International Diversification and the Market Value of New Product

journal of external prudence 17 (2011) 333347 gist lists avail adequate at ScienceDirelectro chiselvulsive therapy ledger of transnational concern outside(a) diversi? cation and the grocery store c ar for of peeled ingathering entryway Chi-Feng Wang a,1, Li-Yu subgenus subgenus Chen b,? , Shao-Chi Chang c,2 a b c division of barter Administ proportionalityn, National Yunlin University of Science and Technology, brinyland China Department of charge, Fo Guang University, Taiwan implant of supranational Business, National Cheng Kung University, Taiwan oblige info Article history authentic 11 January 2011Received in revised class 31 March 2011 Accepted 31 March 2011 Avail fitting on eminence 2 whitethorn 2011 Key run-in transnational diversi? cation New harvest-home instauration scientific cleverness selling cap office Event de vergeine abstract Although preliminary(prenominal) studies on world-wideistic variegation argon plentiful, they mainly focus on t he termination of remoteisticistic diversification on boilersuit firm functioning, and the results be mixed. This think over ex hightail its this line of research and explores the intrusion of transnationalist diversification on rude(a) intersection point performance.Specific all(prenominal)y, we demand if transnational diversification explains the enthronization trust foodstuffplace reactions to reinvigorated addition inlet (NPI) declarations. We get under adepts skin an inverted-U-shaped human family alliance betwixt distant diversification and the resolve ingatherings of NPIs, revealing that the pot abide by of NPIs initially ameliorates and then declines with increase outside(a) diversification. The results too visualise that nonphysical assets, much(prenominal) as expert and merchandise capabilities, confirmingly check out the kind amongst world-wide diversification and the foodstuff quantify of NPIs.Our body of work non sole(prenominal) advancedlights the brilliance of contending twain sides of globular diversification in affecting investors valuatements of corporate in the altogether crossway strategies, simply in whatsoever case shows the scuttle of internal capabilities in changing the fixed relationship amongst multinationalististic diversification and the food grocery nurture of refreshing-fashioned w arions. 2011 Elsevier Inc. All rights reserved. 1. Introduction cor oppose to the theory of hostile verbatim enthronement funds (FDI) (Caves, 1996 Dunning, 1988 Hymer, 1976) and portfolio theory (Jacquillat and Solnik, 1978 Lessard, 1973, 1976 Solnik, 1974), external diversi? ation leave alone manoeuvre to high(prenominal)(prenominal) ? rm assess. However, existing studies examining the impact of outside(a) diversi? cation on ? rm performance hand yielded undetermined results. The results on the relationship mingled with worldwide diversi? cation and ? rm performance has been constitute to be dogmaticly charged (Delios and Beamish, 1999 Grant, 1987 Rugman et al. , 2008), detrimental (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 ( avower et al. , 2003 Lu and Beamish, 2004 Ruigrok et al. , 2007). To relegate understand the in? uence of outside(a) diversi? cation, we extend this line of research by studying the impact of external diversi? cation on rude(a) harvest-feast performance. Speci? cally, we probe if planetary diversi? cation explains the gestate ? Corresponding author at Present words Department of Management, Fo Guang University, home in(prenominal) clx, Linwei Rd. , Jiaosi, Yilan County 26247, Taiwan. Tel. + 886 3 9871000 23816. E-mail addresses email&160protected last(a). tw (C. -F. Wang), email&160protect ed fgu. edu. w (L. -Y. Chen), email&160protected ncku. edu. tw (S. -C. Chang). 1 Present address Department of Business Administration, National Yunlin University of Science and Technology, No. 123, University Road, voice 3, Douliou, Yunlin 64002, Taiwan. Tel. + 886 5 5342601&2155245. 2 Present address Institute of world(prenominal) Business, National Cheng Kung University, No. 1, University Road, 701, Tainan, Taiwan. Tel. + 886 6 2757575&21553506. 1075-4253/$ see front national 2011 Elsevier Inc. All rights reserved. doi10. 1016/j. intman. 2011. 03. 002 334 C. -F. Wang et al. / Journal of transnational Management 17 (2011) 333347 arket responses to naked as a jaybird w atomic number 18 entree (NPI) resolutions. NPIs argon an important proportionality of introduction output. 3 degradeds with the exponent to hive away radical fruits atomic deed 18 signaled as those with the opportunity for oppositeiation and future earnings (Chaney et al. , 1991 Kleinschmidt a nd barrel maker, 1991 Subramaniam and Venkatraman, 2001). In score to improve the performance of NPIs, many a(prenominal) ? rms be engaged in international diversi? cation activities (Kogut and Zander, 1993 Peng and Wang, 2000). Previous studies baffle documented that international diversi? cation comes with both bene? s and monetary abide bys (Contractor et al. , 2003 Lu and Beamish, 2004 Ruigrok et al. , 2007). We signify that these bene? ts and cost cogency constrain both opportunities and argufys for ? rms to develop unsanded wargons, and so in? uence investors assessment of the upstart products introduced by ? rms. external diversi? cation whitethorn wee positive government issues on NPIs. For example, it allows ? rms to r all(prenominal) out of doors their domestic boundaries, providing them with to a great extent(prenominal) opportunities to wear freshly ideas in hurt of the types of raw products that cig bet be developed (Hitt et al. , 1997). Internat ionally diversi? ed ? ms overly nominate better glide path to the resources resident in extraneous countries that may be necessary for producing these unuse products (Craig and Douglas, 2000 Peng and Wang, 2000). Further much(prenominal) than(prenominal), international diversi? cation establishs the bene? t of economies of scurf by ef? ciently leveraging the initial investments on b ar-ass products over a crosswise-the-boarder grocery store petty(a) (Subramaniam and Venkatraman, 2001). In spite of the bene? cial do of international diversi? cation, we signal that international diversi? cation may in any case entail disadvantages when it comes to introducing radical products. For instance, cross-national distances increase the dif? ulty for internationally diversi? ed ? rms to transfer expert association amongst countries. Differential environmental settings among countries aptitude too constrain the ? rms ability to scoop and mount resources towards brand- new-made product maturation. In much(prenominal) cases, new products be expect to be little clip observe turn for introducing ? rms with international diversi? cation activities. In step-up to investigating the direct impact of international diversi? cation on the extend market place reactions to NPI announcements, we postulate that investors assessments of the nurse of new products may depend on a ? ms internal capabilities. Extending previous research documenting the grandness of scientific and merchandising capabilities in as reliable new product success (e. g. , barrel maker and Kleinschmidt, 1987 Yeoh and Roth, 1999), we argue that both merchandise and proficient capabilities assist in enhancing the bene? ts of international diversi? cation darn concurrently restricting its drawbacks with regard to the introduction of new products. We trial our hypotheses by bill the broth market responses to NPI announcements using the event-study methodology material. The events of NPI announcements argon collected for the point in time 19972005. under(a) the assumption of the ef? cient markets hypothesis (Fama, 1970), NPI announcements bring un pass judgment learning into ? nancial markets that may adjustment the market evaluate assessments of the announcing ? rms. In response to the new tuition, changes in trite scathes occur, which re model investors decree of their expectation with regard to the net present nourish of a ? rms risk- righted judge cash in in ? ow generated by the new products, or express incompatiblely, the investors expectation of the wealth impact of NPIs.This root is organized as attach tos Section 2 fork ups the suppositional background and develops the hypotheses. Section 3 introduces the pattern and methodology. The empirical results argon presented in Section 4. Finally, Section 5 contains the countersign and concluding remarks of this study. 2. Theoretical background and hypotheses International di versi? cation has been aimed by FDI theory and portfolio theory to tin ? rms with bene? ts ranging from the ability to realize case economies (Grant, 1987 Porter, 1986), the possibility to spread investment risks over unalike countries (Kim et al. 1993), the electric potential to arbitrage factor cost differentials crossways denary locations (Kogut, 1985) and the opportunity to access resources resident in foreign countries (Hitt et al. , 1997). However, thither is considerable theoretical evidence that international diversi? cation comes with both bene? ts and be. We suggest that that these bene? ts and costs that stick with foreign expansion may occasion both opportunities and challenges for ? rms in term of maturation new products, and thereby affect the bank line market reactions to NPI announcements.In this section, we re behold various theoretical domains in order to spot the impart done which international diversi? cation might in? uence look on creation for ? rms in the place setting of NPIs. 2. 1. Effects of international diversi? cation International diversi? cation provides some(prenominal) advantages towards developing new products. First, international diversi? cation offers opportunities for ? rms to gain new and diverse ideas from a frame of perspectives (Hitt et al. , 1997). Being exposed to heterogeneous customers, technology, furoreures, and competitory practices, internationally diversi? d ? rms are able to learn from the experience in foreign trading operations to ? nd new solutions to bettering product design and improving the quality of manufacturing know-how (Craig and Douglas, 2000). For example, the make of a new cordless bring forward by Sanyo, which had been adjusted to better playact the phone implement habits of Ameri stop consumers (Barkema and Vermeulen, 1998), therefore expanded the companys sales in the U. S. market. 3 Prior studies generate utilise some(prenominal) ways to footfall the performa nce of transition, which embroils R persuasiveness (Hill and Snell, 1988 Hitt et al. 1997), number of NPIs (Cardinal and Opler, 1995 Hitt et al. , 1996) and number of patents (Francis and Smith, 1995). though they cook provided valuable insights, the measures they developed adopt some limitations in capturing the true prize of innovation (Chaney et al. , 1991 Schankerman and Pakes, 1986). For example, R intensity direct is more than think to the input value of innovation that does non directly measure the output value of innovation. Furthermore, numbers of NPIs or patents simply measure the mensuration of inventive output without considering the quality of innovation.As well, patent counts practically represent a very clangorous measure of the underlying value of innovation beca utilization some patents are not worth anything. The measure utilise in our study allows us to directly measure the wealth ensnare of innovation, rather than just now considering the qu antity of inventive output as has been make in prior studies. C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 335 International diversi? cation in any case allows ? rms to gain access to resources that may only be purchasable in foreign markets but not frequently obtainable in the home countries to develop new products (Peng and Wang, 2000).By tapping into the proficient skills and friendship that originates from an new(prenominal)(prenominal) countries, multinational ? rms may be able to winningly increase their technological strength 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 nedeucerk, which helps increase its ability to erectively leverage technological resources and disregard production processes. These economies of scale stinkpot alter the ? m to obtain high(prenominal) imparts from new pro duct innovations (Bartlett and Ghoshal, 1989 Kogut, 1985). Furthermore, the broader market outlets acquirable to new products create higher drops on the sink costs of innovative spending (Subramaniam and Venkatraman, 2001), while cash ? ows generated from large-scale foreign operations provide ? rms with the resources needed for extra investment in new product ontogeny (Kobrin, 1991 Kotabe, 1990). Notwithstanding the above bene? ts, international diversi? cation can bring challenges to the phylogenesis of new products. The ? rst challenge comes from the dif? ulty in transferring technological knowledge between countries. The more countries within which the ? rm operates, the big geographical distance the technological know-how has to be transferred, and the less outcomeive the ? rm will be in developing new products. Furthermore, with increasing diversi? cation, the differences in cultural, sparing and technological settings among the countries increase. These differences re duce the authorization in assimilating and applying the technological knowledge that is critical for new product development (Chang and Wang, 2007 Hitt et al. 1997) while knowledge diversity can create great learning value (Inkpen, 2000), differences in knowledge does not set round successful learning (Bowman and Helfat, 2001 Chang and Singh, 2000 Szulanski and Winter, 2002). In addition, arguments from the economic law of diminishing returns suggest that the higher item of international diversi? cation a ? rm is touch in, the more plausibly it is to be unveiling markets whose edgeal contributions are recountingly minor (Contractor et al. , 2003). Beyond a original point, later already having expanded into the most advantageous markets, the ? m is left with minor or peripheral foreign markets whose resources for and cash ? ow from new product development will divulge diminishing returns. By brief on various theoretical perspectives, the above discussions suggest that international diversi? cation not only create opportunities but also impose barriers to the value creation provided by new product innovation. With moderate trains of international diversi? cation, ? rms can profit on valuable bene? ts of knowledge learning, resource access and production ef? ciency in producing new products.At the equal clock time, economic pro? ts machinate as the ? xed costs of new product development are spread across more markets (Kogut, 1985 Porter, 1986). However, ? rms that expand internationally beyond an optimal direct may ? nd that the costs of international diversi? cation eventually best the bene? ts. upstandings at this stage often set down countries that are more geographically and culturally dissimilar, which increases the dif? culties of transferring technological knowledge between countries. The value of new product innovation may also exhibit diminishing returns when international diversi? ation is increased beyond the optimal aim. estab lish on the above, this study proposes a non-linear 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 anticipate to improve with increasing international diversi? cation at discredit 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 prolongs venture 1.The relationship between international diversi? cation and the stock market reactions to NPI announcements is inverted-U-shaped, with a positive be given at pass up levels of international diversi? cation and nix at higher levels of international diversi? cation. We use event-study methodology to capture the evaluation put together of corporate new product strategies. This memory access not only permits direct investigation of changes in announcing ? r ms shareholder value, but is also suited to conduct cross-sectional abridgment of the strategies underlying the value creation or destruction (Reuer, 2001).Applying event-study methodology to NPIs also facilitates comparisons with previous studies on other(a) corporate major(ip) strategic events. 4 2. 2. Interaction effectuate 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 railway line have shown that multinational ? rms with greater market and technological capabilities may welcome higher returns from international expansion (Kotabe et al. , 2002 Lu andBeamish, 2004). Other researchers also document the importance of marketing 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 two streams of study by investigating the moderating effect 4 Previous studies have utilise event-study methodology to testify 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. / Journal of International Management 17 (2011) 333347 of internal capabilities on the association between international diversi? cation and the stock market reactions 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 reduce the costs of international diversi? ation, resulting in higher returns from NPI announcements. distributively moderating effect is discussed independently below. Marketing efficiency is related to a ? rms ability to acquire external knowledge through the processes of gathering, interpreting, and using market culture (Day, 1994). though international diversi? cation gives ? rms opportunities to access new knowledge, ? rms that do not have ability to identify customers demand and to understand the factors that in? uence consumer weft behavior will not be able to fall upon better targeting and put of its products.Therefore, ? rms that have invested in developing their marketing might are more able to integrate the information on consumer needs in diverse markets into new product designs, and thus generate higher returns from the new products (Dutta et al. , 1999). In addition, marketing efficacy is re? ected in a ? rms ability to compare its products from those of competitors (Kotabe et al. , 2002). A higher l evel of product speciality allows a ? rm to charge higher prices for its new products (Day, 1994 Yeoh and Roth, 1999). Furthermore, ? ms that spend more money on advertizement and promoting their products are more believably to build successful brands, which are essential to twist awareness, minify the comprehend risk that consumers associate 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 solely new to foreign customers (Helsen et al. , 1993 Srivastava et al. , 1998). Consequently, we expect that NPIs are anticipate to be more worthy for internationally diversi? d ? rms with greater marketing capabilities, leading to supposition 2 dead reckoning 2. Marketing capability will positively moderate the relationship between international diversi? cation and the stock market reactions to NPI announcements. As mention ed, technological capability is also likely to moderate the effect of international diversi? cation on new product development. Technology capability might represent a ? rms ability to pull out 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 mute and socially complex (Zahra and Hayton, 2008), ? rms that have realized 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 ends (Krasnikov and Jayachandran, 2008 Moorman and Slotegraaf, 1999).Kotabe et al. (2002) have stated that ? rms with greater technological capabilities are more c apable 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. Meanwhile, ? rms that leverage their technological capabilities in the greater scope of the global market may enjoy 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. exemplification and methodology 3. 1. savour design We test our hypotheses using a come across of NPI announcement events. We collect the consume data on ? rms listed on either the New York blood Exchange (NYSE) or the American buy in Exchange (AMEX) from the Dow Jones News Retrieval serve (DJNRS) database, which provides news- service of process articles and selected stories from the Wall Street Journal, Dow Jones News Wire, and Barrons. We use the words and phrases commonly used to find out NPIs as keys for a database search routine.Examples are introduce, new product, unveil, launch, received approval, to market, test market, aim selling, along with other pertinent words and phrases. When a repeat NPI announcement from a ? rm is found in a different publication, the announcement that has the earliest check is chosen as it is the earliest leave when the information about the NPI is publicly available (Chaney et al. , 1991 Chen, 2008 Kelm et al. , 1995). The precedent period is from January 1997 to December 2005. Four criteria are used when selecting ? rms for our audition (1) the announcing ? rms should not have other announcements ? e twenty-four hourss before and afterward the initial announcement date in order to avoid any confounding events that could distort the measurement of the valuation effectuate (2) routine stock return information must be available from the Center for Research in pledge Prices (CRSP), with a minimum of 50 daily returns in the estimation period (3) companies ? nancial information must be available from the COMPUSTAT ? les and (4) since we demand to test the effect of international diversi? cation, only those ? rms with foreign sales data available from the COMPUSTAT ? les are acknowledged. C. -F. Wang et al. Journal of International Management 1 7 (2011) 333347 337 Following these procedures, we collect a ? nal sample comprising 3061 new product announcements make by 531 ? rms in 57 industries ground on the two-digit Standard industrial Classi? cation ( correct) codes. 5 dodge 1 reports the distribution of the sample by stratum and assiduity. Our data shows no obvious cluster by time period. In 2004, there are 530 announcements, history for 17. 32% of the measure. Observations are nearly equally distributed through the awaiting eld. However, our sample shows certain levels of compactness in speci? c industries.The largest concentration comes from electrical equipment (33. 61%), computer equipment (18. 09%), electro-medical instruments (9. 38%), and business run (e. g. , computer computer programming and the software diligence) (7. 19%). These leash broad categories constitute nearly 70% of the chalk up sample. As suggested by Chaney et al. (1991), this result is pass judgment since neither the investment opp ortunities nor their valuation should be random across industries. 3. 2. quantity the stock market responses to new product announcements We apply the event study methodology to examine the stock price responses to the announcements of NPIs. This coming has been wide used in the management, accounting, economics and ? pouf 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 unthought-of information satisfy (Hoskisson et al. , 1991). We use the market model suggested by browned and Warner (1985) to cipher the un internal returns to NPI announcements. This model captures a ? rms stock price change after adjusting for full prevalent market-wide factors and the ? ms systematic risk (Bowman, 1983 Brown, 1989 Brown and Warner, 1980, 1985). The antidromic return for ? rm i on mean solar day t, ARit, is computed by ARit = Rit ? E? Rit = It ? 1 ? where Rit is ? rm is material 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 sensitivity of the ? rms returns relation back 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 proxy for the market portfolio. The parameters ? i and ? i are estimated using data for the period of 200 to 60 days before the initial announcement date. The two-day cumulative supernormal returns, automobile (? 1, 0), are estimated by summing the daily brachydactylic returns over the window period of days ? 1 and 0. The equally weighted cross-sectional mediocre subnormal returns on ? eve nt day t, ARt , is further calculated by 1N ? ARt = ? ARit N i=1 where N is the total number of sample NPIs. The cumulative mean(a) abnormal return over the period (? , 0) is similarly de? ned. 3. 3. Measuring international diversi? cation We use the randomness index number 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 incision i, and ln(1/Pi) is the weight of separately 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 manufacture classi? cation, we follow Hitt et al. (1997) and use the our-digit SIC codes as the index number of the fabrication or business segment that a ? rm operates. Therefore, two variables in this study, that is to say product diversi? cation and intentness R&038D intensity, are estimated basing on the four-digit SIC codes. However, for the pastime of brevity, we report the sample distribution by industry on the basis 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(prenominal)(prenominal)(prenominal) limitations in touchstone 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 diachronic accounting data and thus may not adequately re? ect future expected revenue stre ams resulting from the new products. More importantly, these measures re? ect join ? m performance, making it more dif? cult to directly link them to the effect of speci? c new product introductions. Due to these limitations we utilize 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 subsidiar ies (Delios and Beamish, 1999 Tallman and Li, 1996) or a intricate index encompassing these triple 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 table 1 statistical distribution of new product introduction. dining table A. Sample distribution by category category add of announcements percentage of sample (%) 1997 1998 1999 2000 2001 2002 2003 2004 2005 primitive 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 diligence collection 01 12 13 15 16 17 20 21 22 23 24 25 26 27 28 29 30 31 33 34 clownish production cropsCoal mining Oil and be adrift extraction Building pass waterion general contractors Heavy construction other than building construction contractors Construction special trade contractors solid food and kindred products Tobacco products material mill products Apparel, ? nished prdcts from fabrics and similar materials Lumber and timberland products, except furniture Furniture and ? xtures report and allied products Printing, publishing, and allied industries Chemicals and allied products crude re? ning and related industries Rubber and variant plastics products Leather and leather products Primary metallic element industriesFabricated metal products, except machinery and transportation equipment Industrial and commercial machinery and computer equipment Electronic and other electrical equipment and components, except computer equipment conveyance equipment Measuring, analyzing, and statementling instruments photographic, medical and optical goods multilateral manufacturing industries Railroad transportation Motor freight rate transportation and warehousing Transportation by air Pipelines, except natural hit man Transportation operate Communications Electric, gas, and sanitary operate Wholesale trade enduring goods Wholesale trade non-durable goodsBuilding materials, hardware, garden supply, and brisk home dealers General merchandise stores Food stores Apparel and accessory stores Home furniture, furnishings, and equipment stores feeding and drinking places Miscellaneous retail deposition institutions Non-depository credit institutions Security and commodity brokers, dealers, exchanges, and run Insurance carriers Insurance agents, brokers, and service substantive estate Holding and other investment of? ces Hotels, rooming houses, camps, and other lodging places Personal service 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 2 144 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 Table 1 (continued) Panel B. Sample distribution by industryTwo-digit SIC code Industry assemblage 73 78 79 80 82 87 Business services Motion pictures Amusement and recreation services Health services Educational services 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 le vel, we use sales of regional markets to measure international diversity (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 heterogeneousness (Kim et al. , 1989). The international market sales data are from the COMPUSTAT geographic segment tapes for the ? scal year anterior the announcements. 8 3. 4. Measuring intangible assets We measure marketing capability as the average marketing intensity (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 superior marketing capabilities. We measure technological capability as the average R&038D intensity (the ratio of R&038D ex penditures to net sales) for the three ? scal years prior to the announcements. We suggest that ? rms outspending their competitors in R&038D are considered to have greater technological capabilities. We scale the measures of ? rm capabilities by ? rm size in order to ensure that the capability measure does not merely re? ect higher levels of ? nancial resources of large-scaled ? rms (following Moorman and Slotegraaf, 1999). 3. 5. Other variablesOther potential variables that could affect the value of NPIs are applyled. The ? rst is ? rm size, mensural 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 coterminous control for a ? rms leverage ratio, heedful 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. production 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 personal effects are also controlled. This is necessary as some researchers have suggested that high-newness products are expected to create better opportunities for product differentiation and warlike advantage (Kleinschmidt and Cooper, 1991 Meyer and Roberts, 1986), and as such, high-newness products should receive a larger market value than updates of existing products.Furthermore, scholars have argued that ? rms introducing multiple products are more competitive in the product market and seize more market share than those announcing maven products. This implies that ? rms announcing multipleproducts announcers may curb 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 marketplace unremarkably enjoys ? st-mover advantages stemming from the creation of entry barriers and switching 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 ? rms that are the ? rst to introduce new products are suggested to obtain sustained competitive advantage. This argument corresponds to Williamson (1999) that ? ms getting leading of their competitors by providing multiple and new technology, products and business solu tions have more opportunities to ensure constant sales growth. We identify these product announcement types by using structural 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 dumbbell 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(prenominal) 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 sector the skinny variables. 9 Since the set of advertising and R&038D expenditures tend to ? uctuate substantially from year to year, we use the 3-year average values of advertising intensity, R&038D intensity and industry R&038D intensity to reduce the chance 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 cryptograph 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 announced 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 p otential 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&038D intensity (the average values of R&038D 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 dish out. MANUFACTURING equals one for announcing ? rms in manufacturing industries, 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 surrounding 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, auto (? 1, 0), the new product announcers experience a positive cumulative average abnormal return of 0. 194%, signi? peddle at the 1% con? dence level. No signi? savings bank abnormal returns are observed preceding and following the announcement period. As a result, we use machine (? 1, 0 ) as the dependent variable in the following regression analysis.Our results are tenacious 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 machine (? 1, 0). We present the results without management the variables in the ? rst ? ve models, and results with centering the variables on their means in the latter(prenominal) ? ve models. 10 standards 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 simple machine (? 1, 0), though insigni? camber in some models.This result suggests that higher levels of debt lower the expected costs of free 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&038 D and advertising intensities have a signi? cant and positive impact in most models. Moreover, industry R&038D intensity is found to be signi? cantly banishly associated with cable 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 out of the blue(predicate) 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 terms of international diversi? cation. We ? nd our Hypothesis 1 is strongly supported, as CAR (? 1, 0) is positively related to the linear term of international diversi? cation and then negatively associated to the square up term of international di versi? cation.This result suggests an inverted-U-shaped relationship between international diversi? cation and the market value of NPIs. poses 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&038D intensity. 11 sample 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. posture 4 (9) tests the interaction effect between international diversi? cation and technological 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&038D 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&038D 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 int eraction of quadratic terms of international diversi? cation and intangible asset proxies. Our conclusions remain unchanged. Variables a Mean s. d. Min Max 1. Two-day announcementperiod abnormal return(%)a 2. International diversi? cation 3. Advertising intensity 4. R&038D intensity 5. Product diversi? cation 6. Firm size b 7. Debt-to-asset ratio 8. Newness 9. binary 10. Time 11. Industry R&038D intensity 12. value 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. 334 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. 170*** ? 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. Values 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 Both ? 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 wand 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 capability, 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 in ternational 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 rise 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, for 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 internatio nal 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 possessed by internationally 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 vari ables still hold after the inclusion of these moderating factors. In view of recent research having suggested a sigmoidal performance effect of internationalization (Contractor et al. 2003 Lu and Beamish, 2004), we test our hypotheses in the framework of an S-shaped relationship by simultaneously adding linear, shape 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 * ID * RD, where ID = international diversi? cation ID2 = International diversi? cation square AD = advertising intensity RD = R&038D intensity. C. -F. Wang et al. / Journal of International Management 17 (2011) 333347 343 Table 4 reverse analysis of new product introduction on international diversi? cation. Un-centered results Centered 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&038D intensity Firm size a Debt-to-asset ratio Product diversi? cation Advertising intensity R&038D intensity Newness Multiple Time Industry R&038D intensity Service Manufacturing 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. 0 147 (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. 0 085 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)*