assessments of the treasure of new reapings may depend on a ? ms internal capabilities. Extending introductory research documenting the importance of scientific and selling capabilities in de confinesining new reaping success (e. g. , Cooper and Kleinschmidt, 1987 Yeoh and Roth, 1999), we argue that both trade in and technical capabilities assist in enhancing the bene? ts of international diversi? cation while at the kindred time restricting its drawbacks with visit to the introduction of new products. We test our hypotheses by measuring the stock food grocery responses to NPI annunciations exploitation the guinea pig-study methodology example. The events of NPI proclamations argon dupeed for the accomplishment 19972005. Under the assumption of the ef? cient markets hypothesis (Fama, 1970), NPI announcements put down unanticipated study into ? nancial markets that may tilt the market nourish assessments of the announcing ? rms. In response to the new information, changes in stock sets occur, which conciliate investors revision of their frontation with regard to the net present abide by of a ? rms adventure-adjusted anticipate exchange ? ow generated by the new products, or stated differently, the investors expectation of the wealth impact of NPIs.This report is organized as follows persona 2 provides the abstractive undercoat and develops the hypotheses. Section 3 introduces the sampling and methodology. The empirical results atomic number 18 presented in Section 4. Finally, Section 5 contains the discussion and concluding remarks of this study. 2. Theoretical background and hypotheses International div ersi? cation has been suggested by FDI theory and portfolio theory to provide ? rms with bene? ts ranging from the force to realize subdue economies (Grant, 1987 Porter, 1986), the possibility to airing investment risks over different countries (Kim et al. 1993), the potential to arbitrage component part cost differentials across seven-fold locations (Kogut, 1985) and the opportunity to access resources resident in opposed countries (Hitt et al. , 1997). However, in that respect is considerable theoretical take the stand that international diversi? cation comes with both bene? ts and costs. We suggest that that these bene? ts and costs that accompany distant expansion may create both opportunities and challenges for ? rms in terms of exploitation new products, and at that placeby run the stock market reactions to NPI announcements.In this section, we review discordant theoretical domains in order to list the channels with which international diversi? cation might i n? uence grade conception for ? rms in the context of NPIs. 2. 1. Effects of international diversi? cation International diversi? cation provides several advantages towards developing new products. First, international diversi? cation offers opportunities for ? rms to gain new and diverse ideas from a variety of perspectives (Hitt et al. , 1997). Being exposed to varied customers, technology, cultures, and competitive practices, internationally diversi? d ? rms ar able to learn from the experience in foreign ope proportionalityns to ? nd new solutions to get outing product flesh and improving the eccentric of manufacturing know-how (Craig and Douglas, 2000). For example, the launch of a new cordless telephone by Sanyo, which had been adjusted to better meet the phone utilisation habits of American consumers (Barkema and Vermeulen, 1998), consequently expanded the companys gross gross gross gross sales in the U. S. market. 3 Prior studies pay off utilize several ways to musical rhythm the performance of institution, which includes R passion (Hill and Snell, 1988 Hitt et al. 1997), repress of NPIs (Cardinal and Opler, 1995 Hitt et al. , 1996) and number of letters patents (Francis and Smith, 1995). Though they eat up provided valuable insights, the gradations they developed establish some limitations in capturing the rightful(a) nurse of innovation (Chaney et al. , 1991 Schankerman and Pakes, 1986). For example, R vividness is much than related to the input set of innovation provided does non instantaneously broadsheet the output value of innovation. Furthermore, numbers of NPIs or patents just now measure the amount of money of inventive output without considering the quality of innovation.As well, patent counts ofttimes represent a actually noisy measure of the underlying value of innovation beca exercise to the highest stratum patents atomic number 18 non worth anything. The measure employ in our study allows us to di rectly measure the wealth heart of innovation, rather than just now considering the quantity of inventive output as has been done in preliminary studies. C. -F. Wang et al. / daybook of International Management 17 (2011) 333347 335 International diversi? cation also allows ? rms to gain access to resources that may only be accessible in foreign markets nevertheless not frequently obtainable in the home countries to develop new products (Peng and Wang, 2000).By tapping into the technological expertnesss and experience that originates from new(prenominal) countries, multinational ? rms may be able to successfully increase their technological dexterity in developing new products (Hitt et al. , 1997 Kotabe, 1990 Peng and Wang, 2000 Subramaniam and Venkatraman, 2001). Moreover, international diversi? cation provides a ? rm with a wider national ne iirk, which helps increase its exponent to substanceively supplement technological resources and rationalize drudgery process es. These economies of scale can enable the ? m to obtain high go throughs from new product innovations (Bartlett and Ghoshal, 1989 Kogut, 1985). Furthermore, the broader market outlets unattached to new products create higher(prenominal)(prenominal) hark backs on the sunk costs of innovative expense (Subramaniam and Venkatraman, 2001), while bills ? ows generated from large-scale foreign operations provide ? rms with the resources needed for unembellished investment in new product development (Kobrin, 1991 Kotabe, 1990). Notwithstanding the preceding(prenominal) bene? ts, international diversi? cation can bring challenges to the development of new products. The ? rst challenge comes from the dif? ulty in transferring technological cognition between countries. The more countries within which the ? rm operates, the bigger geographic distance the technological know-how has to be transferred, and the less effectuateive the ? rm go away be in developing new products. Furthermor e, with increasing diversi? cation, the differences in cultural, economic and technological settings among the countries increase. These differences drop the effectiveness in assimilating and applying the technological knowledge that is critical for new product development (Chang and Wang, 2007 Hitt et al. 1997) while knowledge revolution can create greater development value (Inkpen, 2000), differences in knowledge does not guarantee successful learning (Bowman and Helfat, 2001 Chang and Singh, 2000 Szulanski and Winter, 2002). In addition, arguments from the economic law of change magnitude returns suggest that the higher degree of international diversi? cation a ? rm is involved in, the more in all probability it is to be entering markets whose marginal contri entirelyions atomic number 18 comparatively lowly (Contractor et al. , 2003). beyond a genuine point, afterward already having expanded into the nigh advantageous markets, the ? m is left with minor or peripheral foreign markets whose resources for and cash ? ow from new product development leave behind exhibit diminishing returns. By swig on various theoretical perspectives, the above discussions suggest that international diversi? cation not only create opportunities that also levy barriers to the value creation provided by new product innovation. With moderate takes of international diversi? cation, ? rms can capitalize on valuable bene? ts of knowledge learning, resource access and production ef? ciency in producing new products.At the same time, economic pro? ts rise as the ? xed costs of new product development be spread across more markets (Kogut, 1985 Porter, 1986). However, ? rms that expand internationally beyond an optimal aim may ? nd that the costs of international diversi? cation at last exceed the bene? ts. Firms at this stage a good deal enter countries that atomic number 18 more geographically and culturally dissimilar, which increases the dif? culties of transfe rring technological knowledge between countries. The value of new product innovation may also exhibit diminishing returns when international diversi? ation is increased beyond the optimal level. base on the above, this study proposes a non- bianalogue and inverted-U-shaped relationship between international diversi? cation and the stock market reactions to NPI announcements, suggesting that the market value of NPIs is judge to improve with increasing international diversi? cation at lower levels of international diversi? cation and then decline with increasing international diversi? cation at higher levels of international diversi? cation. For these reasons, we propose our ? rst hypothesis as follows speculation 1.The relationship between international diversi? cation and the stock market reactions to NPI announcements is inverted-U-shaped, with a positive slope at lower levels of international diversi? cation and negative at higher levels of international diversi? cation. We uti lize event-study methodology to bewilder the e paygrade effect of corporate new product strategies. This begining not only permits direct investigation of changes in announcing ? rms shareholder value, but is also suited to conduct cross-section(a) digest of the strategies underlying the value creation or destruction (Reuer, 2001).Applying event-study methodology to NPIs also facilitates comparisons with previous studies on separate corporate major strategic events. 4 2. 2. fundamental interaction effects of intangible assets and international diversi? cation Although our theoretical framework should hold for all ? rms, the effect of international diversi? cation on new product performance may depend on ? rms intangible assets. Scholars in international melodic line organization aim shown that multinational ? rms with greater market and technological capabilities may receive higher returns from international expansion (Kotabe et al. , 2002 Lu andBeamish, 2004). early(a) researchers also document the importance of merchandising and technological capabilities in the success of new products (e. g. , Cooper and Kleinschmidt, 1987 Danneels, 2002 Krasnikov and Jayachandran, 2008 Moorman and Slotegraaf, 1999 Yeoh and Roth, 1999). We make advances in linking these twain streams of study by investigating the discuss effect 4 Previous studies suck up practice sessiond event-study methodology to test the wealth effect of major corporate events, such as diversi? cation (Doukas and Lang, 2003 Hoskisson et al. , 1991), divestitures (Benou et al. , 2008), alliances (Das et al. 1998 Kale et al. , 2002), regulatory change (Bowman and Navissi, 2003), NPIs (Chaney et al. , 1991 Chen, 2008 Kelm et al. , 1995), R expenditures (Szewczyk et al. , 1996), and patents (Austin, 1993). 336 C. -F. Wang et al. / daybook of International Management 17 (2011) 333347 of internal capabilities on the affiliation between international diversi? cation and the stock market reacti ons to NPI announcements. We suggest that internationally diversi? ed ? rms that have greater marketing and technological capabilities are more able to extract the bene? ts and load the costs of international diversi? ation, resulting in higher returns from NPI announcements. Each moderating effect is discussed individual(a)ly below. Marketing content is related to a ? rms ability to acquire external knowledge through the processes of gathering, empathiseing, and using market information ( twenty-four hour blockage, 1994). Though international diversi? cation gives ? rms opportunities to access new knowledge, ? rms that do not have ability to identify customers needs and to understand the factors that in? uence consumer choice behavior will not be able to achieve better targeting and positioning of its products.Therefore, ? rms that have invested in developing their marketing dexterity are more able to integrate the information on consumer needs in diverse markets into new pr oduct designs, and consequently generate higher returns from the new products (Dutta et al. , 1999). In addition, marketing capacity is re? ected in a ? rms ability to differentiate its products from those of competitors (Kotabe et al. , 2002). A higher level of product differentiation allows a ? rm to cathexis higher prices for its new products (Day, 1994 Yeoh and Roth, 1999). Furthermore, ? ms that croak more money on denote and promoting their products are more likely to mannequin successful brands, which are essential to grammatical twisting awareness, reducing the perceived risk that consumers fit in with new products, and ? nally increasing the adoption rate of new products introduced (Chandy and Tellis, 2000 Dowling and Staelin, 1994 Sorescu et al. , 2003). This is particularly important for ? rms that are completely new to foreign customers (Helsen et al. , 1993 Srivastava et al. , 1998). Consequently, we expect that NPIs are expected to be more worthwhile for intern ationally diversi? d ? rms with greater marketing capabilities, leading to assumption 2 venture 2. Marketing potentiality will positively moderate the relationship between international diversi? cation and the stock market reactions to NPI announcements. As mentioned, technological qualification is also likely to moderate the effect of international diversi? cation on new product development. Technology electrical capacity might represent a ? rms ability to absorb external knowledge (Penner-Hahn and Shaver, 2005 Tsai, 2001). A ? rm may be able to access certain new knowledge through international diversi? ation, but without the capacity to absorb such knowledge a ? rm may not enhance its capabilities within new product innovation. Since knowledge gained from international markets is often tacit and socially complex (Zahra and Hayton, 2008), ? rms that have established a capability in a particular research skill are better able to interpret and assess the knowledge in that area. Technological capability also refers to a ? rms ability to apply knowledge gained from foreign markets to commercial message ends (Krasnikov and Jayachandran, 2008 Moorman and Slotegraaf, 1999).Kotabe et al. (2002) have stated that ? rms with greater technological capabilities are more capable of ? nding better product design solutions. The technical risks in developing new products are more likely to be reduced for such ? rms (Kelm et al. , 1995). Furthermore, ? rms with greater technological capability are more able to lower production costs by improving manufacturing processes. Moreover, technological capability helps ? rms to speed up the product development process and satisfy the market more quickly (Rabino and Moskowitz, 1981). Thus, ? ms that have greater technological capabilities are more likely to enhance their revenues in international markets by providing those markets with new products of better quality. beggarlywhile, ? rms that leverage their technological capabi lities in the greater mountain chain of the global market may sleep together the bene? ts of economies of scale inherent in the innovation process. As a result, we expect that NPIs are more worthwhile for internationally diversi? ed ? rms with greater technological capabilities, leading to Hypothesis 3 Hypothesis 3. Technological capability will positively moderate the relationship between international diversi? ation and the stock market reactions to NPI announcements. 3. Sample and methodology 3. 1. Sample design We test our hypotheses using a prototype of NPI announcement events. We collect the taste selective information on ? rms listed on either the New York Stock Exchange (NYSE) or the American Stock Exchange (AMEX) from the Dow Jones news programworthiness recovery Service (DJNRS) infobase, which provides news- dish out articles and selected stories from the Wall Street journal, Dow Jones News Wire, and Barrons. We drill the words and phrases commonly used to describ e NPIs as keys for a secondbase search routine.Examples are introduce, new product, unveil, launch, received approval, to market, test market, begin selling, along with some other apposite words and phrases. When a repeat NPI announcement from a ? rm is show in a different publication, the announcement that has the earliest date is chosen as it is the earliest date when the information about the NPI is publicly on hand(predicate) (Chaney et al. , 1991 Chen, 2008 Kelm et al. , 1995). The savour close is from January 1997 to December 2005. quaternity criteria are used when selecting ? rms for our standard (1) the announcing ? rms should not have other announcements ? e age before and after the initial announcement date in order to repeal any confounding events that could distort the mensuration of the valuation effects (2) daily stock return information must be available from the Center for Research in Security Prices (CRSP), with a minimum of 50 daily returns in the est imation period (3) companies ? nancial information must be available from the COMPUSTAT ? les and (4) since we want to test the effect of international diversi? cation, only those ? rms with foreign sales entropy available from the COMPUSTAT ? les are included. C. -F. Wang et al. Journal of International Management 17 (2011) 333347 337 pursuance these procedures, we collect a ? nal sample comprising 3061 new product announcements made by 531 ? rms in 57 industries found on the two-digit Standard industrial Classi? cation ( fix) codes. 5 table 1 reports the dissemination of the sample by stratum and industry. Our data shows no obvious cluster by time period. In 2004, there are 530 announcements, method of accounting for 17. 32% of the quantity. Observations are approximately evenly distributed through the quelling familys. However, our sample shows certain levels of concentration in speci? c industries.The largest concentration comes from electrical equipment (33. 61%), r eady reckoner equipment (18. 09%), electro-medical instruments (9. 38%), and concern assistants (e. g. , reckoner programming and the software industry) (7. 19%). These tercesome broad categories constitute nearly 70% of the total sample. As suggested by Chaney et al. (1991), this result is expected since neither the investment opportunities nor their valuation should be random across industries. 3. 2. metre the stock market responses to new product announcements We employ the event study methodology to examine the stock price responses to the announcements of NPIs. This approach has been widely used in the management, accounting, economics and ? nance disciplines to examine the impact of ? rm-speci? c events on ? rm value. The event study approach suggests that, in an ef? cient capital market, the market will adjust and result in returns different from those that are normally expected if the NPI announcement has unexpected information content (Hoskisson et al. , 1991). We us e the market exemplification suggested by chocolate-brown and Warner (1985) to estimate the brachydactylic returns to NPI announcements. This model captures a ? rms stock price change after adjusting for general market-wide factors and the ? ms systematic risk (Bowman, 1983 browned, 1989 Brown and Warner, 1980, 1985). The vicarious return for ? rm i on day t, ARit, is computed by ARit = Rit ? E? Rit = It ? 1 ? where Rit is ? rm is actual returns on day t, and It ? 1 represents the information set available to the market about the ? rm at time t ? 1. The expected return for ? rm i on day t is estimated by E? Rit = It ? 1 ? = ? i + ? i Rmt where Rmt is the return for the market portfolio on day t, ? i is the intercept, and ? i measures the risk or sensitiveness of the ? rms returns relative to the market portfolio. We de? e Day 0 (t = 0) as the initial announcement date. We use the value- weighted CRSP Index as the substitute for the market portfolio. The parameters ? i and ? i are estimated using data for the period of 200 to 60 years before the initial announcement date. The two-day cumulative supernormal returns, railroad car (? 1, 0), are estimated by summing the daily unnatural returns over the window period of days ? 1 and 0. The equally weighted cross-sectional clean anomalous returns on ? event day t, ARt , is foster deliberate by 1N ? ARt = ? ARit N i=1 where N is the total number of sample NPIs. The cumulative average brachydactylous return over the period (? , 0) is withal de? ned. 3. 3. measuring international diversi? cation We use the entropy major power to estimate international diversi? cation. 7 The entropy measure of international diversi? cation is de? ned as ? Pi* ln(1/Pi), where Pi is the percentage of sales in geographic segment i, and ln(1/Pi) is the weight of all(prenominal) geographic segment. This measure thus considers both the number of geographic segments in which a ? rm operates and the relative importance of sales contributed by each geographic segment. 5 For the industry classi? cation, we follow Hitt et al. (1997) and use the our-digit fix codes as the indicator of the industry or business segment that a ? rm operates. Therefore, two proteans in this study, namely product diversi? cation and industry R&D glitz, are estimated basing on the four-digit SIC codes. However, for the sake of brevity, we report the sample statistical statistical distribution by industry on the buns of the two-digit SIC codes. 6 Other performance measures of new product strategies that are most commonly used in previous studies include return on assets, return on sales, return on equity, return on investment and pro? t margin (e. g. , Li and Atuahene-Gima, 2001 Moorman, 1995).However, these accounting measures have several limitations in measuring new product performance (Chang and Wang, 2007 Kalyanaram et al. , 1995 Pauwels et al. , 2004). For example, the differences in accounting policies across ? rms make performance comparisons dif? cult. These measures are also not risk-adjusted as they do not consider business risks associated with individual ? rms when measuring performance, and they are based on historical accounting data and thus may not adequately re? ect future expected revenue streams resulting from the new products. More importantly, these measures re? ect aggregate ? m performance, making it more dif? cult to directly link them to the effect of speci? c new product introductions. overdue to these limitations we employ an event study methodology in order to examine stock price responses to announcements of NPIs. This method captures the ? rms stock price change after adjusting for the ? rms systematic risk (Bowman, 1983 Brown, 1989 Brown and Warner, 1980, 1985), as well as re? ects investors expectations of a ? rms future cash ? ow related to this new product (Chaney et al. , 1991 Chen, 2008 Chen et al. , 2002 Kelm et al. , 1995). 7 Previous studies have used several proxies of international diversi? ation. The most commonly used measures are the ratio of foreign sales to total sales (Grant, 1987 Tallman and Li, 1996), the ratio of foreign assets to total assets (Daniels and Bracker, 1989 Ramaswamy, 1995), numbers of foreign countries in which a ? rm has subsidiaries (Delios and Beamish, 1999 Tallman and Li, 1996) or a composite index encompassing these trio dimensions (Gomes and Ramaswamy, 1999 Sullivan, 1994). However, these measures only capture the extent but not the distribution of international diversi? cation. In this study, we follow Hitt et al. (1997) and use the entropy measure of international diversi? ation to account for the extent of sales in global markets and their weighting. C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 338 add-in 1 Distribution of new product introduction. gameboard A. Sample distribution by year Year take of announcements per centum of sample (%) 1997 1998 1999 2000 2001 2002 2 003 2004 2005 Total 354 279 370 313 232 247 391 530 345 3061 11. 56 9. 11 12. 08 10. 22 7. 58 8. 07 12. 77 17. 32 11. 30 100. 00 Panel B. Sample distribution by industry Two-digit SIC code application group 01 12 13 15 16 17 20 21 22 23 24 25 26 27 28 29 30 31 33 34 Agricultural production cropsCoal mining rock oil and gas extraction Building construction general contractors Heavy construction other than building construction contractors Construction modified trade contractors Food and kindred products baccy products Textile mill products Apparel, ? nished prdcts from fabrics and similar materials ram and wood products, except furniture article of furniture and ? xtures Paper and confederate products Printing, publishing, and allied industries Chemicals and allied products Petroleum re? ning and related industries no-account and miscellaneous plastics products Leather and leather products uncomplicated metal industriesFabricated metal products, except machinery and transit equipment Industrial and commercial machinery and computing device equipment electronic and other electrical equipment and components, except computer equipment emigration equipment Measuring, analyzing, and applyling instruments photographic, medical and opthalmic goods Miscellaneous manufacturing industries Railroad transportation repel freight transportation and warehousing Transportation by air Pipelines, except inseparable gas Transportation services communications Electric, gas, and sanitary services Wholesale trade durable goods Wholesale trade non-durable goodsBuilding materials, hardware, tend supply, and mobile home dealers General merchandise stores Food stores Apparel and accessory stores dwelling furniture, furnishings, and equipment stores Eating and drinking places Miscellaneous sell Depository institutions Non-depository credit institutions Security and goodness brokers, dealers, exchanges, and services Insurance carriers Insurance agents, brokers, and servi ce Real estate Holding and other investment of? ces Hotels, rooming houses, camps, and other lodging places ain services 35 36 37 38 39 40 42 45 46 47 48 49 50 51 52 53 54 56 57 58 59 60 61 62 63 64 65 67 0 72 Number of announcements Percent of sample (%) 1 1 8 1 1 1 28 4 2 2 3 6 13 76 118 2 9 2 23 21 0. 03 0. 03 0. 26 0. 03 0. 03 0. 03 0. 91 0. 13 0. 07 0. 07 0. 10 0. 20 0. 42 2. 48 3. 85 0. 07 0. 29 0. 07 0. 75 0. 69 554 1029 18. 09 33. 61 72 287 2. 35 9. 38 41 4 2 receipts 1 1 120 20 19 10 2 3 3 8 6 14 13 2 18 17 34 5 3 9 6 6 1. 34 0. 13 0. 07 4. 70 0. 03 0. 03 3. 92 0. 65 0. 62 0. 33 0. 07 0. 10 0. 10 0. 26 0. 20 0. 46 0. 42 0. 07 0. 59 0. 56 1. 11 0. 16 0. 10 0. 29 0. 20 0. 20 C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 339 put back 1 (continued) Panel B. Sample distribution by industryTwo-digit SIC code industriousness group 73 78 79 80 82 87 Business services Motion pictures Amusement and enjoyment services Health services educational service s Engineering, accounting, research, management, and related services Nonclassi? able establishments 99 Total Number of announcements Percent of sample (%) 220 13 4 2 1 10 7. 19 0. 42 0. 13 0. 07 0. 03 0. 33 36 3061 1. 18 100. 00 As data is not available at the country level, we use sales of regional markets to measure international revolution (as used by e. g. , Hirsch and Lev, 1971 Hitt et al. , 1997 Miller and Pras, 1980). Following Hitt et al. 1997), we group foreign markets into four regions based on economic and political conditions Africa, Asia and the Paci? c, Europe, and the Americas. Although not perfect, this approach allows us to focus on between-market heterogeneity (Kim et al. , 1989). The international market sales data are from the COMPUSTAT geographic segment tapes for the ? scal year preceding the announcements. 8 3. 4. Measuring intangible assets We measure marketing capability as the average marketing strong point (the ratio of advertisement expenditures to net sales) for the three ? scal years prior to the announcements. 9 We suggest that ? ms who invest more in marketing activities are considered to have victor marketing capabilities. We measure technological capability as the average R&D warmth (the ratio of R&D expenditures to net sales) for the three ? scal years prior to the announcements. We suggest that ? rms outspending their competitors in R&D are considered to have greater technological capabilities. We scale the measures of ? rm capabilities by ? rm size in order to tick that the capability measure does not merely re? ect higher levels of ? nancial resources of large-scaled ? rms ( sideline Moorman and Slotegraaf, 1999). 3. 5. Other variable quantitysOther potential variables that could run into the value of NPIs are manipulateled. The ? rst is ? rm size, mensurable by the natural logarithm of total sales of the announcing ? rm for the ? scal year preceding the announcement (following Kotabe et al. , 2002 Lu and Beamish, 2004). We next affirm for a ? rms leverage ratio, measured as the ratio of total debt to total assets for the ? scal year prior to the announcement (following Chen et al. , 2002 Chen, 2008). We also control for the degree of product diversi? cation for the ? scal year preceding the announcement. overlap diversi? cation is measured by the entropy index (? Pi * ln(1/Pi), where Pi is the percentage of ? rm sales in business segment i, and ln(1/Pi) is the weight of each segment). Following Hitt et al. (1997), we de? ne business segments as those having the same four-digit SIC codes. The product-speci? c effects are also controlled. This is incumbent as some researchers have suggested that high-newness products are expected to create better opportunities for product differentiation and competitive advantage (Kleinschmidt and Cooper, 1991 Meyer and Roberts, 1986), and as such, high-newness products should receive a larger market value than modifys of existing products.Furthermore, sc holars have argued that ? rms introducing multiple products are more competitive in the product market and seize more market share than those announcing single products. This implies that ? rms announcing multipleproducts announcers may appropriate much of the bene? ts associated with new products, and are thus expected to experience a larger increase in market value than those announcing a single product (Acs and Audretsch, 1988 Hendricks and Singhal, 1997). Moreover, researchers have documented that the ? rst to introduce a new product in the market usually enjoys ? st-mover advantages stemming from the creation of entry barriers and electrical switch costs, and from high consumer recognition and preference to the ? rst product (Jovanovic and MacDonald, 1994 leeward et al. , 2000). Therefore, ? rst-moving ? rms are predicted to gain a higher announcement return at the time of NPIs than followers do. The aforementioned ? rms that introduce high-newness and multiple products or ? r ms that are the ? rst to introduce new products are suggested to obtain bear on competitive advantage. This argument corresponds to Williamson (1999) that ? ms getting ahead of their competitors by providing multiple and new technology, products and business solutions have more opportunities to ensure lasting sales growth. We identify these product announcement types by using morphologic content analysis on the news content (as in Chaney et al. , 1991 Lee et al. , 2000 Firth and Narayanan, 1996). Based on the analysis of the news content, we create three dummy variables NEWNESS, MULTIPLE and TIME. 8 The main reason for using data one year before the announcements is to capture the most recent impact of a ? ms attributes on the market reactions to new product introductions. Several independent variables are measured by the data one year preceding the announcements, including international diversi? cation, ? rm size, debt-to-asset ratio, product diversi? cation and two industry sec tor dummy variables. 9 Since the set of publicizing and R&D expenditures tend to ? uctuate substantially from year to year, we use the 3-year average values of advertising ardor, R&D specialty and industry R&D transport to reduce the portion that a random and extreme value in one year disproportionately in? ences our measure of intangible assets. 340 C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 NEWNESS equals one if the product is highly innovative, and correct if it is an update or an enhancement of an existing product (as in Chaney et al. , 1991 Chen, 2008). MULTIPLE equals one for multiple-products denote simultaneously by a ? rm, and zero for single announcements (as in Chaney et al. , 1991 Chen, et al. , 2002). TIME equals one if the announcing ? rm is the ? rst mover, and zero otherwise (as in Lee et al. , 2000 Chen, 2008).Finally, we consider two industry-related factors. The ? rst is the technological opportunity of the industry in which the announcing ? rms operate. Chaney et al. (1991) asserted that the valuation effect of NPIs is higher for ? rms in more technologically based industries, as they are considered to have more innovation opportunities and greater potential for future growth. In contrast, Kelm et al. (1995) found that investors respond positively to new product announcements by ? rms in less-technology-intensive industries because new product announcements by these ? rms are relatively nexpected by investors. Technological opportunities at the industry level are measured by the average industry R&D strong point (the average values of R&D expenditures divided by net sales for all ? rms in the same four-digit SIC industry) for the three ? scal years prior to the announcements (following Chan et al. , 1990 Kelm et al. , 1995). In addition, we control for the industry-speci? c effect with two dummy variables MANUFACTURING and SERVICE. MANUFACTURING equals one for announcing ? rms in manufacturing indust ries, and zero otherwise. SERVICE equals one for announcing ? ms in service industries, and zero otherwise. This is done as several studies have argued that the effect of internationality on performance for manufacturing ? rms is different from that for service ? rms (Capar and Kotabe, 2003 Contractor et al. , 2003). We therefore separate the sample ? rms into service, manufacturing and other industries according to 2-digit SIC codes and apply two industry dummies to control for the industry-speci? c effects. Table 2 presents the means, standard deviations, and correlations for all variables for the sample of NPI announcements. 4. Empirical resultsTable 3 provides estimates of abnormal returns around the announcement date and the adjoin days. The results show that innovations such as NPIs are perceived by investors as value-increasing activities. For the two-day announcement period cumulative abnormal returns, railway car (? 1, 0), the new product announcers experience a positive cumulative average abnormal return of 0. 194%, signi? buzzword at the 1% con? dence level. No signi? cant abnormal returns are observed preceding and following the announcement period. As a result, we use automobile (? 1, 0) as the dependent variable in the following regression analysis.Our results are consistent with prior studies (e. g. , Chaney et al. , 1991 Chen, 2008 Chen et al. , 2002 Kelm et al. , 1995). Table 4 reports the regression results with the dependent variable elevator car (? 1, 0). We present the results without centering the variables in the ? rst ? ve models, and results with centering the variables on their means in the latter ? ve models. 10 modelings 1 and 6 are baseline models that include only the control variables and two measures of intangible assets. Among the control variables, leverage ratio is found to be positively associated with CAR (? 1, 0), though insigni? cant in some models.This result suggests that higher levels of debt lower the expected c osts of dissolve cash ? ow (Jensen, 1986), and new products announced by ? rms with a higher leverage ratio are therefore perceived as more worthwhile. Of the two ? rm-speci? c assets variables, both R&D and advertising intensities have a signi? cant and positive impact in most models. Moreover, industry R&D intensity is found to be signi? cantly negatively associated with CAR (? 1, 0). This result suggests that investors respond positively to new product announcements by ? rms in less technology-intensive industries because new product announcements by these ? ms are relatively unexpected by investors (Kelm et al. , 1995). Other control variables are not found to have signi? cant explanatory power in terms of the variation in announcement abnormal returns. In model 2 (7), we test the impact of international diversi? cation on the stock market reactions to NPI announcements by including the linear and square up terms of international diversi? cation. We ? nd our Hypothesis 1 is st rongly supported, as CAR (? 1, 0) is positively related to the linear term of international diversi? cation and then negatively associated to the squared term of international diversi? cation.This result suggests an inverted-U-shaped relationship between international diversi? cation and the market value of NPIs. instances 3 (8), 4 (9) and 5 (10) test the moderating effects of intangible assets by including the interaction term of international diversi? cation and advertising intensity and the interaction term of international diversi? cation and R&D intensity. 11 place 3 (8) tests the interaction effect between international diversi? cation and marketing capability. The statistically signi? cant and positive coef? cient of the interaction term suggests that the market value of NPIs increases when internationally diversi? d ? rms have greater marketing capacities. Thus, Hypothesis 2 is supported. Model 4 (9) tests the interaction effect between international diversi? cation and te chnological capability. We also ? nd a statistically signi? cant and positive coef? cient of the interaction term. Thus, Hypothesis 3 is supported. To test the robustness of these ? ndings, we simultaneously include the interaction of international diversi? cation and advertising intensity and the interaction of international diversi? cation and R&D intensity in model 5 (10). Results remain unchanged to those in models 3 (8) and 4 (9).It is noted that the main effects between international diversi? cation and the abnormal returns of NPIs remain robust in all models with the addition of the interaction terms. To gain further insights into our ? ndings, we construct Figs. 1 and 2 by drawing on the results of models 3 and 4. We use CAR (? 1, 0) as the measurement of market value of NPIs. When illustrating the impact of advertising intensity (R&D intensity) and 10 Since some variables are constructed from other variables, we follow Aiken and West (1991) by subtracting each variable from its mean value in the sample to minimize their collinearity. 11To test the robustness of our conclusion, we re-examine the regression analysis by incorporating the interaction of quadratic terms of international diversi? cation and intangible asset proxies. Our conclusions remain unchanged. Variables a Mean s. d. Min liquid ecstasy 1. Two-day announcementperiod abnormal return(%)a 2. International diversi? cation 3. Advertising intensity 4. R&D intensity 5. point of intersection diversi? cation 6. Firm size b 7. Debt-to-asset ratio 8. Newness 9. Multiple 10. m 11. Industry R&D intensity 12. Service industry 13. Manufacturing industry 0. 194 0. 037 ? 0. 242 0. 230 0. 653 0. 012 0. 081 0. 816 8. 541 0. 00 0. 827 0. 302 0. 359 0. 236 0. 236 0. 748 0. 424 0. 022 0. 148 0. 659 1. 860 0. 149 0. 379 0. 459 0. 480 0. 390 0. 425 0. 434 0. 000 0. 000 0. 000 0. 000 ? 0. 781 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 1. 382 0. 317 4. 696 2. 533 12. 060 1. 099 1. 000 1. 000 1. 000 2. 3 34 1. 000 1. 000 2 3 4 5 6 7 8 1. 000 ? 0. 033* 1. 000 0. 102*** ? 0. 071*** 1. 000 ? 0. 004 ? 0. 042** ? 0. 016 1. 000 0. 149*** 0. 092*** ? 0. 158*** 0. 399*** 1. 000 ? 0. 111*** 0. 001 ? 0. 090*** 0. 052*** 0. 075*** 1. 000 0. 036** ? 0. 002 0. 010 ? 0. 003 0. 027 ? 0. 021 1. 000 9 0. 076*** 0. 050*** 0. 015 ? 0. 024 0. 016 ? 0. 100*** 0. 33* 1. 000 The two-day period (? 1,0) abnormal return is estimated by summing up abnormal returns from the day before (day ? 1) to the announcement date (day 0). Firm size is measured by the natural logarithm of net sales. ***p b 0. 01, **pb0. 05, *pb0. 1. b 10 11 12 13 0. 045** ? 0. 022 0. 056*** 0. 039** 0. 024 ? 0. 050*** 0. one hundred seventy*** ? 0. 040** 1. 000 0. 257*** ? 0. 083*** 0. 252*** ? 0. 042** ? 0. 188*** ? 0. 098*** 0. 031* 0. 039** 0. 055*** 1. 000 ? 0. 382*** 0. 000 ? 0. 137*** ? 0. 206*** ? 0. 020 0. 199*** ? 0. 007 ? 0. 147*** ? 0. 064*** ? 0. 151*** 1. 000 0. 342*** 0. 017 0. 143*** 0. 151*** ? 0. 017 ? 0. 222*** . 009 0. 147*** 0. 068*** 0. 166*** ? 0. 960*** 1. 000 C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 Table 2 Descriptive statistics and correlations. 341 342 C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 Table 3 Abnormal returns for new product introduction announcements. Event day Mean AR (%) t-statistic ? 10 ?9 ?8 ?7 ?6 ?5 ?4 ?3 ?2 ?1 0 ? 1,0 +1 +2 +3 +4 +5 +6 +7 +8 +9 + 10 ? 0. 023 ? 0. 005 0. 025 ? 0. 016 ? 0. 025 ? 0. 005 0. 047 0. 001 ? 0. 039 0. 093 0. 101 0. 194 ? 0. 038 0. 058 0. 081 ? 0. 056 0. 027 ? 0. 073 ? 0. 055 0. 053 ? 0. 025 ? 0. 054 ? 0. 450 0. 092 0. 471 ? 0. 309 ? 0. 477 ? 0. 099 0. 888 0. 003 ? 0. 731 1. 918* 2. 038** 2. 885*** ? 0. 756 1. 086 1. 329 ? 1. 138 0. 529 ? 1. 403 ? 1. 078 1. 118 ? 0. 471 ? 0. 972 (0. 653) (0. 927) (0. 638) (0. 758) (0. 633) (0. 921) (0. 375) (0. 998) (0. 465) (0. 055) (0. 042) (0. 004) (0. 450) (0. 278) (0. 184) (0. 255) (0. 597) (0. 161) (0. 281) (0. 264) (0. 638) (0. 331) ***p b 0. 01, **p b 0. 05. value in parentheses are p-values. international diversi? cation on CAR (? 1, 0), we hold other control variables at the average level. If the control variables are dummy ones, we substitute these variables with their modes. 2 twain ? gures provide supportive evidence for our hypotheses. First, the relationship between international diversi? cation and the market value of NPIs is found to be inverted-U-shaped, with the slope positive at lower levels of international diversi? cation but negative at higher levels of international diversi? cation. For example, in Fig. 1, for ? rms with no marketing capability, at the initial stage, there is a positive impact on the market value of NPIs with an increase of 0. 62% in CAR (? 1, 0) when the level of international diversi? cation increases from zero to 0. 8. Beyond this threshold of 0. , a higher level of international diversi? cation is associated with a decreasing CAR (? 1, 0). In Fig. 2, for ? rms with no technological cap ability, there is a positive impact on the market value of NPIs with an increase of 0. 63% in CAR (? 1, 0) when the level of international diversi? cation increases from zero to 0. 8. Beyond this point, more international diversi? cation results in lower market values of NPIs. In addition, these graphs illustrate the performance differences across ? rms with different levels of intangible assets. For example, in Fig. 1, for a ? rm with a degree of international diversi? cation of 0. and a level of marketing capability of 0. 3, there is an expected CAR (? 1, 0) that is almost 0. 89% higher than that for a ? rm at the same level of international diversi? cation but with the marketing capability of 0. 1 at a degree of international diversi? cation of 1. 2, there is an expected improvement in CAR (? 1, 0) of 3. 25% when the level of marketing capability increases from 0. 1 to 0. 3. The same procedure can be used to explain the moderating effect of technological capability. In Fig. 2, fo r a ? rm with a level of international diversi? cation of 0. 4 and a level of technology capability of 1. , there is an expected CAR (? 1, 0) that is 2. 09% higher than that for a ? rm at the same level of international diversi? cation but with the technological capability of 0. 4 at a degree of international diversi? cation of 1. 2, there is an expected improvement in CAR (? 1, 0) of 4. 92% when the technology capability of a ? rm increases from 0. 4 to 1. 6. 5. Discussion and conclusions This paper examines the importance of international diversi? cation in explaining the stock market reactions to NPI announcements. Using NPI announcements from the period 19972005, we found an inverted-U-shaped relationship between international diversi? ation and the market value of NPIs, with a slope positive at lower levels of international diversi? cation but negative at higher levels of international diversi? cation. This relationship is moderated by the intangible assets feature by internat ionally diversi? ed ? rms. We ? nd that announcing ? rms with greater technological and/or marketing capabilities achieve higher abnormal returns from NPIs. The main effects of the international diversi? cation variables still hold after the inclusion of these moderating factors. In view of recent research having suggested a sigmoid performance effect of internationalisation (Contractor et al. 2003 Lu and Beamish, 2004), we test our hypotheses in the framework of an S-shaped relationship by simultaneously adding linear, squared and cubed terms of international diversi? cation in the regression. However, our sample does not reveal the S-shaped association between international diversi? cation and the market value of NPI. 12 The equations for the graphs presented in Figs. 1 and 2 are as follows, respectively CAR (? 1, 0) = ? 0. 0037 + 0. 0157 * ID ? 0. 0099 * ID2 ? 0. 0147 * AD + 0. 1476 * ID * AD and CAR (? 1, 0) = ? 0. 0049 + 0. 0168 * ID ? 0. 0112 * ID2 + 0. 0056 * RD + 0. 295 * I D * RD, where ID = international diversi? cation ID2 = International diversi? cation squared AD = advertising intensity RD = R&D intensity. C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 343 Table 4 Regression analysis of new product introduction on international diversi? cation. Un-centered results concentrate on results Independent variables Model 1 Model 2 Intercept ? 0. 0005 (? 0. 072) ? 0. 0042 ? 0. 0017 ? 0. 0037 ? 0. 0009 (? 0. 591) (? 0. 233) (? 0. 525) (? 0. 122) 0. 0178 0. 0157 0. 0168 0. 0143 (3. 156)*** (2. 737)*** (2. 967)*** (2. 486)** ? 0. 0099 ? 0. 0099 ? 0. 0112 0. 0113 (? 2. 188)** (? 2. 175)** (? 2. 434)** (? 2. 455)** International diversi? cation International diversi? cation squared International diversi? cation ? Advertising intensity International diversi? cation ? R&D intensity Firm size a Debt-to-asset ratio Product diversi? cation Advertising intensity R&D intensity Newness Multiple Time Industry R&D intensity Service Manufactur ing Adjusted R2 F value Number of observations a Model 3 Model 4 0. 1476 (2. 236)** ? 0. 0001 ? 0. 0002 (? 0. 336) (? 0. 484) 0. 0072 0. 0071 (1. 531) (1. 516) ? 0. 0001 0. 0000 (? 0. 069) (0. 037) 0. 0667 ? 0. 0147 (2. 100)** (? 0. 04) 0. 0090 0. 0087 (1. 878)* (1. 832)* ? 0. 0003 ? 0. 0002 (? 0. 182) (? 0. 138) 0. 0016 0. 0016 (1. 085) (1. 055) ? 0. 0007 ? 0. 0006 (? 0. 466) (? 0. 407) ? 0. 0034 ? 0. 0032 (? 1. 804)* (? 1. 686)* 0. 0020 ? 0. 0007 (0. 032) (? 1. 121) ? 0. 0005 ? 0. 0015 (? 0. 079) (? 0. 252) 0. 0051 0. 0064 2. 20*** 2. 41*** 3061 3061 Model 6 0. 0036 (0. 637) 0. 1629 (2. 458)** 0. 0295 0. 0003 (0. 676) 0. 0073 (1. 569) ? 0. 0009 (? 0. 744) 0. 0527 (1. 673)* 0. 0093 (1. 941)* ? 0. 0004 (? 0. 195) 0. 0017 (1. 141) ? 0. 0006 (? 0. 389) ? 0. 0018 (? 0. 977) ? 0. 0030 (? 0. 519) ? 0. 0012 (? 0. 218) 0. 0005 1. 15 3061 Model 5Model 7 Model 8 Model 9 0. 0022 0. 0032 0. 0030 0. 0042 (0. 392) (0. 567) (0. 517) (0. 726) 0. 0178 0. 0174 0. 0192 0. 0189 (3. 156)*** (3. 081)*** (3. 375)*** (3. 326)*** ? 0. 0099 ? 0. 0099 ? 0. 0112 ? 0. 0113 (? 2. 188)** (? 2. 175)** (? 2. 434)** (? 2. 455)** 0. 1476 (2. 236)** 0. 0333 (1. 978)** (2. 225)** ? 0. 0001 ? 0. 0002 (? 0. 257) (? 0. 410) 0. 0085 0. 0086 (1. 803)* (1. 824)* ? 0. 0001 0. 0000 (? 0. 102) (0. 012) 0. 0709 ? 0. 0185 (2. 226)** (? 0. 383) 0. 0056 0. 0049 (1. 107) (0. 971) ? 0. 0002 ? 0. 0001 (? 0. 109) (? 0. 051) 0. 0018 0. 0018 (1. 221) (1. 2061) ? 0. 0009 ? 0. 0009 (? 0. 641) (? 0. 99) ? 0. 0046 ? 0. 0046 (? 2. 341)** (? 2. 302)** ? 0. 0005 ? 0. 0016 (? 0. 082) (? 0. 265) ? 0. 0015 ? 0. 0027 (? 0. 252) (? 0. 463) 0. 0060 0. 0077 2. 33*** 2. 58*** 3061 3061 0. 1629 (2. 458)** 0. 0295 0. 0003 (0. 676) 0. 0073 (1. 569) ? 0. 0009 (? 0. 744) 0. 0527 (1. 673)* 0. 0093 (1. 941)* ? 0. 0004 (? 0. 195) 0. 0017 (1. 141) ? 0. 0006 (? 0. 389) ? 0. 0018 (? 0. 977) ? 0. 0003 (? 0. 519) ? 0. 0012 (? 0. 218) 0. 0005 1. 15 3061 Model 10 (1. 978)** ? 0. 0001 ? 0. 0002 ? 0. 0001 (? 0. 336) (? 0. 484) (? 0. 257) 0. 0072 0. 0071 0. 0085 (1. 531) (1. 516) (1. 803)* ? 0. 0001 0. 0000 ? 0. 0001 (? 0. 069) (0. 37) (? 0. 102) 0. 0667 0. 0817 0. 0709 (2. 100)** (2. 517)** (2. 226)** 0. 0090 0. 0087 0. 0249 (1. 878)* (1. 832)* (2. 659)*** ? 0. 0003 ? 0. 0002 ? 0. 0002 (? 0. 182) (? 0. 138) (? 0. 109) 0. 0016 0. 0016 0. 0018 (1. 085) (1. 055) (1. 221) ? 0. 0007 ? 0. 0006 ? 0. 0009 (? 0. 466) (? 0. 407) (? 0. 641) ? 0. 0034 ? 0. 0032 ? 0. 0046 (? 1. 804)* (? 1. 686)* (? 2. 341)** 0. 0020 ? 0. 0007 ? 0. 0005 (0. 032) (? 1. 121) (? 0. 082) ? 0. 0005 ? 0. 0015 ? 0. 0015 (? 0. 079) (? 0. 252) (? 0. 252) 0. 0051 0. 0064 0. 0060 2. 20*** 2. 41*** 2. 33*** 3061 3061 3061 0. 0333 (2. 225)** ? 0. 0002 (? 0. 410) 0. 0086 (1. 824)*