Italian Verb Conjugations Apparecchiare

apparecchiare: to prepare, to set, to get ready Regular  first-conjugation Italian verbTransitive verb (takes a  direct object) INDICATIVE/INDICATIVO Presente io apparecchio tu apparecchi lui, lei, Lei apparecchia noi apparecchiamo voi apparecchiate loro, Loro apparecchiano Imperfetto io apparecchiavo tu apparecchiavi lui, lei, Lei apparecchiava noi apparecchiavamo voi apparecchiavate loro, Loro apparecchiavano Passato Remoto io apparecchiai tu apparecchiasti lui, lei, Lei apparecchi noi apparecchiammo voi apparecchiaste loro, Loro apparecchiarono Futuro Semplice io apparecchier tu apparecchierai lui, lei, Lei apparecchier noi apparecchieremo voi apparecchierete loro, Loro apparecchieranno Passato Prossimo io ho apparecchiato tu hai apparecchiato lui, lei, Lei ha apparecchiato noi abbiamo apparecchiato voi avete apparecchiato loro, Loro hanno apparecchiato Trapassato Prossimo io avevo apparecchiato tu avevi apparecchiato lui, lei, Lei aveva apparecchiato noi avevamo apparecchiato voi avevate apparecchiato loro, Loro avevano apparecchiato Trapassato Remoto io ebbi apparecchiato tu avesti apparecchiato lui, lei, Lei ebbe apparecchiato noi avemmo apparecchiato voi aveste apparecchiato loro, Loro ebbero apparecchiato Future Anteriore io avr apparecchiato tu avrai apparecchiato lui, lei, Lei avr apparecchiato noi avremo apparecchiato voi avrete apparecchiato loro, Loro avranno apparecchiato SUBJUNCTIVE/CONGIUNTIVO Presente io apparecchi tu apparecchi lui, lei, Lei apparecchi noi apparecchiamo voi apparecchiate loro, Loro apparecchino Imperfetto io apparecchiassi tu apparecchiassi lui, lei, Lei apparecchiasse noi apparecchiassimo voi apparecchiaste loro, Loro apparecchiassero Passato io abbia apparecchiato tu abbia apparecchiato lui, lei, Lei abbia apparecchiato noi abbiamo apparecchiato voi abbiate apparecchiato loro, Loro abbiano apparecchiato Trapassato io avessi apparecchiato tu avessi apparecchiato lui, lei, Lei avesse apparecchiato noi avessimo apparecchiato voi aveste apparecchiato loro, Loro avessero apparecchiato CONDITIONAL/CONDIZIONALE Presente io apparecchierei tu apparecchieresti lui, lei, Lei apparecchierebbe noi apparecchieremmo voi apparecchiereste loro, Loro apparecchierebbero Passato io avrei apparecchiato tu avresti apparecchiato lui, lei, Lei avrebbe apparecchiato noi avremmo apparecchiato voi avreste apparecchiato loro, Loro avrebbero apparecchiato IMPERATIVE/IMPERATIVO Presente    apparecchia apparecchi apparecchiamo apparecchiate apparecchino INFINITIVE/INFINITO Presente apparecchiare Passato avere apparecchiato PARTICIPLE/PARTICIPIO Presente apparecchiante Passato apparecchiato GERUND/GERUNDIO Presente apparecchiando Passato avendo apparecchiato Italian Verbs Italian Verbs  teaches about auxiliary verbs, reflexive verbs, and the use of various tenses as well as verb conjugations, definitions, and examples. Italian Verbs For Beginners  is a reference guide to Italian verbs.

Media Influence On American Culture - 1563 Words

There is no doubt that the media has a huge role in American culture. The media is prevalent on every medium, from newspapers, to television, the Internet, and mobile applications. However, the controversial argument of whether American culture is more influenced or more informed by the media still stands. â€Å"American culture† is what I consider to be the social norms, fashion, topics of discussion, current events, and mindsets that are popular within the general American population. The â€Å"media† to me refers to all forms of news and popular culture from sources such as television news sources, online news websites, online blogs, and social media networks - basically any public medium with a large audience (in this case, the American†¦show more content†¦These major companies along with their local news counterparts also have a huge online presence, with their websites and accounts on every popular social media network like Facebook, Twitter, and Instagr am. The study from Croteau and Hoynes mentions that 65% of adults in the US have broadband Internet access at home. This makes the networks more relevant to the younger population, who mainly use the Internet. To reach the older population that prefers reading newspapers, other news companies continue to produce newspapers in addition to their online presence. The media is inescapable due its large and easy availability. Due to this, the media has a huge influence over American culture because everything the media presents is seen by millions of Americans. This makes the media an influencer instead of just an informer, because the media is the main source of how information and news are spread. Everything the media produces and publicizes becomes American culture. Besides the media’s wide availability, another major factor that makes the media a powerful influencer over American culture is the media’s ability to select exactly what is spread to these mass audiences. 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Using Internet Behavior to Deliver Relevant Television Commercials Free Essays

string(82) " search process for low-involvement products has an immediate purchasing horizon\." INTMAR-00124; No. of pages: 11; 4C: Available online at www. sciencedirect. We will write a custom essay sample on Using Internet Behavior to Deliver Relevant Television Commercials or any similar topic only for you Order Now com Journal of Interactive Marketing xx (2013) xxx – xxx www. elsevier. com/locate/intmar Using Internet Behavior to Deliver Relevant Television Commercials Steven Bellman a,? Jamie Murphy b, d Shiree Treleaven-Hassard a James O’Farrell c Lili Qiu c Duane Varan a a Audience Research Labs, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia Australian School of Management, Level 1, 641 Wellington Street, Perth, WA 6000, Australia Business School, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia d Curtin Graduate School of Business, 78 Murray Street, Perth, WA 6000, Australia b c Abstract Consumer footprints left on the Internet help advertisers show consumers relevant Web ads, which increase awareness and click-throughs. This â€Å"proof of concept† experiment illustrates how Internet behavior can identify relevant television commercials that increase ad-effectiveness by raising attention and ad exposure. Product involvement and prior brand exposure, however, complicate effective Internet-targeting. Ad relevance matters more for low-involvement products, which have a short pre-purchase search process. For the same reason, using Web browsing behavior to make inferences about current ad relevance is more accurate for low-involvement products. Prior brand exposure reduces information-value, even for relevant commercials, and therefore dampens ad relevance’s effect on attention and ad exposure.  © 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved. Keywords: Consumer search behavior; Advertising; Ad relevance; Product involvement; Behavioral targeting; Attention; Ad avoidance; Television; Internet; Experiment; Heart rate Introduction Television, declining in value for advertisers in recent years, is shrinking as a mass medium due to the proliferation of networks and consequent audience fragmentation. At the same time, digital video recorders (DVRs) simplify TV ad avoidance (Wilbur 2008). Finally, advertising budgets are shifting to other media such as the Internet, where interest-based targeting has increased banner ad effectiveness by 65% (Goldfarb and Tucker 2011). Addressability, heralded decades ago, uses technology to track customer preferences and subsequently tailor advertising (Blattberg and Deighton 1991). Sending ads only to interested households improves advertising’s value for consumers by increasing its relevance, and for advertisers by reducing wastage (Gal-Or and Gal-Or 2005; Gal-Or et al. 2006; Iyer, Soberman, and Villas-Boas 2005). Advertising addressability ? Corresponding author. E-mail addresses: s. bellman@murdoch. edu. au (S. Bellman), jamie. perth@gmail. com (J. Murphy), treleaven-hassard@audiencelabs. com (S. Treleaven-Hassard), jamesofarrell@hotmail. com (J. O’Farrell), lili. qiu@uwa. edu. au (L. Qiu), varan@audiencelabs. com (D. Varan). based on consumer Web behavior could apply to other media nd devices such as television, smart phones, tablet devices and satellite radio (Shkedi 2010). Although search engine keywords and online social network data could augment targeting based on Web browsing behavior (Delo 2012; Jansen and Mullen 2008; Jansen et al. 2009), this addressable advertising â€Å"proof of concept† paper uses solely Web browsing behavio r. Currently, TV advertisers target relevant commercials based on location, lifestyle and purchasing information (Marcus and Walpert 2007). A cable company, for instance, might use subscriber information to send different ads to different ethnic groups (Vascellaro 2011b). But information in these databases can be months or years old. Current product and brand interest based on Internet behavior could add a new layer to a targeting database. Nearly all (85%) of the United States population are Internet users (Pew Internet and American Life Project 2012), leaving digital footprints that suggest product interest. Cable companies that package cable and broadband Internet services, Comcast for example, could align household Internet and TV-viewing data to increase the relevance of marketing communication. The basic intuition behind targeting TV ads based on Web rowsing behavior is that time spent browsing pages in a 1094-9968/$ -see front matter  © 2013 Direct Marketing Educational Foundation, Inc. Published by Elsevier Inc. All rights reserved. http://dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (20 13), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx 2 certain product category increases interest in commercials for brands in that category. This intuition needs empirical testing, and the literature on consumer search suggests that differences among product categories may complicate applying this intuition (Richins and Bloch 1986). This paper opens with our conceptual framework, which distinguishes ad relevance from product involvement (Batra and Ray 1983). Consumers tend to use an ongoing search process (Bloch and Richins 1983) for high-involvement products; buying the wrong brand entails greater financial, social, or psychological risks than for low-involvement products (Rossiter and Percy 997). Internet shopping strategies differ, therefore, between high- and low-involvement products (Moe 2003). These differences in involvement, along with prior brand exposure, lead to four hypotheses about the effects of TV ad relevance discovered via Web-browsing behavior. After a discussion of the methodology and results, the paper closes with implications, limitations and future research avenues. Conceptual Framework Ad Relevance and the Consumer Search Process Advertising has relevance before, during, and after purchase (Vakratsas and Ambler 1999). Consumer pre-purchase search has two phases, exploratory and goal-directed search (Janiszewski 1998). Consumer information needs change from generic product information (e. g. , hotels) to brand-specific information (e. g. , Hilton), including advertising by these brands (Rutz and Bucklin 2011). In St. Elmo Lewis’ classic AIDA model (Strong 1925), exploratory search begins with awareness; consumers first recognize their need for a product. As interest grows, they explore options in the category and seek information from friends and the media, including the Internet. In the later oal-directed search phase, they desire a particular product or brand. Finally, they put that desire into action and buy a specific brand. Ad relevance for a product is highest during goal-directed search, lower during exploratory search, and practically non-existent with consumers unaware of a product need. Product Involvement and Web Browsing Behavior Moe (2003) illustrates how useful matching ads to Web browsing behavior can be, and the complications associated with product involvement. Most products are low-involvement, attracting attention only during the pre-purchase search process (Bloch and Richins 983). Since pre-purchase search for these products generally ends in a purchase, the search process for low-involvement products has an immediate purchasing horizon. You read "Using Internet Behavior to Deliver Relevant Television Commercials" in category "Essay examples" But the risks associated with high-involvement products lead many consumers, especially product enthusiasts, to engage in ongoing search, to continuously update their knowledge or just for enjoyment (Richins and Bloch 1986). Examples of such products include automobiles, computers, and fashion items (see Table 2 later). A search for information about a high-involvement product may not end in a purchase, and often has a future urchasing horizon. Moe (2003) used two dimensions, low versus high ad relevance (explo ratory vs. goal-directed search) and low versus high involvement (immediate vs. future purchasing), in a 2 ? 2 matrix to define four Web browsing strategies used by Internet shoppers (Table 1). Moe (2003) categorized visitors to a real store’s Web site, which sold nutrition products such as vitamins, into these four strategies. Shoppers interested in a low-involvement product with an immediate purchasing horizon adopt a hedonic browsing strategy during exploratory search, and advertising has low relevance. They use the directed buying strategy during goal-directed search, and advertising has high relevance. Shoppers use the other two strategies for a high-involvement product with a future purchasing horizon. Advertising for high-involvement products should have relatively lower relevance for shoppers using the exploratory knowledge building strategy, compared to shoppers using the goal-directed search/ deliberation strategy. Table 1 also reports the average Web browsing time for these four strategies. These data suggest that long versus short Web browsing time can signal high ad relevance for low-involvement products. Directed buyers averaged over 36 minutes visiting the online store. In contrast, hedonic browsers spent one fifth as much time on the site, about seven minutes. Long versus short Web browsing time, however, may not signal high ad relevance for high-involvement products. First, average Web browsing time is nearly 3? times longer for high- rather than low-involvement products due to the ongoing nature of search for these products (Richins and Bloch 1986). Second, Moe’s (2003) data suggest that the opposite pattern of Web browsing times will indicate low versus high ad relevance for high-involvement products. In line with theory that predicts an inverse-U effect of product experience on search activity (Moorthy, Ratchford, and Talukdar 1997), knowledge-building shoppers (low ad relevance) recorded the longest Web browsing times, nearly two hours in a single session. Shoppers with a search/deliberation strategy (high ad relevance) and extensive category knowledge focus their search time on specific products or brands and record relatively shorter Web browsing times, about the same duration as directed buyers. Table 1 Influence of ad relevance and product involvement on Web browsing behavior. Product involvement Ad relevance Low (exploratory search) Low (immediate purchasing horizon) High (future purchasing horizon) High (goal-directed search) SHORT Hedonic browsing (6:41) LONG Knowledge building (111:47) LONG Directed buying (36:33) SHORT Search/ deliberation (37:59) NOTE—Adapted from Moe (2003). Numbers in parentheses are the average Web site browsing time for each of the four Internet shopping strategies (minutes:seconds). Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. ntmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx The next section uses this conceptual framework to propose four hypotheses about the effects of ad relevance, indicated by Web browsing behavior, on attention and ad exposure. Hypotheses Moderating Effect of Product Involvement According to the conceptual framework above, W eb browsing behavior can suggest ad relevance. A long time browsing information about a product indicates a consumer likely in goal-directed search for that product; brand advertising has high relevance, but only for low-involvement products. For highinvolvement products, Web browsing behavior is unrelated to ad relevance, or the opposite pattern, short rather than long Web browsing time, is likely to signal greater ad relevance. When advertising is relevant, that is, a consumer is in the goal-directed phase of product search, a TV commercial for that product should receive above average attention. When people pay attention to external stimuli, their heart rate goes down, most likely to minimize interference with information-intake (Lacey 1967). In other words, greater attention to relevant ads will associate with a decrease in heart rate. Ad relevance should also increase ad exposure, by reducing ad avoidance. As viewers may avoid TV commercials mechanically by channel-changing or fast-forwarding, addressable commercials interest TV advertisers as a method to combat ad avoidance. This ad exposure is better measured in viewing time, which conveys more information than a simple binary measure of ad avoidance (Gustafson and Siddarth 2007). Single-source data that match a household’s commercial viewing time to its purchase history suggests viewers are more likely to watch relevant ommercials, that is, commercials for products the household buys, as opposed to irrelevant commercials (Siddarth and Chattopadhyay 1998). A recent field trial found that addressable TV ads can reduce ad avoidance by 32% (Vascellaro 2011a). Less ad avoidance means longer viewing times for commercials, and therefore high ad relevance commercials will increase ad exposure. According to the conceptual model in Table 1, high versus low product involvement is likely to moderate the reliability of Web browsing time as an indicator of high versus low ad relevance, attention, and ad exposure. High involvement with a product is likely to translate into high interest in advertising by brands of that product during both exploratory and goal-directed search. For high-involvement products, therefore, TV commercials could have high ad relevance, attention, and ad exposure, whether or not Web browsing behavior has been recently observed. Furthermore, for high-involvement products, short rather than long Web browsing time could indicate relatively greater ad relevance. Consumers, however, are less likely to seek information online or offline about low-involvement products (Bloch and Richins 1983; Bloch, Sherrell and Ridgway 1986). This suggests that Web browsing for low-involvement products is highly valuable for behavioral targeting, as pre-purchase search for these products is for an immediate need (Moe 2003). For low-involvement products, Web browsing behavior should be a 3 highly reliable indicator of ad relevance, attention and ad exposure for TV commercials, but this will not be the case for high-involvement products. Thus, product involvement will moderate the effects of ad relevance indicated by Web browsing behavior: H1. Ad relevance based on Web browsing behavior will increase attention to commercials for low-, but not for high-involvement products. H2. Ad relevance based on Web browsing behavior will increase ad exposure to commercials for low-, but not for high-involvement products. Moderating Effect of Prior Brand Exposure Another variable likely to moderate addressability effects is prior exposure to advertising for a brand. Prior brand exposure reduces a commercial’s information value, even when that information is relevant (Campbell and Keller 2003; Pechmann and Stewart 1989). Prior exposure should therefore reduce a viewer’s willingness to pay attention to the commercial (Potter and Bolls 2012), or to choose ad exposure over ad avoidance (Bellman, Schweda, and Varan 2010; Woltman Elpers, Wedel, and Pieters 2003). Hypotheses 3 and 4 predict that prior brand exposure moderates the effects of ad relevance and involvement on attention and ad exposure: H3. Prior brand exposure reduces the effect of ad relevance on attention to commercials for low-involvement products. H4. Prior brand exposure reduces the effect of ad relevance on ad exposure to ommercials for low-involvement products. The next section describes the experiment to test these four hypotheses. Methodology Overview To test the concept of using Internet behavior to deliver relevant TV commercials, this experiment drew on two seemingly unrelated lab sessions. In the first lab session, each participant’s Web browsing behavior was analyzed to discover highly relevant products. In the seco nd lab session, this knowledge was used to individually customize the playlist of TV commercials shown to each participant. Sample and Design The experiment was a 2 ? 2 ? 2 mixed design. Prior brand xposure (yes/no) was a between-participants factor. The â€Å"yes† group saw Web banner ads in the first lab session, exposing them to visual aspects of the TV commercials for the same brands shown in the second lab session. All TV commercials were for U. S. brands unavailable in the test market, Australia, ensuring no prior brand exposure in the â€Å"no† group. Ad relevance (high/low) and Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 4 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx A. The home page for the six high-involvement product categories. B. The home page for a subcategory of high-involvement products: credit cards. Fig. 1. The Web site used to unobtrusively measure interest in 12 product categories. A. The home page for the six high-involvement product categories. B. The home page for a subcategory of high-involvement products: credit cards. Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. oi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx product involvement (high/low) were both within-participants factors for the TV commercials shown in the second lab session. A total of 211 members of an audience panel, representative of the Australian public, earned $30 (AUD) to participate in two la b sessions totaling 90 minutes. These participants were randomly assigned to the two between-participants groups (yes, prior brand exposure = 109, no = 102). Half the sample (49%) were women, and ages ranged from 19 to 78 years (M = 45, SD = 15). All had high levels of Internet experience (Venkatesh and Agarwal 2006). Careful procedures, such as describing the two lab sessions as separate studies, helped ensure that participants were unaware that their Web browsing behavior in the first lab session influenced the TV commercials served in the second lab session. Lab Session 1 In the first lab session, participants evaluated the fictitious â€Å"Consumer Choices† Web site (Fig. 1A), which displayed information about six high- and six low-involvement product categories, identified from published classifications (Kover and Abruzzo 1993; Ratchford 1987; Rossiter, Percy, and Donovan 991; Vaughn 1986). Each product category had three subcategories (Table 2). The five pages of content for each of these 36 subcategories were matched across products for depth, breadth and reading level to allow meaningful time-in-category comparisons. Participants had four minutes to explore the six highinvolvement categories, and another four m inutes to explore the six low-involvement categories (the order, high- or lowinvolvement first, was randomized). Browsing time in each category was logged. For each participant, the two product ategories (one high- and one low-involvement) browsed for the longest time were that participant’s two high ad relevance categories. The two corresponding low ad relevance categories (one high- and one low-involvement) were randomly selected from the participant’s categories with the shortest browsing times (e. g. , 0 seconds). For participants in the prior brand exposure group, banner advertisements were at the top of each page. In the no prior brand exposure group, a generic photo-montage of the same size occupied this ad space. Each of the 36 subcategories advertised a different brand. For each participant, one brand was chosen randomly to represent its subcategory across both stages of the experiment (e. g. , Capital One, Fig. 1B), from the two brands available for each subcategory, a total of 72. The duration of prior exposure to a brand was the time the participant spent viewing pages of content about the brand’s subcategory (i. e. , prior exposure was higher for high ad-relevance categories). Lab session 1 ended after participants completed an extensive online survey about the Web site’s usability (Agarwal and Venkatesh 2002; Venkatesh and Agarwal 2006). This survey reated a 20-minute delay, realistically replicating the process of identifying ad relevance based on Web browsing behavior, and subsequently delivering a set of customized commercials to a TV set-top box. 5 Lab Session 2 Participants went to a different laboratory for the second lab session, in which they evaluated new TV programs. Participants first verified their name and date of bir th displayed on the TV screen, to ensure no miss-targeting of the customized ads (Gal-Or et al. 2006). They then practiced using the TV remote control to select programs and mechanically avoid ads. Participants selected one of four new one-hour U. S. television programs—drama, comedy, reality or documentary—to evaluate for potential airing in Australia. They were told these programs had been recorded off-air in the U. S. , with ads included. This selection procedure successfully eliminated differences in program liking (Coulter 1998), which can affect advertising response (Norris, Colman, and Aleixo 2003). Each program had five ad breaks, with five 30-second ads in each break. The ads shown in the first four breaks were individually customized based on the ad relevance information discovered in the first lab session. The four test ads— for two high ad-relevance products (one high- and one low-involvement) and two low ad-relevance products (one high- and one low-involvement)—were counterbalanced across the first four breaks, always appearing in the middle position to avoid primacy and recency effects (Pieters and Bijmolt 1997). The remaining eight product categories each contributed two filler ads, the 16 required for the first four ad breaks. The fifth ad break, which always showed the same five filler ads, created a natural delay before measuring brand recall. While participants watched their chosen program, the two ependent variable measures were collected unobtrusively. Attention was heart rate decrease relative to each participant’s pre-program baseline heart rate (Potter and Bolls 2012). The slowest heart rate during a commercial—representing the peak of attention (Lang et al. 1993)—was subtracted from the participant’s slowest resting-baseline heart rate (Wainer 1991). Heart rate was measured via pulse photoplethysmography at two places: the lobule of the ear and the distal phalanx of the non-dominant hand’s ring finger. The signal, ear or finger, with the fewest artifacts (mainly caused by movement) was retained. Sixty-four participants (30% of 211, women = 47%, age range 19-75 yrs) consented to this procedure and yielded usable heart rate data. None of these participants was on medication that affects heart rate (Andreassi 2007). Thanks to an efficient mixed-level design, the size of this sub-sample was sufficient to test the two attention hypotheses with 99. 9% power (Faul et al. 2007). Ad exposure was the number of seconds that the commercial displayed on the screen before avoidance. Participants avoided ads by pressing the remote control’s skip button, which jumped to the next ad or program segment. In this experiment skipping was impossible during the program and during the first five seconds of each commercial, to ensure that each skip decision was on the merits of the ad rather than a general goal of avoiding all commercials. A matched sample (n = 81) confirmed that this procedure added a nonsignificant 1. 67 seconds of ad exposure, compared to participants able to skip at any time. Although previous studies have used ad viewing time to measure ad attention (Olney, Holbrook, and Batra 1991), in this study Please cite this article as: Steven Bellman, et al. Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx 6 Table 2 Product categories and subcategories. Involvement Category Subcategories High Automotive 1. Luxury Cars 2. Compact 4WDs 3. Sedans 4. Credit Cards 5. Financial Planning 6. Reta il Banking 7. Digital Televisions 8. Computers 9. Kitchen and Laundry Appliances 10. Jewellery 11. Casual Wear 12. Sportswear 13. Home Insurance 14. Automotive Insurance 15. Life Insurance 16. Deodorant 7. Hair Care 18. Allergy Medication 19. Hamburgers 20. Mexican Food 21. Chicken 22. Household Cleaners 23. Laundry Detergent 24. Cleaning Tools 25. Gardening 26. Tools 27. Pest Control 28. Chocolate Bars 29. Mints 30. Chewing Gum 31. Soft Drinks 32. Energy Drinks 33. Coffee 34. Frozen Meals 35. Packaged Meats 36. Desserts Financial Services Technology Fashion Apparel Insurance Health Well-Being Low Fast Food Home Cleansers Home Maintenance Candy Beverages Packaged Food NOTE—For every subcategory, two brands were available for selection (i. e. , 72 brands). attention and ad exposure were uncorrelated (r = ? 06, p = . 665), justifying the use of both measures. After watching the one-hour program, participants completed a second online survey on the same flat screen monitor used to watch the program. In line with the cover story for lab session 2, this survey began by measuring program liking (Coulter 1998; Cronbach’s alpha = . 96). The survey went on to measure manipulation checks of ad relevance and product involvement, and managerially relevant outcomes associated with greater attention and ad exposure (see the Appendix A). After completing this survey, participants were debriefed, hanked, and given their gift-card. products for which they were in the goal-directed search phase. This was confirmed by significant differences in self-reported purchasing horizon, measured in the post test (Table 3). Products classified as high ad-relevance, based on Web browsing time, were more likely to be used or purchased in the next month than those classified as low ad-relevance (Mlow ad-relevance = 3. 65 times per month vs. Mhigh ad-relevance = 6. 78). As predicted by the conceptual framework in Table 1, a significant two-way interaction between ad relevance a nd product involvement ualified this Internet-targeting main effect (Table 3). Using Web browsing time, ad relevance was inferred more accurately for low- rather than high-involvement products. For high-involvement products, purchase/usage was more likely for products inferred as low ad-relevance, based on Web browsing time (Mlow ad-relevance = . 20 times per month vs. Mhigh ad-relevance = . 10). Failure to observe Web browsing did not indicate low ad-relevance for high-involvement products, and as shown in Table 1, short rather than long Web browsing time could indicate relatively greater ad relevance. Also in line with Table 1, low-involvement products had a significantly shorter purchasing horizon compared to highinvolvement products (Mlow-involvement = 10. 28 times per month vs. Mhigh-involvement = . 15; Table 3). Product Involvement The manipulation of product involvement was also successful, measured by self-reported product involvement (Mlow-involvement = 4. 02 [on a 7-pt scale] vs. Mhigh-involvement = 4. 93, p b . 001, partial ? 2 = . 27), even without individual customization. No other effects were significant (e. g. , ad relevance: Mlow ad-relevance = 4. 40 vs. Mhigh ad-relevance = 4. 55, p = . 213, partial ? 2 = . 007). Table 3 ANOVA results. Effect Within-participants effects Ad relevance Product involvement Purchasing horizon (monthly frequency) Attention (heart rate decrease) Ad exposure (viewing time in seconds) 10. 08** (. 05) 122. 15*** (. 37) 10. 78** (. 05) 1. 26 (. 01) .19 (. 001) 1. 40 (. 01) 3. 67 †  (. 06) 1. 34 (. 02) 1. 64 (. 03) 2. 17 (. 03) .27 (. 004) 4. 64* (. 07) 7. 14** (. 03) 2. 42 (. 01) 1. 90 (. 01) .38 (. 002) 2. 47 (. 01) 1. 02 (. 005) .17 (. 001) 209 .01 (b . 001) 62 .56 (. 003) 209 Independent Variable Checks Ad relevance ? product involvement Ad relevance ? prior brand exposure Product involvement ? prior brand exposure Ad relevance ? product involvement ? prior brand exposure Between-participants effect Prior brand exposure via Web banner ads Error degrees of freedom Ad Relevance The validity of the ad relevance factor depends critically on whether participants spent more time in lab session 1 looking at NOTES—F ratios (hypothesis degrees of freedom = 1). Numbers in parentheses are effect sizes (partial ? 2): small = . 01, medium = . 06, large = . 14. Significant effects in bold. p = . 06, * p b . 05, ** p b . 01, *** p b . 001. Results Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx Fig. 2B shows that, in line with H1, ad relevance bas ed on Web browsing time increased attention to commercials for low-, but not for high-involvement products. Attention was measured by heart rate decrease (HRD): the greater the ecrease, the more attention to the commercial. But H1 was only partially supported, as this effect was significant only without prior brand exposure (H1 in Table 4), as predicted by H3 (see below). The effect of ad relevance on ads for low-involvement products generated a marginally significant main effect of ad relevance on attention (Tables 3 and 4). Similarly, planned contrasts (Winer 1991) showed that in line with H2, ad relevance based on Web browsing time increased ad exposure to commercials for low-, but not for high-involvement products (Fig. A and H2 in Table 4). Ad exposure was measured by ad viewing time: how much of an ad was seen before pressing the skip button. A longer ad viewing time means more ad exposure and less ad-avoidance. This effect delivered a significant effect of ad relevance even a fter collapsing across low- and high-involvement products (Table 3). Moderating Effects of Prior Brand Exposure: Hypotheses 3 and 4 The effect of ad relevance on attention to commercials for low-involvement products predicted by H1 was qualified by the significant three-way interaction predicted by H3, among ad elevance, product involvement and prior brand exposure (Table 3). Prior brand exposure reduced the effect of ad relevance on attention to commercials for low-involvement products, most likely because prior brand exposure reduced their information-value. After prior brand exposure, viewers paid equal attention to the test commercials, no matter what their ad relevance (Fig. 2B and H3 in Table 4). Prior brand exposure also reduced the effect of ad relevance on ad exposure to commercials for low-involvement products, as predicted by H4. After prior brand exposure, ad exposure Discussion This study tested the effectiveness of Internet-targeted TV advertising, using recent Web browsing to identify a household’s relevant TV commercials. The results suggest that this method of Internet-targeting significantly increases attention and ad exposure, even when based only on Web browsing behavior rather than search-engine keywords. These results echo similar field trials of addressable TV ads (Vascellaro 2011a) and single-source data (Siddarth and Chattopadhyay 1998), which have shown how ad relevance can increase TV ad exposure. However, these results also show that product nvolvement and prior brand exposure complicate Internettargeting of TV commercials. First, the overall effect of Internet-targeting on ad exposure in this study was due solely to its effect on commercials for A. No Prior Brand Exposure -5 Attention (heart rate decrease [bpm]) Effects of Ad Relevance: Hypotheses 1 and 2 was not significantly longer for high- versus low ad-relevance commercials for l ow-involvement products (Fig. 3B and H4 in Table 4). The results of the four hypothesis tests are summarized in Table 5. -6 -5. 84 -7 -8 -7. 88 -8. 43 -9 -9. 11 -10 Low Ad Relevance -11 High Ad Relevance -12 Low High Product Involvement B. Prior Brand Exposure -5 Attention (heart rate decrease [bpm]) Prior Brand Exposure Prior brand exposure, via Web banner ads, increased brand recall but not significantly (Mno = 4. 3% vs. Myes = 6. 8%, p = . 132, partial ? 2 = . 011). Prior brand exposure did, however, have a significant two-way interaction with ad relevance (p = . 017, partial ? 2 = . 027). When prior brand exposure was present, brand recall was significantly higher for high versus low ad-relevance TV commercials (Mlow ad-relevance = 3. 2% vs. Mhigh ad-relevance = 9. 6%, p = . 016, partial ? 2 = . 053). When prior brand exposure was absent, brand recall was not significantly different for high versus low ad-relevance commercials (Mlow ad-relevance = 5. 4% vs. Mhigh ad-relevance = 3. 9%, p = . 441, partial ? 2 = . 006). Since ad relevance was determined by Web browsing time, participants who recorded zero browsing times for their low ad-relevance categories had no prior brand exposure. No other effects were significant. In particular, prior brand exposure did not interact with product involvement, suggesting no differences in cognitive avoidance of Web banner ads in the first lab session for lowversus high-involvement products. -6 -7 -8 -7. 76 -8. 07 -7. 84 -8. 51 -9 -10 Low Ad Relevance -11 High Ad Relevance -12 Low High Product Involvement Fig. 2. The effects of ad relevance and product involvement on attention to TV commercials, measured by heart rate decrease, for the two prior brand exposure groups: (A) no prior brand exposure, and (B) prior brand exposure via Web banner ads. Pl ease cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. Journal of Interactive Marketing xx (2013) xxx–xxx 8 Table 4 Cell means. Low ad relevance Variable ? 7. 55†  Attention (heart rate decrease) No prior brand exposure Prior brand exposure Ad exposure (viewing time in seconds) No prior brand exposure Prior brand exposure High ad relevance Test Low product High product Low product High product involvement involvement involvement involvement H1 ? 6. 95 ? 7. 13x ? 5. 84x H3 ? 7. 96 ? 8. 07 H2 19. 99x 19. 18x ? 8. 32†  ? 8. 43 ? 8. 44 ? 8. 49x ? 9. 11x ? 7. 88 ? 7. 84 ? 8. 14 ? 7. 76 ? 8. 51 20. 79 21. 23x 21. 22x 21. 25 19. 48x 18. 79x H4 8. 14 ? 8. 19 20. 16 21. 01x 21. 70x 20. 33 20. 50 19. 58 21. 42 21. 46 20. 75 22. 17 NOTES—Means in the same row with the same superscript letters d iffer significantly (p b . 05) using planned contrast tests (except: †  p b . 06). which in turn increases ad liking (r = . 25, p b . 001). Although consumers have privacy concerns about targeted advertising (Spangler, Hartzel, and Gal-Or 2006), these concerns about Internet-targeted TV commercials could be alleviated if these commercials displayed the Digital Advertising Alliance’s Advertising Choices Icon and viewers could opt out from eceiving these commercials (youradchoices. com). For advertisers, these results support the concept of using Internet-targeting to reduce wastage in advertising budgets. Internet targeting also increases the effectiveness of TV commercials, by increasing ad exposure, which increases brand recall (r = . 14, p b . 05) and purchase intention (r = . 34, p b . 001). The results also show that Internet targeting is more critical for advertising low-involvement products, such as food, as opposed to high-involvement products like durables. Altho ugh changing the habitual nature of low-involvement onsumption is hard, commercials for low-involvement products may often suffer from bad timing. To combat this, many advertisers use continuous advertising (Ephron 1995), which is expensive and counterproductive by increasing prior brand exposure. Internet-targeting provides a way of continually monitoring household interest in low-involvement products, showing ads only when they are relevant and minimizing prior exposure. Relevance for habitual purchases, for which the A. No Prior Brand Exposure Implications Ad Exposure (ad viewing time [seconds]) 25 21. 70 20 0. 16 20. 33 18. 79 15 Low Ad 10 Relevance 5 High Ad Relevance 0 Low High Product Involvement B. Prior Brand Exposure Ad Exposure 30 (ad viewing time [seconds]) low-involvement products. But targeting-accuracy may not matter for high-involvement products, such as durables. Meta-analysis shows that advertising is more effective, on average, for durables rather than non-durable s (Sethuraman, Tellis, and Briesch 2011). Consumers often gather information about high-involvement products they are not planning to purchase immediately (Moe 2003; Richins and Bloch 1986). Commercials for high-involvement products attract consistently high levels of attention and ad viewing time, as sources of information during the ongoing search process for these products. For this reason, ad-relevance can be high for high-involvement products, whether or not Web browsing behavior is observed. Second, prior brand exposure reduces the information-value of advertising (Campbell and Keller 2003). Consumers pay less attention to TV commercials, evaluate them more negatively, and are more likely to avoid them (Bellman, Schweda, and Varan 2010; Woltman-Elpers, Wedel, and Pieters 2003). In this study, prior brand exposure dampens the effects of ad relevance and product involvement. Relevant commercials for low-involvement products receive more attention and ad exposure only when prior brand exposure is not present. 30 25 20 19. 58 20. 75 21. 42 22. 17 15 Low Ad 10 Relevance 5 High Ad Relevance 0 For consumers, the results of this study suggest that Internet targeting can improve their TV viewing experience. Internet targeting increases ad relevance, which means TV commercials are worth watching rather than avoiding. In this study, greater ad relevance due to Internet targeting increases ad exposure, Low High Product Involvement Fig. 3. The effects of ad relevance and product involvement on ad exposure, measured by ad viewing time for the two prior brand exposure groups: (A) no prior brand exposure, and (B) prior brand exposure via Web banner ads. Please cite this article as: Steven Bellman, et al. , Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx Table 5 Results of hypothesis tests. Hypothesis Accepted? H1. Ad relevance, based on Web browsing ehavior, will increase attention to commercials for low-, but not for high-involvement products. H2. Ad relevance, based on Web browsing behavior, will increase ad exposure to commercials for low-, but not for high-involvement products. H3. Prior brand exposure reduces the effect of ad relevance on attention to commercials for low-involvement products. H4. Pr ior brand exposure reduces the effect of ad relevance on ad exposure to commercials for low-involvement products. PARTIALLY (with no prior brand exposure) YES YES YES household does not search online, might be determined by knowledge of the household’s shopping cycle. For advertisers of high-involvement products, ad timing is less critical, and traditional databases derived from cable subscription data, or warranty cards, seem adequate for targeting. And advertising still plays a role outside the consumer search process, most importantly to create awareness and interest in new purchases (Vakratsas and Ambler 1999). Conclusions Limitations withstanding, this study demonstrates how Webbased targeting can deliver the right TV commercial to the right person, and at the right time. Timeliness is particularly important for low-involvement products, as their relevance may change aily or even hourly. Timely Internet activity data can help TV advertisers identify commercials that currently interest a consumer. Digital-targeting’s potential heightens as individuals and households increasingly add devices and applications for online multi-tasking (Pilotta and Schultz 2005). This article illustrates a viable technique to tempt marketing practitioners a nd academics, and fuel information privacy concerns. A framework for information privacy research builds on three broad dimensions: (1) multiple publics, (2) information channel developments, and (3) public responses to privacy ctions (Peltier, Milne, and Phelps 2009). Failure to address privacy concerns is one of several limitations to this study and a promising future research avenue. Limitations and Future Research Suggestions This study’s main limitation is customizing ad relevance individually rather than group-wise (Richins and Bloch 1986) in order to test the concept of Internet targeting. Individual differences provide alternative explanations and add noise to the observed ad relevance effect (Cook and Campbell 1979). Using over 30 product subcategories helps distribute this noise evenly. The procedure in this article resembles how Fazio et al. 1986) investigated attitude accessibility. In two experiments, they individually customized a list of 16 attitude objects on the 9 basis of each participant’s reaction times in a pretest, and validated this procedure in a third experiment by obtaining identical results using manipulated stimuli. Future experiments could use a similar procedure to manipulate ad relevance (Perkins and Forehand 2012). Another limitation is using Web-browsing rather than search-engine keywords to identify ad relevance. Parameters for the former were more feasible for a controlled experiment (e. g. only 72 commercials were needed). However, searchengine queries provide a more direct and accurate means of identifying the consumer’s stage in the search process (Rutz and Bucklin 2011). Future studies may find the benefits of using search-engine queries are greater (Langheinrich et al. 1999). Internet-based targeting for high-involvement products might be improved by using search-engine queries, and more sophisticated analysis of Web browsing behavior. For example, Cai, Feng, and Breiter (2004) identify travel sites as highly relevant when a visitor views pages conveying specific as pposed to general information. Moe (2006) demonstrates how clickstream data can be used to infer both the stage of the decision process and the decision rule, which together might help identify abnormally high ad relevance for highinvolvement products. This study used ad viewing time as a measure of ad exposure. But in other studies, especially field studies, the relationship between ad viewing time and effectiveness may not be positive (cf. Tse and Lee 2001). For example, Greene (1988) observed that an ad avoider in the field â€Å"has to really watch the set to see/know/perceive what she or he is doing nd ends up with more commercial exposure value† (p. 15). Future studies should attempt to replicate these findings in field trials. Also, ad exposure may have nonlinear threshold effects, 1 or be affected by differences between commercials (Woltman Elpers et al. 2003). A promising future research avenue is ex perimentally manipulating the content of ads (e. g. , Teixera, Wedel, and Pieters 2010), as well as their ad relevance. Ideally, other psychophysiological measures of attention (Potter and Bolls 2012) could have been used but in the current setting eart rate was the least invasive. The manipulation of prior brand exposure was too weak to generate a main effect on explicit memory, but did have a significant interaction effect. The explanation is most likely that prior brand exposure was manipulated by the presence of Web banner ads and these ads tend to be processed preattentively or cognitively avoided (Chatterjee 2008; Dreze and Hussherr 2003). Future studies could manipulate prior exposure using more attention-getting stimuli, such as brand integrations in Web site editorial. If Web banners are used, implicit measures 1 For example, brand recall may require a minimum ad exposure equal to 70% of an ad’s duration (21 s for a 30 s ad). To test for a non-linear threshold effect of ad exposure on brand recall, ad exposure was categorized into ? ve bins, 0–9 s, 10–15 s, 16–21 s, 22–25 s, and 26–30 s. This analysis revealed only a signi? cant linear trend (p b . 001, partial ? 2 = . 040) in the means for these bins: 0%, 1. 6%, 2. 5%, 3. 9%, 10. 5%. This result may have differed, however, if the study had measured message recall. The authors thank an anonymous reviewer for suggesting this analysis. Please cite this article as: Steven Bellman, et al. Using Internet Behavior to Deliver Relevant Television Commercials, Journal of Interactive Marketing (2013), http:// dx. doi. org/10. 1016/j. intmar. 2012. 12. 001 10 S. Bellman et al. / Journal of Interactive Marketing xx (2013) xxx–xxx of banner ad effectiveness could be used as manipulation checks (Perkins and Forehand 2012). A final limitation of this study is investigating the effect of targeting ads solely by interest in a product category. Future studies could examine the effects of other personalization strategies, such as interest in specific brands, programs, creative execution styles, and offers (Verhoef et al. 010). Each of these strategies merits evaluation and comparison in order to determine effective methods of targeting addressable TV advertising. Acknowledgments The authors would like to thank the editor and the two anonymous reviewers for their constructive feedback during the review process. The authors are also grateful to Adrian Duffell, Karl Dyktinski, Emily Fielder, Michael Gell, Shannon Longville, and a team of research assistants for their considerable help in conducting the experiment reported here. This research was funded by the sponsors of the Beyond: 30 project (www. beyond30. org). Appendix A. Manipulation-checks and other measures In addition to the two unobtrusive measures of attention and ad exposure collected during lab session 2, which were the main dependent variables, an online survey at the end of the second lab session collected self-report measures of manipulation checks and managerially relevant outcome measures. Except for product involvement (Mittal 1995; alpha = . 97), the survey used validated single-item measures (e. g. , ad liking; Bergkvist and Rossiter 2007). To accommodate the slightly different question wording required for each of the 72 brands, plus selecting only the articipant’s four test brands to ask questions about, the survey did not use a random order of questions, but the following fixed, minimally biasing order (Rossiter and Percy 1997). Brand recall (unaided correct brand recall = 1, else = 0) was measured after program liking. Purchase intention was measured next, using Juster’s (1966) 11-point scale for high-involvement prod ucts and Jamieson and Bass’s (1989) 5-point scale for low-involvement products. Ad liking was next, followed by product involvement, and finally purchasing horizon: purchase/usage frequency per month, measured by different 8-point scales for low- and igh-involvement products (low: â€Å"never† to â€Å"3 or more times a day†; high: â€Å"do not plan to purchase† to â€Å"within the next month†; Goldberg and Gorn 1987). 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Analysis of Job Description of Attaining Corporate Position at Water P

Question: Write a statement addressing the required attributes for the advertised Graduate Position at Water Partners. In writing your statement, you should make mention of any skills that you have developed while studying Financial Accounting Theory this semester. Answer: Introduction This study deals with understanding the job responsibilities of attaining graduate position at Water Partners. In this particular assignment, statement attributes are explained with advertised Graduate position as far as possible. It mentions various skills as well as job description in developing study of financial accounting theory for the same (Williams 2012). Financial Accounting Theory aims in examining various theories depending upon understanding of financial accounting in decision-making process. It explores in business entities for making decisions for accounting methods as well as disclosure of financial information in indulging in complete regulations (Spiceland, Thomas and Herrmann 2011). Part B Statement addressing the required attributes for advertised Graduate Position at Water Partners Job Description for Graduate Position at Water Partners requires essential skills and detailed understanding of financial accounting theory. Water partners as well as private clients in audit accounts (Shim, Siegel and Shim 2012) employ graduate position accountants. Graduate Accountant should be able to provide financial advices as well as undertakes accounts administration for the same. It is necessary that accountants provides financial advices to clients that ranges from multinational organization as well as government bodies to small independent business in an overall manner (Scott 2011). For attaining graduate position at Water partners, it is necessary in specializing particular areas like audit, management as well as forensic accountancy and taxation. Addition to that, accountant should have complete knowledge on assurance and corporate finance for smooth functioning of Water partners. It is important to understand the fact that accountants go through a rigorous recruitment a s well as qualification process for getting into Water partners (Previts, Walton and Wolnizer 2011). Typical duties of corporate accountant Corporate Accountant should be able to prepare accounts as well as tax returns Corporate Accountant should administer payrolls as well as controlling over income and expenditure for the same For getting corporate position, it is necessary to gain understanding on auditing financial position For gaining the position, it is essential to compile as well as present reports in form of budgets, business plans as well as commentaries and financial statements. Corporate Accountant should analyze accounts as well as business plans Corporate Accountant should provide tax returns services in reference with current legislation. They should lead as well as manages multi-disciplined team. It makes full contribution as Senior Management for working in tight deadlines For gaining the position, it is essential for financial forecasting as well as risk analysis in the upcoming years Corporate Accountant requires in dealing with insolvency cases In gaining corporate position, it negotiates in terms of business deals as well as moves with clients in associated organization. Corporate Accountant should be able in meets as well as interviewing clients for the same. They should help in business advisory as well as financial services. In gaining corporate position, accountant should be able to manage colleagues, workloads as well as deadlines in an overall manner. Typical Employers of Chartered Accountants Corporate Position at Water partners should be able to render private firms of accountants. It serves as professional services firms as well as industrial organizations (Needles and Powers 2012). They should provide operations management in accounts department especially for debtors as well as creditors ledger. Qualifications and Training required for gaining Corporate Position at Water Partners It is required to have qualification from recognized professional accountancy body. It demonstrates from employers, clients as well as public for rendering training as well as skills for performing the job in desired form (Libby, Libby and Short 2011). Qualification as Chartered Accountants takes place for at least three years starting from work experiences. It demands for study exams as well as full-time employment as well as graduates. It considers ways for packages as offered in training contract. It works towards attainment of chartered status as well as provisions in training activities for attainment of customer satisfaction (Leung 2011). It reveals salary as well as atmosphere of business firm. As part of training activities, graduates needs to complete three years of work experience. Prior gained experience comes from relevant internships and certain development objectives as well as qualification providers. Qualification depends upon fulfilment on matters relating to trainin g objectives, professional ethics as well as professional exams in the most appropriate way (Horngren 2013). Key Skills requires for attaining corporate position at water Partners It is important to understand the fact that corporate accountants go through rigorous recruitment as well as qualification process in reflecting high qualification status. Employers look for graduates in accordance with attaining skills like: In order to undertake corporate position at Water Partners, it is necessary to posses enough self-motivation for handling difficult tasks as well as challenges for the same (Dyckman, Magee and Pfeiffer 2011). It is essential to posses enough responsibility in the business firm and helping attitudes at the same time (Spiceland, Thomas and Herrmann 2011). It should have ability in reflecting own work and wider consequences in respect with financial decisions in the most appropriate way It should indulge in business acumen as well as interest in an effective way It should posses enough organizational skill as well as ability in managing deadlines in an accurate form Corporate Accountant should have attributes in working as team as a whole They should involve in client facing as well as posses interpersonal skills They should have analytical ability in methodological approach for numerical. Conclusion From the above analysis, it gives detailed analysis of job description of attaining corporate position at Water partners. On critical analysis, it is understood that financial accountants provides specialist services to Water partners. It ensures preparation of financial statements based upon general ledgers as well as participating in important financial decisions at the same time. It requires involving in mergers as well as acquisition in respect with planning and long-term financial projections in an overall manner. It requires performing external audits by examination in financial statements. It performs internal audits as well as fair representation of legal requirement at water Partners. Reference List Dyckman, T., Magee, R. and Pfeiffer, G. (2011).Financial accounting. [Westmont, Ill.]: Cambridge Business Publishers. Horngren, C. (2013).Financial accounting. Frenchs Forest, N.S.W.: Pearson Australia Group. Leung, D. (2011).Inside Accounting. Farnham, Surrey, England: Gower. Libby, R., Libby, P. and Short, D. (2011).Financial accounting. New York: McGraw-Hill/Irwin. Needles, B. and Powers, M. (2012).Financial accounting. Mason, OH: South-Western Cengage Learning. Previts, G., Walton, P. and Wolnizer, P. (2011).A global history of accounting, financial reporting and public policy. Bingley: Emerald. Scott, W. (2011).Financial accounting theory. Toronto, Ont.: Pearson Canada. Shim, J., Siegel, J. and Shim, J. (2012).Financial accounting. New York: McGraw-Hill. Spiceland, J., Thomas, W. and Herrmann, D. (2011).Financial accounting. New York: McGraw-Hill/Irwin.

How to Use Long-Tail Keywords to Improve Your WordPress Sites SEO

You probably know how important keywords are to your website. Theyre a crucial part of any Search Engine Optimization (SEO) strategy, helping you rank higher on sites like Google. However, you may not know that a distinction can be made between short-tail and long-tail keywords.This difference is important, because while many sites exclusively target the big ticket short-tail keywords, focusing on their longer cousins can be a more viable strategy. Long-tail keywords are more precise, so theyre better able to attract your target audience. Plus, youll face less competition when trying to rank highly with them.This guide to long-tail keywords will explain what they are, and make it clear why you might want to start using them in your content strategy. Then, well show you how to get started! Dog care is an example of a traditional, short-tail keyword. Its broad enough to apply to many Google searchers. Most short-tail keywords are one or two words long, such as fitness or used cars.Unde rstanding what people search for online is key to getting your content noticed.In contrast, a long-tail keyword is usually three or more words long, often capping out at five or six words.So instead of targeting dog care, your blog post could use the keyword how to care for a dog. Other examples of long-tail keywords might include how to improve my fitness and find used cars nearby. Despite what seems like a small difference, there are some compelling reasons to use this type of keyword.Why you should start using long-tail keywordsTraditionally, most SEO advice has focused on short-tail keywords. These keywords give you access to the widest audience, since short keywords nearly always have a higher search volume. While cook pasta might have a hundred thousand daily searches, how to cook homemade pasta might only have ten thousand.However, long-tail keywords have their own unique advantages:Theyre more descriptive, and tell people more about your contents topic. So while youre target ing a smaller pool, its made up of people who are more likely to be interested.Theres less competition for longer keywords. This means you dont have to fight for views with hundreds of established websites.Youll often see SEO benefits, since long-tail keywords help search engine bots recommend your content to the right people.Long-tail keywords are often easier to work into your content naturally.Longer keywords tend to have lower search volumes and less competition.Of course, this isnt an either-or choice. Theres no reason you cant target both long and short keywords on your site. Long-tail keywords are increasingly proving their effectiveness, however, so now is the time to start using them.Where to start looking for long-tail keywordsIts always smart to develop your keywords through research. That way, you can find phrases people are actually searching for. The simplest way to start generating some long-tail keyword ideas is to use the Google search engine itself.Youve probably n oticed that Google suggests alternative keywords to searchers. These suggestions are based on real queries, so theyre excellent options for you to use. Start by typing in a few words describing the topic you need a keyword for. In most cases, Google will immediately provide a list of options:If you scroll down to the bottom of the page, youll also see a section listing related searches:Both places are perfect for spotting longer, more specific keywords that Google users are actually searching for. You can also use a dedicated research tool, such as the Google Keyword Planner. This is a free resource that will show you the search volume and competition level for just about any keyword.The Google Keyword Planner  provides useful information about keyword analytics.Another good tool to help you find longtail keywords is KWFinder. It gives you three different methods of uncovering longtail keywords that people search for.Regardless of where you go, youll want to look for keywords that have low competition, but still offer a decent search volume. Youll also want to focus on those you can work naturally into your content. Ultimately, finding strong long-tail keywords isnt any harder than doing the same with shorter keywords. Just remember to stick with phrases that are at least three words long.How to use long-tail keywords effectivelyOnce you have a long-tail keyword to target, you simply need to incorporate it into your content. The process isnt much different than using short-tail keywords, so if you have some SEO experience you should know what to do.All the same, here is the general process youll want to follow when using long-tail keywords:Start by finding a keyword and writing content based on it, instead of the other way around. That way, you know you have a built-in audience. Youll also want to choose a different keyword for each major piece of content (such as a page or blog post).Incorporate the keyword into multiple places, but be careful not to overus e it. Long-tail keywords tend to stand out more, and readers might catch on if you use it every other paragraph. Try to use it in the title, at least one header, the first paragraph, and occasionally throughout the text.Make sure youre using the keyword naturally, rather than stuffing it into sentences where it doesnt belong.Add the keyword to other crucial places, such as your contents meta description and your images alt text.Finally, dont forget to track your keywords performance! The information you get will help you make better choices over time, so you can be confident that youre targeting the best long-tail keyword options.ConclusionCompetition is fierce for many of the most popular keywords used in online searches. Therefore, it can be smart to focus your efforts on longer, more specific phrases. The pool of searchers youre targeting will be smaller, but youre likely to attract a lot more of them if you use long-tail keywords effectively.To find long-tail keywords to use in your content, you can start by checking out Googles suggested and related searches. The Google Keyword Planner will also be an invaluable tool. Then you can incorporate your new keywords into your content. Just remember to use them naturally, and follow the usual SEO best practices.Do you have any questions about how to incorporate long-tail keywords into your own content? Ask away in the comments section below! Here's how to start using long-tail #keywords to improve your #SEO

Organizational Culture and Decision Making Example

Organizational Culture and Decision Making Example Organizational Culture and Decision Making – Article Example ï » ¿ Organizational Culture and Decision Making An organisation is often recognised by the culture that is prevalent in the organisation and the mode of working followed. This is not solely a management concept relevant to companies, but also to healthcare units. By organisational culture, we mean, the attitudes, values and ethical perception of the organisation and how it works in different situations. â€Å"Organization culture is the emergent result of the continuing negotiations about values, meanings and proprieties between the members of that organisation and with its environment†. (Organizational Culture: An Introduction, edited by Nasreen Taher, Hyderabad: ICFAI University Press, 2005, pp 82-92.) Organisational culture often characterises the way an organisation functions and how major job requisites are carried out. Let us take the example of a healthcare unit whose culture is characterised by an open door policy, where the doctors and paramedics are approachable. The decision-making strategy in such an organisation would be one that would be open to all and sundry, or would at least involve individuals from all the hierarchal branches, rather than being limited to the top crux. This illustration clearly elucidates the view that an organisation’s culture often impacts decision-making in the organisation. (Website: culturecreation.com.au/) When an organisation makes changes in its strategy, it must take care not to keep the information limited to its top hierarchy and must make sure it penetrates to reach all levels of employees. This is because of the fact that every employee and his work functioning plays a great role in carrying forward a strategy made by the organisation. Change in strategy needs to be a combined effort from all quarters. It also impacts the culture at the organisation, since work processes begin to differ. For instance, if an organisation makes the decision that it shall adopt a more aggressive marketing strategy, it comes up with special treatments and varied infrastructural facilities and involves every paramedics assistance. This is because, only then will the strategy work effectively with each and every employee contributing a more aggressive stance and output, furthering the overall strategy of the organisation. In addition to this, the workplace culture must be global and cosmopolitan in a healthcare unit, since it caters to no specific crowd. The patients could come from varied backdrops of life and it is essential to embrace a cosmopolitan stance, in order to avoid any sort of intimidating scenarios. This would also help bind the staff and paramedics together, and help them counter problems or act in a united manner. Thus, adopting a globally applicable culture is a great way to boost the healthcare unit in terms of its ambience and atmosphere. Thus, it is evident by what has been outlines, that organisational culture is an important parameter in almost every activity of a healthcare unit. A healthcare unit must most certainly work towards developing a more interactive and employee-friendly culture to facilitate better cooperation and coordination amongst employees. REFERENCES Website: culturecreation.com.au/ Organizational Culture: An Introduction, edited by Nasreen Taher, Hyderabad: ICFAI University Press, 2005, pp 82-92. Website: www.ezinearticles.com

Business Enterprise Essay Example | Topics and Well Written Essays - 1000 words

Business Enterprise - Essay Example â€Å"A business model describes the rational of how an organization creates, delivers and captures value† (Osterwalder & Pignuer, 2009). A business model canvas is a visual chart. The elements in the chart will describe the firm’s value proposition, infrastructure, customers and finances. It describes its elements through the building blocks. Key partners as well as key suppliers have to be included in this part of the model. For the success of the site Spotify needs a good deal with the related parties like the recording company. Another key partner is Facebook. All the account holders of Facebook have an opportunity to deal with Spotify. Key resources are required to offer the value proposition to the customers; or deliver what the customers want. Key resources can be â€Å"physical, intellectual, human and financial resources† (Osterwalder & Pignuer, 2010). The key resource for this company is music. Since, it has to make available all music to the entire world, so the music license has to be obtained. A server is also required to reach the customer. Value proposition is something which the company is giving to its customers. In other words, the factors which are forcing the customer to buy the products of the company are termed as the value proposition of the company. Here, the value proposition is between the listeners and the advertisers. The value proposition for the listeners is that, it offers a large amount of music for least cost. And the site is legally registered. The songs can be listened through a smartphone and can be listened offline too. Another offer is that we can share songs. For the advertisers, the site is making a platform to advertise their products and services. In the current context, customer is considered as a king. Companies are required to give what the customers want. In service industries also, the company have to keep in

GASB and FASB Accounting Essay Example | Topics and Well Written Essays - 750 words

GASB and FASB Accounting - Essay Example Whereas FASB has the objective to establish and improve standards for financial accounting and reporting that will help in guiding and educating public including auditors and other users of financial statements.   GASB was constituted in 1984 to succeed National Council on Government Accounting as a standard-setting body for state and local governmental bodies, whereas FASB issues standards and other pronouncements for entities other than governmental bodies. However, when there are no pronouncements on certain issues from GASB, the pronouncements issued by the FASB shall become applicable to governmental bodies as well. So far as business organizations are concerned, they have to abide by the standards issued by FASB. Non- business organizations, non- government organizations follow FASB and the government organizations come under the domain of GASB.   GASB is very specific to state legislature while issuing pronouncements. FASB, on the other hand, issues pronouncements that are universal and cater the business on a federal basis. In fact â€Å"FASB receives many requests for action on various financial accounting and reporting topics from all segments of its diverse constituency, including investors and the SEC. The auditing profession is sensitive to emerging trends in practice, and consequently, it is a frequent source of requests. Requests for actions include both new topics and suggested review or reconsideration of existing pronouncement.†(Facts about FASB, page 1)   It is believed that governments need not show profits like other financial entities.

Harsh Parenting during Adolescence Research Paper

Harsh Parenting during Adolescence - Research Paper Example More often than not these social constraints are enforced and reinforced by parents. (Choudhury, Blakemore and Charman) A variety of reasons are prescribed for parental control including (but not limited to) the rebellious attitude of teenagers, the parent’s desire to make the individual more conforming to their ideals and ideologies and the need to make the individual more compliant to social norms and values. These objectives are met by parents in a variety of ways. The relationship between teenagers and parents is generally a rocky one. In order to exert their influence, parents may resort to physical and emotional coercion. (Kelley) Such parental behaviour is seen to affect adolescent growth and their adult behaviour negatively. Most adolescents with coercive parents are known to develop aggressive symptoms later in life. This aggression may be emotional or physical and may continue throughout an adult’s life unabated. (Pedersen) Though the effects of parental contr ol on adolescent behaviour are well documented but the immediate outcomes have been historically overlooked. Parents exerting themselves on children encourage the growth of individuals who are seeking chances to overthrow the established regime of parental control. The results are often disastrous such as school shootouts such as the Columbine massacre. Moreover, teenagers may resort to joining gangs or resort to drug use in order to exert their independence. It remains notable here that all forms of parental control result in deviant social behaviour. Therefore it can be hypothesised that excessive parental control during adolescence can lead to an increase in deviant behaviour in society. This text attempts to analyse such a relationship through secondary research. Literature Review Numerous studies have been conducted in order to clarify the connection between parental exertion and resulting adolescent behaviour. Various perspectives and aspects have been covered through these st udies. This text was prepared by reviewing a few instrumental studies and their results which are discussed below. The distinction between physiological control and behavioural control for human beings has long been established firmly. (Baumrind) Baumrind’s study was conducted over a fourteen weeks period where he observed three different groups of children. The behaviour of each group was markedly different. One group was composed of energetic and friendly children while another group was composed of conflicted children who were irritable. The last group was composed of impulsive and aggressive children. The parents of these children were interviewed to discern the distinct patterns of parenting. There is an overwhelming tendency to combine these two aspects of human control and to study their effects together. Such an approach is hardly considered feasible as it tends to coalesce related aspects so that they are not distinctly recognisable anymore. For example the psycholog ical effects of beatings on a child who is being cajoled psychologically as well cannot be distinctly related. The typological approach developed by Baumrind is highly helpful in this regard as it delineates categorical distinctions to psychologically and behaviourally controlling parents. For example, authoritative parents are represented as being warm and accepting. Such parents tend to establish strict behavioural guidelines but promote psychological