Sects Cults and Catholic Church Essay Example for Free

Sects Cults and Catholic Church Essay The Seventh Day Adventists A sect is a religious group with controversial beliefs, they are groups that break away from a main group/religion and form their own set of beliefs, which differ from the teachings of their parent group. Sects also reject the authority of their parent group. The Seventh Day Adventists is an example of a group that broke away from their parent religions of Millerite Movement and Christianity, to become a sect. New York was the home of the 1840s Millerite movement; Millerites were followers of he teachings of William Miller who prophesied the second coming of Jesus Christ to Earth on the 22nd October 1844. When Jesus did not appear on this day the Millerites dissolved, however from the ashes of one movement came the next as the Seventh Day Adventists arose from the disbanded Millerites. The Seventh Day Adventist Church was officially founded in 1863 and the four founding fgures were Joseph Bates, James White, Ellen G. White and J. N. Andrews. The Church quickly became popular and began to spread worldwide, reaching the shores of New Zealand in the 1880s only shortly after its official establishment back in the States. Today the Seventh Day Adventist Church boasts over 16 million members globally and is the twelfth largest religious body in the world.

Food Analysis: Starch, Protein and Reducing Sugars

Food Analysis: Starch, Protein and Reducing Sugars A Qualitative and Quantitative study of Food Analysis to test for the presence of starch, protein and for reducing sugars. Sorina Popa Laboratory Partner: Chris Paterson Objectives: The aims for this experiment are to carry out a number of qualitative procedures in order to identify different food traces such as starch, protein and glucose that are present or absent within the aqueous tests. Introduction: Food science is the application of biological, chemical and physical composition of food as well as the concepts that highlight food processing. The governance within the Food Science Industries are exceptionally strict when it comes to the quality and the safety of their manufactured products. The role of a Food Scientist is to examine the microbiological, biochemical and physical equities of food. The main three categories of food are proteins fats and carbohydrates. Benedict’s test was considered perfect for this experiment as this test is can detect a positive result for reducing monosaccharides or disaccharides sugars such as glucose and lactose. During the process of heating, the alkali in the Benedict’s reagent becomes highly reactive and it behaves as a strong reducing agent.The significant colour change that occurs from a clear blue colour to a brick red precipitate indicates a positive result for the presence of glucose within a food sample. The green/yellow colour change can indicate a vague presence of protein as well as the presence of glucose. Starch is an example of a polysaccharide that is found mostly within plants. Plants use starch to store energy.The Iodine Test is extremely sensitive and can detect up to 0.00002M of a solution tested at a temperature of 20 Â °C. However, if the sample’s pH is low, the iodine solution’s reactions wouldn’t occur with the sample solution tested. Iodine solution determines the presence of starch most easily when the cell walls are damaged and broken down in order to chemically react with the starch grains. In the presence of starch there is a colour change from Brown to Blue/Black. It is expected for starch to be present within potatoes, flour, certain vegetables and cereals. Proteina and amino acids are the building blocks of protein. The amino acids are linked by peptide bonds. Protein is highly found within meat, seeds and beans.The biuret test was considered ideal for this experiment as it can detect higher concentrations of protein.The reaction formed comes from an organic compound as its heated and a high temperature resulting to a positive test for protein. The biuret reagent is composed of diluted copper sulphate within a strong alkali.The colour change from blue to purple originates from the coordinate complex that is found between the cupric ions and the nitrogen atoms.The Bradford Test was also considered for this experiment as it its a rapid and highly sensitive method for testing for Protein. [1] Materials: The materials were as in the ITT Biology1 Food Analysis Protocols Manual. [2] Methods: There were 4 different experiments carried out in order to test for different components withing different food samples tested. The Iodine Test, Benedict Test, Biuret Test and Bradford Test were carried out as per Itt Biology1 Food Analysis Protocols Manual. [2] Results/Data: Table1: Assay Results indicating the presence of reducing sugars applying Benedict solution on the different aqueous solutions tested in the laboratory: [6] Table2: Assay Results indication the presence of Starch applying Iodine solution on the different aqueous solutions tested in the laboratory: [5] Table 3: Assay Results indication the presence of Protein applying Biuret Reagent on the different aqueous solutions tested in the laboratory: [3] Table 4: Assay Results indication the presence of Protein applying Bradford Reagent on the different aqueous solutions tested in the laboratory: [4] Discussion: The following table will indicate the expected results of the solutions tested in the laboratory: [7] Solution A: From the data obtained there is a positive result for the presence of glucose as the colour obtained was Green. The colour Green shows that there was another trace element as well as the presence of Glucose. For the Iodine test the colour obtained was Yellow towards Brown which indicates there was a negative result for the presence of starch. There was a negative result for the presence of protein using the Biuret Reagent as the original colour Blue remained the same. However, when this solution was tested for the presence of protein using Bradford Reagent, there was a colour change from Brown to Light Blue indicating that there are small traces of protein present within this solution. This leads to a conclusion that solution A can be classified as being High Energy Glucose Drink diluted 1 in 20. Solution B: From the data obtained it showed to have the presence of Glucose as the colour obtained was Green. The colour Green tells us that traces of protein has been present as well as Glucose. To sustain this statement, when solution B was tested using Bradford Reagent , it showed a positive result for the presence of protein due to the colour change from Brown to Blue. However there was no presence of Starch within this solution as the colour remained the iodine brown/yellow original colour. This leads to the conclusion that solution B might have been the Diet Carbonated Lemon Lime Drink diluted 1 in 20. Solution C: Looking at the data obtained, Reducing sugars are present within this solution as the colour changed from Blue to Green. The Iodine test showed a negative result for the presence of Starch as the colour remained Brown. However, traces of Protein was present when the Bradford Test was carried out. This signifies that the solution C can be the Carbonated Diet Lemon and Lime Drink diluted 1 in 1000.According to the expected results, the Carbonated Lemon and Lime Drink diluted 1 in 1000 showed to have a positive result for Reducing sugar, and Protein. However, since this solution was diluted 1 in 1000, it’s possible that the presence of protein didn’t show because of the insufficient amount of protein. The Bradford Test showed to have the ability to indicate small traces of protein. Solution D: Analysing the data obtained the wasn’t any presence of Glucose in the Reducing Sugars Assay as the colour remained blue. There wasn’t any Starch present when Iodine solution was added in the Solution D due to no change in the colour i.e. Brown. However, the Biuret Test indicated a positive result for the presence of protein due to the colour change from Blue to Purple. As the Biuret test is known to detect large traces of protein, the presence of protein also came positive when the Bradford Reagent was used. Looking at the different solutions and their expected results, Solution D can be considered to be Sports Supplement diluted 1 in 10 since it is said it’s based on protein and not so much Carbohydrate based. This can be the reason why the Iodine and Benedict Test showed negative results. Solution E From the results obtained it indicated that there are traces of Glucose as the colour changed from Blue to Yellow/Brown. The colour brown isn’t the presence only for the presence of glucose which is orange. There are traces of a different component within the Solution E. There aren’t any traces of Starch when the Iodine Solution was added to a sample of Solution E. However, the extra trace element that appeared during the Bradford Test.The colour changed from Brown to dark Blue signifying traces of protein. When the solution was tested for protein using the Biuret Reagent, it showed a negative result as there was no colour change. As a conclusion, the Solution E appears to be Cow’s Milk diluted 1 in 20. Solution F: Analysing the data obtained from carrying out different aqueous procedures, it showed that there is a negative result for the presence of Reducing Sugars as the colour remained Blue after boiling process. There was also a negative result for the presence of Starch when Iodine solution was added and the colour remained the colour of Iodine solution i.e. Brown/Yellow. However, there was a positive result using both Biuret and Bradford Reagents as the colour changes to Purple when Biuret Reagent was used and the colour changed to dark Blue when Bradford Reagent was used. Comparing the result from this solution to the other expected solutions, Solution F can be looked upon to be Liquidised Cauliflower Filtered and Diluted 1 in 5. Solution G: From the results obtained it showed that there was a positive result for the presence of Glucose as there was a colour change from Blue to Brown. The colour brown also indicates there is another trace element present within this solution as well as Glucose. In the Iodine Test there was a positive result for the presence of starch as the colour change was Orange. This is an unusual colour as the actual positive colour indication for the presence of starch is Blue/Black. However, the colour orange can indicate there are more than one trace elements that are present within this solution. When the Bradford Test was carried out, a negative result was obtained as the colour did not change in Biuret and Bradford Test. From the data obtained, Solution G can be Diet Carbonated Lemon and Lime Drink diluted 1 in 10. Solution H: From the results obtained it showed a negative result for reducing sugar as the colour remained Blue. However, there was a positive result for the presence of starch as the colour changed from Brown/yellow to Orange. There was also a positive result when the solution was tested for protein. When Biuret Reagent was used the colour didn’t change which leads to a negative result but when the Bradford Reagent was used there was a positive result as the colour changed into Light Blue. This can mean that the Solution H can be classified to be Wheat flour 0.5% w/v solution. Conclusion: The purpose of these Qualitative experiments was to analyse in depth the aqueous solutions given and tested for the presence of starch, traces of protein and for reducing sugars. The data collected from each solution was compared with the expected results from specific solutions from which some were diluted more than 5 times. The results obtained were remarkably close to the results expected. This concludes that the overall assays undertaken were a success due to the results obtained and discussions made. References: Books/Manuals: [1] ITT Laboratory Skills Manual (2014-2015), Biology1, pg. 44-51 [2] ITT Biology Analysis Protocols (2014-2015) [3] Malhotra VK (2003) 4th Edition, Food Analysis, Practical Biochemistry for Students, Ch.48. [4] Shanmugam S., Sathish Kumar T, Panneer Selvam K, (2010) Laboratory Handbook on Biochemistry, Eastern Economy Edition, pg:26-27 Online Links: [5] British Nutrition Foundation (2004), Test for Starch, (Energy and Nutrients1995) (http://www.foodafactoflife.org.uk/attachments/92592385-dfb2-4ad6d61cf053.pdf) Accessed on 26th October 2014 @10.00am. [6] British Nutrition Foundation (2004), (Energy and Nutrients 1995) (http://www.foodafactoflife.org.uk/attachments/f4525d5b-0133-49b1e394c729.pdf) Accessed on 26th October [emailprotected] 10.30am. [7] Conde Nast (2014) Self Nutrition Data (http://nutritiondata.self.com/facts/beverages/7399/2) accessed on 26th [emailprotected].

Perceptions of Time in Great Gatsby Essay -- essays research papers

Time is an idea described in diverse periods and aspects, for example philosophical, psychological, physical and biological. This time flows consistently but is broken into the past, present and future. Since we only live in the present forever in preparation for our futures and dreams, when we try to live in the past it restricts our future. Throughout F. Scott Fitzgerald's novel The Great Gatsby, Gatsby wasted time and his life for a single dream, and it was his illusion of his idyllic future that made time a key dimension in his life. Fitzgerald sees life in satiric-tragic dimensions, as a contest between romantic illusion and coarse reality. The reality slowly and viciously disintegrates the illusion. Gatsby suffers from past memories of Daisy and tries to revive the relationship and in the process Gatsby was murdered. Nick wonders, "Almost five years! There must have been moments even that afternoon when Daisy tumbled short of his dreams - not through her own fault, but because of the colossal vitality of his illusion." (101). Gatsby's impractical view of Daisy was, s...

Relative Dating Essay -- essays research papers fc

The Fundamental Principles of Relative DatingRelative dating involves placing events in their proper chronological sequence, that is, in the order of their occurrence (Dutch 1998). This type of dating tells us which geologic event happened first, but does not give an exact date to which something happened. There are several different methods that are used in relative dating. These are the fundamental methods that are used in the field by geologists' and earth scientists to gather information about the relative age of rock bodies and other cool geologic stuff. These principles are the principle of superposition, the principle of original horizontality, the principle of cross-cutting relationships, and the principle of inclusions.The principle of superposition is defined as in the environment of an undisturbed layer of sedimentary rocks; the layers on the bottom are older than the layers towards the top. The pictures I have taken show very good examples of this. By using the principle of superposition we can know that the layers toward the bottom are older than the layers toward the top. The rock body shown in the pictures attached, started out as one layer, as millions and millions of years passed more layers of sedimentary rock were placed on top of each other one after another, each layer was deposited at a later time than the one before it. The youngest layer is on the top, and the oldest layer is on the bottom. This principle was founded by the Danish anatomist Nicolas ...

Amy Tans The Joy Luck Club Essay -- Amy Tan Joy Luck Club Essays

Amy Tan's â€Å"The Joy Luck Club† The â€Å"Joy Luck Club,† by Amy Tan, is a collection of short stories about the relationships between Chinese born mothers and their American born daughters. The story called â€Å"Four Directions† is about a woman named Waverly Jong. The story is about Waverly trying to tell her mother that she is getting married to a American man named Richard. Waverly was a chess champion as while she was a young girl and she remembers the strategy that she used in her matches, and in her life, as she tries to tell her mother about a marriage to an American man. Waverly’s mother was raised in China under Chinese traditions. Waverly’s mother wants Waverly to marry a Chinese man and dos not want Waverly to marry an American man. As Waverly brings us through her decision making process, she questions the Chinese traditions that her mother strictly follows. Since Waverly grew up in an American society, she has lost the Chinese traditions that her mother has tried to teach her and therefore has weakened the bond between Waverly and her mother.   Ã‚  Ã‚  Ã‚  Ã‚  As Waverly brings her mother through her house, Waverly lets her mom see the male items that are around to hint to her mother that she is living with a man, like his clothes around the bedroom and his barbells on the floor. Waverly goes to her closet and shows her mother the fur coat that Richard had given to her. After seeing the coat, Waverly’s mom says: â€Å"This is not so good,’ she said at last. ‘It is just leftover...

Related To Malnutrition And Obesity Health And Social Care Essay

A literature reappraisal is a digest of resources that provide the land work for farther survey. It is often found as a subdivision of a published research survey. Literature reappraisal refers to the activities involves in seeking for information on a subject and developing a comprehensive image of the province of the cognition on the subject. Reappraisal of literature is a written sum-up of the survey conducted antecedently related to the present survey subject. ( Polit and Hungler, 1999 ) The research worker did an broad reappraisal of literature on the research subject in order to derive deeper penetration into the job and to roll up maximal relevant information for constructing the foundations of the survey.In the present survey the reappraisal of literature is organized under the undermentioned headers ;Section-I: Surveies related to malnutrition and fleshiness at school degree. Section-II: Surveies related to consequence of planned nursing intercession. Section-III: Surveies related to knowledge and pattern on Healthy Food Habits among kids. Section-IV: Surveies related to Pender ‘s Health Promotion Model Theory Section-V: Surveies related to Conceptual model based on Pender ‘s wellness publicity theoretical account ( 2002 )SECTION-I: STUDIES RELATED TO MALNUTRITION AND OBESITYMalnutrition in early childhood causes irreparable harm to the development of kid and consequences in wastage of human resources. Hence decrease in the high rate of kid mortality and morbidity due to malnutrition becomes an of import undertaking of policy shapers and societal development contrivers study conducted in rural countries of India revealed that abut 90 % of the kids suffer from different classs of malnutrion and about 15 % of them are in utmost grades of malnutrition. Shetty, P.S. , ( 2000 ) concluded that in an person a series of physiology & A ; behavior response can happen. as a consequence of low energy consumption that is below the acceptable degree of demands. If they individual seek to follow the lower energy consumption so it is good for the endurance of single. Hensrud, DD. , ( 2000 ) reviewed a journal nutrition showing and appraisal which revealed the both under nutrition and over nutrition which leads to increased morbidity and mortality rate. Rio-Grande Dosul. , ( 2004 ) conducted that because of the excess helping of sugar sweetened bevarage, there is an increased opportunity of acquiring fleshiness in most of the in-between school kids. that is approximately 60 % due to the alterations in the feeding wonts, the individuals who are populating in the developed states are more prone to acquire fleshiness. Depending on the composing & A ; the quality of the diet the nutrient consumption has to be related with the fleshiness. Rodriguez, NR. , ( 2005 ) concluded that the kids assorted nutritionary demands in relation to the growing. For the normal growing of the immature kids they should take equal sum of energy & A ; indispensable aminoacids.A broad scope of protein consumption of about.6 to2.9gm/kg should be given for the immature kids. Charles. , ( 2005 ) concluded that since 1960 ‘s the prevalence rate of fleshiness has increased more among the kids in U.S.One of the of import factor that is lending to the paediatric fleshiness is ingestion of sugar sweetened drinks. Veteri, F.E. , ( 2010 ) concluded a series of inquiry associated with the equal energy & A ; protein intake. that is necessary for the growing & A ; proper operation of the children.Inorder to fulfill the protein demands big sum of protein must be ingested along with energy consumption. The present survey shows that there is an associated between the eating wonts and fleshiness.SECTION-II: STUDIES RELATED TO EFFECT OF PLANNED NURSING INTERVENTIONPiffer.S, Kaisermann.D. , ( 2003 ) presented paper reports the consequences of a study on dietetic wonts of 1,398 kids go toing first category of primary school in Trento state ( Northern Italy ) the undermentioned points were investigated. Frequency of interruption fast and nutrient intake.frequency of nutrients at school the construct of tracer nutrients as veggies, fruits, and Sweet was besides investigated. The consequences were analysed harmonizing gender, country of abode, learning method and educational degree of parents. The information about nutritionary manner are satisfactory even if they are strongly associated to education degree of parents, above all of the female parent. The adequateness of nutritionary manner is increasing with the increasing of educational degree. School repast, offering selected nutrients t o all kids go toing fulltime learning subdivision, can re-equilibrate nutritionary manner, diminishing the differences associated to education degree of the parents. Delisle, H. , ( 2010 ) conducted a survey sing the importance of placing the healthy and culturally relevant dietetic forms. which helps in advancing wellness & A ; forestalling diet related chronic disease. The surveies shows that a limited no of nutrients determines the quality of diet & A ; result of wellness. The traditional diets are more fitter & A ; utile when comparison to untraditional dietetic forms. Apart from this healthy feeding wonts are more executable if the attack to the nutrient consumption is equal. Present informations can be used for implementing and bettering wellness publicity action on right dietetic wonts in kid goon, maintaining count of the function of instruction degree of the parents. During the development of kids they need equal proportion of healthy nutrients as like the grownup eat.SECTION-III: STUDIES RELATED TO KNOWLEDGE AND PRACTICE ON HEALTHY FOOD HABITS AMONG CHILDREN:This article shows the dietetic pattern that is following by the kids.Who are go toing the farm school. The findings shows that proper dietetic patterns determines the nutritionary position it besides influence the societal economical & A ; psychological development of the kids. Gil, A. , ( 2009 ) They identified that the consumption of traditional nutrient has no relation the normal dietetic pattern.They were considered as giving small protection from diseases.The survey findings showed that the organic structure mass index exercisings and the assorted diseases status has no important association with the dietetic form.SECTION-IV: STUDIES RELATED TO PENDER ‘S HEALTH PROMOTION MODELAustin David, R. , ( 2000 ) it describes that assorted elements are involved in the Pender ‘s wellness publicity model.It shows the advantages every bit good as the disadvantage of the theoretical account. For the support of the theoretical account assorted literature surveies has taken. Calderon, ( 2002 ) The determination showed the belief and patterns of breastcancer among aged adult females & A ; their perceptual experience towards this.It consist of both educational & A ; environmental support which areconductive to wellness behavior.For the wellness publicity in the older population co-ordination of assorted services adapted.CONCEPTUAL FRAMEWORK BASED ON PENDER ‘S HEALTH PROMOTION MODEL ( 2002 )Conceptual model is interrelated constructs on abstractions that are assembled together in some rationale strategy by virtuousness relevancy to a common subject ( Polit and Beck, 2004 ) . It is a device which to excite research and the extension of cognition by supplying both way and drift. A model may function as a spring board for scientific findings meaningful and generalizable. The present survey is aimed at developing and measuring the effectivity of planned nursing intercession in footings of cognition and pattern on wellness nutrient wonts among primary scho ol kids in selected school at Salem. The conceptual model of this survey is based on Pender, Murdaugh, C and Parson. , ( 2002 ) Health Promotion Model. Pender, ( 2002 ) defines wellness as the realization of built-in and acquired human potency through end directed behavior, competent ego attention and fulfilling relationships with others, while accommodations are made as needed to keep structural unity and harmoniousness with relevant environment. Health Promotion Model is based chiefly on three theories of human behavior the theory of sound action, the theory of planned behaviour and societal cognitive theory. Theory of reasoned action explains that the major determiner of behaviour is the individual ‘s purpose for that behaviour, when she believes that she has control over the state of affairs.Prior Related Behavior:It highlights the experience with the advancing behaviour. In this survey prior related behaviour of cognition and pattern of primary school kids on 1st twenty-four hours. It includes equal -inadequate cognition and pattern towards wellness nutrient wonts, conveying / non conveying healthy nutrients will be assessed by pre-test on 1st twenty-four hours.Personal Factors:Factors about the individual, that influences wellness advancing behavior. This includes biological and socio-cultural factors in this survey.Biological Factors:Includes age of the sample, gender, type of the household.Socio-cultural factors: Education of the female parent, business of the female parent, faith.Health Promoting Behavior:Behaviours ( or ) actions that people carry out with the purposes of better their wellness. In this survey is specified, wellness advancing cognition and pattern of healthy nutrients to kids pamphlet distributed to the kids giving information sing healthy nutrient wonts to the female parents of kids. Regular practicing of wellness nutrient wonts.Perceived Control of Health:Childs can understand about the in effects of taking debris nutrients.Perceived Health Status:The research worker perceived that there is little betterment in the nutrient wonts of kids of conveying wellness bites.Perceived Benefits of Action:Belief about the positive or reenforcing effects of a wellness advancing behavior. Here it includes kids will comprehend benefits of good balanced diet, sample develops the wellness nutrient wonts and betterment in cognition sing wellness nutrient wonts, stay wellness and energetic. Sensed Barriers of Health Promoting Behavior:Belief about kids reduced attending span, more attracted to advertizements, working female parents.Interpersonal Influences:Belief about learning programme on wellness nutrient wonts and advancing pattern of conveying wellness nutrients on 3, 6, 10th twenty-four hours of pattern appraisal by this research worker.Situational Influences:Peer group.Immediate Competing Preferences:Distracting thought about other attractive activities to make instantly before prosecuting in a wellness promotes behaviour. In this survey, it includes kid ‘s wellness, taking healthy nutrients.Committedness to a Plan of Action:Committedness to transport out a wellness promotes bahaviour. The program should be specific to clip and topographic point, and stipulate whether it will be with identified individual or entirely. Practice healthy nutrient wonts at school scene after learning, this survey describe about the preparation of a realistic program to pattern healthy nutrient wonts by conveying healthy nutrient wonts by conveying healthy bites, and healthy tiffin daily ( forenoon and afternoon ) to the school with the supervising of research worker in alternate yearss.

International Diversification and the Market Value of New Product

Journal of International Management 17 (2011) 333–347 Contents lists available at ScienceDirect Journal of International Management International diversi? cation and the market value of new product introduction Chi-Feng Wang a,1, Li-Yu Chen b,? , Shao-Chi Chang c,2 a b c Department of Business Administration, National Yunlin University of Science and Technology, Taiwan Department of Management, Fo Guang University, Taiwan Institute of International Business, National Cheng Kung University, Taiwan article info Article history: Received 11 January 2011Received in revised form 31 March 2011 Accepted 31 March 2011 Available online 2 May 2011 Keywords: International diversi? cation New product introduction Technological capability Marketing capability Event study abstract Although previous studies on international diversification are plentiful, they mainly focus on the effect of international diversification on overall firm performance, and the results are mixed. This study extends this line of research and explores the impact of international diversification on new product performance.Specifically, we ask if international diversification explains the stock market reactions to new product introduction (NPI) announcements. We find an inverted-U-shaped relationship between international diversification and the announcement returns of NPIs, revealing that the market value of NPIs initially improves and then declines with increasing international diversification. The results also show that intangible assets, such as technological and marketing capabilities, positively moderate the relationship between international diversification and the market value of NPIs.Our study not only highlights the importance of considering both sides of international diversification in affecting investors' assessments of corporate new product strategies, but also shows the possibility of internal capabilities in changing the fixed relationship between international diversification and the market value of new products.  © 2011 Elsevier Inc. All rights reserved. 1. Introduction According to the theory of foreign direct investment (FDI) (Caves, 1996; Dunning, 1988; Hymer, 1976) and portfolio theory (Jacquillat and Solnik, 1978; Lessard, 1973, 1976; Solnik, 1974), international diversi? ation will lead to higher ? rm value. However, existing studies examining the impact of international diversi? cation on ? rm performance have yielded inconclusive results. The results on the relationship between international diversi? cation and ? rm performance has been found to be positive (Delios and Beamish, 1999; Grant, 1987; Rugman et al. , 2008), 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 better understand the in? uence of international diversi? cation, we extend this line of research by studying the impact of international diversi? cation on new product performance. Speci? cally, we test if international diversi? cation explains the stock ? Corresponding author at: Present address: Department of Management, Fo Guang University, No. 160, Linwei Rd. , Jiaosi, Yilan County 26247, Taiwan. Tel. : + 886 3 9871000 23816. E-mail addresses: [email  protected] net. tw (C. -F. Wang), [email  protected] fgu. edu. w (L. -Y. Chen), [email  protected] ncku. edu. tw (S. -C. Chang). 1 Present address: Department of Business Administration, National Yunlin University of Science and Technology, No. 123, University Road, Section 3, Douliou, Yunlin 64002, Taiwan. Tel. : + 886 5 5342601Ãâ€"5245. 2 Present address: Institute of International Business, National Cheng Kung University, No. 1, University Road, 701, Tainan, Taiwan. Tel. : + 886 6 2757575Ãâ€"53506. 1075-4253/ $ – see front matter  © 2011 Elsevier Inc. All rights reserved. doi:10. 1016/j. intman. 2011. 03. 002 334 C. -F. Wang et al. / Journal of International Management 17 (2011) 333–347 arket responses to new product introduction (NPI) announcements. NPIs are an important dimension of innovation output. 3 Firms with the ability to introduce new products are signaled as those with the opportunity for differentiation and future earnings (Chaney et al. , 1991; Kleinschmidt and Cooper, 1991; Subramaniam and Venkatraman, 2001). In order to improve the performance of NPIs, many ? rms are engaged in international diversi? cation activities (Kogut and Zander, 1993; Peng and Wang, 2000). Previous studies have documented that international diversi? cation comes with both bene? s and costs (Contractor et al. , 2003; Lu and Beamish, 2004; Ruigrok et al. , 2007). We suggest that these bene? ts and costs might create both opportunities and challenges for ? rms to develop new products, and hence in? uence investors' assessment of the new products introduced by ? rms. International diversi? cation may have positive effects on NPIs. For example, it allows ? rms to reach outside their domestic boundaries, providing them with more opportunities to gain new ideas in terms of the types of new products that can be developed (Hitt et al. , 1997). Internationally diversi? ed ? ms also have better access to the resources resident in foreign countries that may be necessary for producing these new products (Craig and Douglas, 2000; Peng and Wang, 2000). Furthermore, international diversi? cation creates the bene? t of economies of scale by ef? ciently leveraging the initial investments on new products over a broader market base (Subramaniam and Venkatraman, 2001). In spite of the bene? cial effects of international diversi? cation, we suggest that international diversi? cation may also entail disadvantages when it comes to introducing new products. For instance, cross-nationa l distances increase the dif? ulty for internationally diversi? ed ? rms to transfer technological knowledge between countries. Differential environmental settings among countries might also constrain the ? rm's ability to absorb and apply resources towards new product development. In such cases, new products are expected to be less worthwhile for introducing ? rms with international diversi? cation activities. In addition to investigating the direct impact of international diversi? cation on the stock market reactions to NPI announcements, we postulate that investors' assessments of the value of new products may depend on a ? m's internal capabilities. Extending previous research documenting the importance of technological and marketing capabilities in determining new product success (e. g. , Cooper and Kleinschmidt, 1987; Yeoh and Roth, 1999), we argue that both marketing and technological capabilities assist in enhancing the bene? ts of international diversi? cation while simulta neously restricting its drawbacks with regard to the introduction of new products. We test our hypotheses by measuring the stock market responses to NPI announcements using the event-study methodology framework.The events of NPI announcements are collected for the period 1997–2005. Under the assumption of the ef? cient markets hypothesis (Fama, 1970), NPI announcements bring unanticipated information into ? nancial markets that may change the market value assessments of the announcing ? rms. In response to the new information, changes in stock prices occur, which represent investors' revision of their expectation with regard to the net present value of a ? rm's risk-adjusted expected cash ? ow generated by the new products, or stated differently, the investors' expectation of the wealth impact of NPIs.This paper is organized as follows: Section 2 provides the theoretical background and develops the hypotheses. Section 3 introduces the sample and methodology. The empirical res ults are presented in Section 4. Finally, Section 5 contains the discussion and concluding remarks of this study. 2. Theoretical background and hypotheses International diversi? cation has been suggested by FDI theory and portfolio theory to provide ? rms with bene? ts ranging from the ability to realize scale economies (Grant, 1987; Porter, 1986), the possibility to spread investment risks over different countries (Kim et al. 1993), the potential to arbitrage factor cost differentials across multiple locations (Kogut, 1985) and the opportunity to access resources resident in foreign countries (Hitt et al. , 1997). However, there is considerable theoretical evidence that international diversi? cation comes with both bene? ts and costs. We suggest that that these bene? ts and costs that accompany foreign expansion may create both opportunities and challenges for ? rms in terms of developing new products, and thereby affect the stock market reactions to NPI announcements.In this secti on, we review various theoretical domains in order to identify the channels through which international diversi? cation might in? uence value creation 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 heterogeneous customers, technology, cultures, and competitive practices, internationally diversi? d ? rms are able to learn from the experience in foreign operations to ? nd new solutions to bettering product design and improving the quality 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 use habits of American consumers (Barkema and Vermeulen, 1998), consequently expanded the company's sales in the U. S. market. 3 Prior studies have used several ways to measure the performance of innovation, which includes R intensity (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 have provided valuable insights, the measures they developed have some limitations in capturing the true value of innovation (Chaney et al. , 1991; Schankerman and Pakes, 1986). For example, R intensity is more related to the input value of innovation but does not directly measure the output value of innovation. Furthermore, numbers of NPIs or patents only measure the quantity of inventive output without considering the quality of innovation.As well, patent counts often represent a very noisy measure of the underlying value of innovation because most patents are not worth anything. The measure used in our study allows us to directly measure the wealth effect of innovation, rather than on ly considering the quantity of inventive output as has been done in prior studies. C. -F. Wang et al. / Journal of International Management 17 (2011) 333–347 335 International diversi? cation also allows ? rms to gain access to resources that may only be available in foreign markets but not frequently obtainable in the home countries to develop new products (Peng and Wang, 2000).By tapping into the technological skills and knowledge that originates from other countries, multinational ? rms may be able to successfully 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 network, which helps increase its ability to effectively leverage technological resources and rationalize production processes. These economies of scale can enable the ? m to obtain higher returns from new product innovations (Bartl ett and Ghoshal, 1989; Kogut, 1985). Furthermore, the broader market outlets available to new products create higher returns on the sunk 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 development (Kobrin, 1991; Kotabe, 1990). Notwithstanding the above 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 knowledge between countries. The more countries within which the ? rm operates, the larger geographic distance the technological know-how has to be transferred, and the less effective the ? rm will be in developing new products. Furthermore, with increasing diversi? cation, the differences in cultural, economic and technological settings among the countries increase. These differences reduce 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 diversity can create greater learning 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 diminishing returns suggest that the higher degree of international diversi? cation a ? rm is involved in, the more likely it is to be entering markets whose marginal contributions are relatively minor (Contractor et al. , 2003). Beyond a certain point, after 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 exhibit diminishing returns. By drawing on various theoretical perspectives, the above discussions suggest that international diversi? cation no t only create opportunities but also impose barriers to the value creation provided by new product innovation. With moderate levels 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 are spread across more markets (Kogut, 1985; Porter, 1986). However, ? rms that expand internationally beyond an optimal level may ? nd that the costs of international diversi? cation eventually exceed the bene? ts. Firms at this stage often enter 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 level. Based on the above, this study proposes a non-linear and inv erted-U-shaped relationship between international diversi? cation and the stock market reactions to NPI announcements, suggesting that the market value of NPIs is expected 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: Hypothesis 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 utilize event-study methodology to capture the valuation effect of corporate new product strategies. This approach not only permits direct investigation of changes in announcing ? rms' shareholder value, but is also suited to conduct cross-sectional analysis 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 corporate major strategic events. 4 2. 2. 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 business have shown that multinational ? rms with greater marketing and technological capabilities may receive 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 stre ams of study by investigating the moderating effect 4 Previous studies have used 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. / Journal of International Management 17 (2011) 333–347 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. Each moderating effect is disc ussed independently below. Marketing capability is related to a ? rm's ability to acquire external knowledge through the processes of gathering, interpreting, and using market information (Day, 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 capability 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 capability is re? ected in a ? rm's ability to differentiate its products from those of competitors (Kotabe et al. , 2002). A higher level of product differentiation allows a ? rm to charge higher prices for its new p roducts (Day, 1994; Yeoh and Roth, 1999). Furthermore, ? ms that spend more money on advertising and promoting their products are more likely to build successful brands, which are essential to building awareness, reducing the perceived 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 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 internationally diversi? d ? rms with greater marketing capabilities, leading to Hypothesis 2: Hypothesis 2. Marketing capability will positively moderate the relationship between international diversi? cation and the stock market reactions to NPI announcements. As mentioned, technological capability is also likely to moderate the effect of international d iversi? cation on new product development. Technology capability might represent a ? rm's 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 ? rm's 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 capable of ? nding better product design solutions. The technical risks in developi ng 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 in ternational diversi? ation and the stock market reactions to NPI announcements. 3. Sample and methodology 3. 1. Sample design We test our hypotheses using a sample of NPI announcement events. We collect the sample data on ? rms listed on either the New York Stock Exchange (NYSE) or the American Stock Exchange (AMEX) from the Dow Jones News Retrieval Service (DJNRS) database, which provides news-service articles and selected stories from the Wall Street Journal, Dow Jones News Wire, and Barron's. We use the words and phrases commonly used to describe NPIs as keys for a database search routine.Examples are â€Å"introduce,† â€Å"new product,† â€Å"unveil,† â€Å"launch,† â€Å"received approval,† â€Å"to market,† â€Å"test market,† â€Å"begin 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 date is ch osen as it is the earliest date when the information about the NPI is publicly available (Chaney et al. , 1991; Chen, 2008; Kelm et al. , 1995). The sample period is from January 1997 to December 2005. Four criteria are used when selecting ? rms for our sample: (1) the announcing ? rms should not have other announcements ? e days before and after the initial announcement date in order to avoid any confounding events that could distort the measurement 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 estimation 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 data available from the COMPUSTAT ? les are included. C. -F. Wang et al. Journal of International Management 17 (2011) 333–347 337 Following these procedures, we collect a ? nal sample comprising 3061 new product announcements made by 531 ? rms in 57 industries based on the two-digit Standard Industrial Classi? cation (SIC) codes. 5 Table 1 reports the distribution of the sample by year and industry. Our data shows no obvious cluster by time period. In 2004, there are 530 announcements, accounting for 17. 32% of the total. Observations are nearly evenly distributed through the remaining years. However, our sample shows certain levels of concentration in speci? c industries.The largest concentration comes from electrical equipment (33. 61%), computer equipment (18. 09%), electro-medical instruments (9. 38%), and business services (e. g. , computer programming and the software industry) (7. 19%). These three 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. Measuring 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 use the market model suggested by Brown and Warner (1985) to estimate the abnormal returns to NPI announcements. This model captures a ? rm's stock price change after adjusting for general market-wide factors and the ? m's systematic risk (Bowman, 1983; Brown, 1989; Brown and Warner, 1980, 1985). The abnormal return for ? rm i on day t, ARit, is computed by: ARit = Rit ? E? Rit = It ? 1 ? ; where Rit is ? rm i's 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 sensitivity of the ? rm's 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 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 abnormal returns, CAR (? 1, 0), are estimated by summing the daily abnormal returns over the window period of days ? 1 and 0. The equally weighted cross-sectional average abnormal returns on ? event day t, ARt , is further calculated by: 1N ? ARt = ? ARit ; N i=1 where N is the total number of sample NPIs. The cumulati ve average abnormal return over the period (? , 0) is similarly de? ned. 3. 3. Measuring international diversi? cation We use the entropy index 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 each 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 SIC codes as the indicator of the industry or business segment that a ? rm operates. Therefore, two variables in this study, namely product diversi? cation and industry R&D intensity, are estimated basing on the four-digit SIC codes. However, for the sake of brevity, we report the sample distribution by industry on the basis of the two-digit SIC code s. 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. Due to these limitations we employ an event study methodology in order to examine stock price responses to announcements of NPIs. This method captures the ? rm's stock price change after adjusting for the ? rm's systematic risk (Bowman, 1983; Brown, 1989; Brown and Warner, 1980, 1985), as well as re? ects investors' expectations of a ? rm's 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 three 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) 333–347 338 Table 1 Distribution of new product introduction. Panel A. Sample distribution by year Year Number of announcements Percent of sample (%) 1997 1998 1999 2000 2001 2002 2003 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 Industry 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 Oil and gas extraction Building construction: general contractors Heavy construction other than building construction contractors Construction: special trade contractors Food and kindred produc ts Tobacco products Textile mill products Apparel, ? nished prdcts from fabrics and similar materials Lumber and wood products, except furniture Furniture and ? xtures Paper and allied products Printing, publishing, and allied industries Chemicals and allied products Petroleum re? ning and related industries Rubber and miscellaneous plastics products Leather and leather products Primary metal 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 Transportation equipment Measuring, analyzing, and controlling instruments; photographic, medical and optical goods Miscellaneous manufacturing industries Railroad transportation Motor freight transportation and warehousing Transportation by air Pipelines, except natural gas Transportation services Communications Electric, gas, and sanitary services Wholesale trade: durabl e goods Wholesale trade: non-durable goodsBuilding materials, hardware, garden supply, and mobile home dealers General merchandise stores Food stores Apparel and accessory stores Home furniture, furnishings, and equipment stores Eating and drinking places Miscellaneous retail Depository institutions Non-depository credit institutions Security and commodity brokers, dealers, exchanges, and services Insurance carriers Insurance agents, brokers, and service Real estate Holding and other investment of? ces Hotels, rooming houses, camps, and other lodging places Personal 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 2 144 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) 333–347 339 Table 1 (continued) Panel B. Sample distribution by industryTwo-digit SIC code Industry group 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 level, 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 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 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&D intensity (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 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 controlled. The ? rst is ? rm size, measured 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 control for a ? rm's 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. Product 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 necessary 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 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 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 marketplac e usually 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; Lee 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 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 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 dumm y 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 ? m's 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 sector dummy variables. 9 Since the values of advertising and R&D expenditures tend to ? uctuate substantially from year to year, we use the 3-year average values of advertising intensity, R&D intensity and industry R&D 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) 333–347 NEWNESS equals one if the product is highly innovative, and zero 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 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 measure d by the average industry R&D intensity (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 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 deviati ons, 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, CAR (? 1, 0), the new product announcers experience a positive cumulative average abnormal return of 0. 194%, signi? cant at the 1% con? dence level. No signi? cant abnormal returns are observed preceding and following the announcement period. As a result, we use CAR (? 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 CAR (? 1, 0). We present the results without centering the variables in the ? rst ? ve mod els, and results with centering the variables on their means in the latter ? ve models. 10 Models 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 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&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 unexpe cted 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 squared 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 squared term of international diversi? cation.This result suggests an inverted-U-shaped relationship between international diversi? cation and the market value of NPIs. Models 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 Model 3 (8) tests the intera ction 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 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&D intensity in model 5 (10). Results remain unchanged to those in models 3 (8) and 4 (9).It is noted that the â€Å"main effects† between international diversi? cation and the abnormal returns of NPIs remain robust in all models with the additi on 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 Max 1. Two-day announcementperiod abnormal return(%)a 2. International diversi? cation 3. Advertising intensity 4. R&D intensity 5. Product diversi? cation 6. Firm size b 7. Debt-to-asset ratio 8. Newness 9. Multiple 10. Time 11. Industry R&D intensity 12. Service in dustry 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) 333–347 Table 2 Descriptive statistics and correlations. 341 342 C. -F. Wang et al. / Journal of International Management 17 (2011) 333–347 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. 4 50 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 mar keting 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 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 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, 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 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 NP I announcements. Using NPI announcements from the period 1997–2005, 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 variables still hold after the inclusion of these moderating factors. In view of recent research having suggested a sigmoid 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, squared and cubed terms of international diversi? cation in the regressio n. 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 squared; AD = advertising intensity; RD = R&D intensity. C. -F. Wang et al. / Journal of International Management 17 (2011) 333–347 343 Table 4 Regression 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&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 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. 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. 00 64 0. 0060 2. 20*** 2. 41*** 2. 33*** 3061 3061 3061 0. 0333 (2. 225)** ? 0. 0002 (? 0. 410) 0. 0086 (1. 824)*