Instructions For this assignment, you will write an essay in which you compare and contrast the following strategic measurement tools used by business and human resource professionals as presented in

Keywords: Economic value added, earnings, cash flow, market value added INTRODUCTION Due to the changes in the business environment, business community is looking for more powerful performance measures that overcome the problems associated with the traditional accounting measures, in terms of emphasizing shareholders value maximization, which has become the obsession for managers and capital providers. The traditional accounting measures have been criticized because they failed to represent faithfully: the factors that drive shareholder value (Chari, 2009), profitability (Al-Mamun & Abu-Mansor, 2012), and the financial situation of the firms (Bluszcz, Kijewska & Sojda, 2015). In recent years, firms have been focusing on creating value for their shareholders (Sirbu, 2012), and the value maximization has become a well accepted objective among them (Bhasin, 2013), so the attention should be paid to the elements of shareholders value creation (Ganea, 2015). In this regard, new performance measures have been introduced (Abdeen & Haight, 2002; Chari, 2009), such as Economic Value Added (EVA), Market Value Added (MVA), Cash Flow Return on Investment (CFROI), Total Shareholder Return (TSR), Shareholder Value Added (SVA), and Value Added Management (VAM). EVA, which is considered one of the most popular value indicator measure, is a trade mark developed in the early 1990s by Stern Stewart & Co., a New York based consulting firm that claimed that EVA is superior to traditional accounting measures in measuring shareholder value. The idea behind EVA is that the firm adds value to shareholders if it earns more than the cost of capital employed, where the cost of capital includes the total costs of borrowed capital and equity capital. In other words, EVA is the profit earned by the firm minus the cost of capital.

If EVA is positive, the firm is creating value for its shareholders, and if it is negative, the firm is destroying value. So, EVA differs in that it considers the cost of all capital employed, and not just the cost of borrowed capital as the traditional accounting measures do. Many researchers considered EVA helpful in: indicating how successful a firm is in creating value for shareholders (Epstein & Young, 1998), making financial decision, (Goldberg, 58 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 1999), analyzing capital budget and securities (Kramer & Peters, 2001), valuing investments (Sparling & Turve, 2003), enhancing business environment (Tsuji, 2006), measuring performance (Sharma & Kumar, 2012), identifying investment opportunities (Bhasin, 2013) and determining remuneration policy (Ganea, 2015).

Some other researchers doubted that EVA is a new discovery. Kyriazis and Anastassis (2007), Bhasin (2013), and Nagarajan (2015) argued that a similar concept had been contemplated by economists such as Alfred Marshall for many years before that, particularly in 1890, who spoke about the economic profit, in terms of the real profit that firms make when it covers the cost of its invested capital. Also the Finnish academics and financial press discussed this concept in the early 1970s. In the same context, Goldberg (1999), Keys, Azamhuzjaev & Mackey (2001), De Wet (2005), and Nagarajan (2015) asserted that EVA is a relatively recent variant of residual income, an older financial measure that did not get wide publicity and was abandoned by firms years ago, whereas the difference between EVA and residual income lies in the various adjustments in the financial statements suggested by Stern Stewart & Co. These adjustments aimed to remove the distortions in the accounting profit caused by accounting rules (Machuga, Pfeiffer, & Verma, 2002), and because Stern Stewart & Co.

suggested more than 160 adjustments, many researchers criticized EVA. Goldberg (1999) argued that the cost of EVA may exceed its benefits. Keys, Azamhuzjaev & Mackey (2001) argued that EVA calculation is very complex and too difficult to understand, especially the calculation of the cost of capital. Bhasin (2013) argued that the complex calculation of EVA may lead to calculation errors that lead to misleading results. Regardless of these criticisms for EVA, Large well known firms including Coca-Cola, Polaroid, Sprint Corporation, AT&T, CSX, DuPont, Eli Lilly, Quaker Oats, Briggs & Stratton, and Toys ‘R Us have utilized EVA in investment decisions, capital reallocation, and the performance evaluation (Kramer & Pushner, 1997; Tortella & Brusco, 2003; Al-Mamun & Abu- Mansor, 2012). Recently, Stancu et al. (2017) have asserted that “EVA is the most widely used indicator by firms and financial advisors to measure the company's performance”. While EVA is considered an internal single-period measure of firm performance, MVA is a more forward looking measure (Kramer & Pushner, 1997). MVA is considered a cumulative measure of the value created by the firm (Kramer & Peters, 2001), which is the difference between the market value and the book value of capital (Sparling & Turve, 2003), and from investors’ point of view, MVA is the best external measure of a firm’s performance (De Wet, 2005). There is a general belief that, in order to maximize shareholders value, firms should maximize MVA, and the best way to do so is by maximizing EVA (De Wet & Hall, 2004) because MVA is the sum of all future EVAs (Poornima, Narayan, & Reddy, 2015). In this regard, Khan, Aleemi, and Qureshi (2016) argued that the debate is still on about the superiorit y of EVA over the traditional accounting measures.

Whereas the previous empirical studies revealed controversial results regarding which is superior in explaining MVA; is it EVA or the traditional accounting measures? (Altaf, 2016). This study investigates if Economic Value Added (EVA) is superior to Net Operating Profit after Tax (NOPAT) and Net Cash Flow (NCF) in explaining the change in the Market Value Added (MVA) of the non-financial firms listed on Amman Stock Exchange (ASE) for the year 2016. The results indicated that NCF has the strongest power in explaining the change in MVA, followed by EVA. The results also indicated that the NOPAT does not add additional significant explanatory power to NCF and EVA in explaining the change in MVA. International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 59 LITERATURE REVIEW After the introduction of EVA as a performance measure used in assessing firm's ability to create value for shareholders, studies have revealed controversial results regarding the superiority of EVA over the traditional accounting measures. The most related previous studies supporting the superiority of EVA are presented next, followed by the most related previous studies that do not support the superiority of EVA. Machuga, Pfeiffer, and Verma (2002) examined the effectiveness of EVA and EPS in predicting future earnings. The results indicate that EVA contains more incremental information than EPS in predicting future earnings. Prakash et al. (2003) investigated the impact of adoption of EVA on the key financial ratios as a proxy of firm's performance. The results indicated that most of the financial ratios were significantly improved after the adoption of EVA. Worthington and West (2004) examined whether EVA is more associated with stock returns than traditional accounting measures such as earnings and net cash flow for 110 Australian companies over the period 1992 – 1998. Results indicated that EVA is more closely related to stock returns than traditional accounting measures. Kim, Jae-Hyeon, and Yun (2004) investigated the significance of EVA, after controlling firm stage (contraction period vs. expansion period) and sector (manufacturing vs. non- manufacturing). In addition, they investigated if stock prices follow EVA or the traditional accounting measure such as EPS. The results indicated a positive correlation between EVA and MVA during the contraction period and indicated that the market response to EVA and traditional accounting measure differed between manufacturing and nonmanufacturing sectors.

Sharma and Kumar (2012) examined if EVA can be used as a tool of performance measures and if it is considered better than the traditional accounting measures in Indian market. The results indicated that investors should use EVA along with the traditional accounting measures for decision making. Al-Sheikh (2012) measured the relationship between EVA and the market value of stock prices. The results indicated that there is a relationship between the EVA and the market price per share and this relationship is stronger than the traditional accounting measures. Abu-Wadi and Saqfalhait (2016) analyzed the effect of traditional accounting measures represented by the rate of return on equity and EVA on MVA for Jordanian commercial banks. The results indicated that the both indicators have a significant positive effect on MVA with superiority for EVA. Contrary to the previous studies; Kramer and Pushner (1997) tested the relationship between EVA and MVA. The results did not support the arguments that EVA is the best measure of corporate success in adding value to shareholder. Turve and Lake (2000) examined the relationship between EVA and the stock market performance in the Canadian food processing sector. The results provided little support that high-EVA firms lead to high shareholders value.

Kramer and Peters (2001) tested if EVA could be considered as a proxy for MVA across 53 industries. The results indicated that there is no marginal benefit from using EVA as a proxy for MVA instead of the traditional accounting measure like net operating profit after tax. Sparling and Turve (2003) assessed the strength of the relationship between EVA as a tool for valuing investments and shareholder return. The results indicated a weak correlation between them. De Wet (2005) analyzed the relationship between some traditional accounting measures (e.g., cash flow from operations and earning per share) and EVA with MVA as a proxy for shareholder value in South Africa market. The results did not indicate the superiority of 60 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 EVA, and indicated that the stronger relationships exist between MVA and cash flow from operations. Kyriazis and Anastassis (2007) investigated the explanatory power of EVA and traditional accounting measures with respect to stock returns and firms’ market va lue in Athens Stock Exchange. The results indicated that EVA does not have a stronger correlation with firms’ MVA than the traditional accounting measures. Visaltanachoti, Luo, and Yi Yi (2008) compared EVA with traditional accounting measures (e.g., cash flow from operations, earnings before income tax, and residual income) in terms of its relationship with sector returns. The results indicated that the association between sector returns and the traditional accounting measures is higher than that with EVA. Bhasin (2013) analyzed the effectiveness of EVA over the traditional accounting measures. The results indicated that there is no strong evidence to support the superiority of EVA over the traditional accounting measures in its association with MVA. Khan, Aleemi and Qureshi (2016) examined if EVA have superiority over the traditional accounting measures (e.g., return on equity, return on assets, operating cash flows and earning per share) in explaining stock price of non-financial firms listed on Karachi Stock Exchange for the period 2009-2012. The results indicated that the traditional accounting measures outperformed EVA in explaining the behavior of stock prices. Altaf (2016) tested if EVA is a better indicator than traditional accounting measures in explaining MVA for manufacturing and service firms in India. The results indicated that the operating income has the strongest relationship with MVA in both sectors, while EVA showed a weak positive relationship with MVA.

HYPOTHESES The aim of this study is to investigate if Economic Value Added (EVA) is superior to Net Operating Profit after Tax (NOPAT) and Net Cash Flows (NCF) in explaining the change in Market Value Added (MVA) of the non-financial firms listed on Amman Stock Exchange (ASE) for the year 2016. Based on the stated aim, the following null hypotheses were developed and tested: H 1: Net Operating Profit after Tax (NOPAT) is superior to Economic Value Added (EVA) in explaining the change in Market Value Added (MVA). H 2: Net Cash Flow (NCF) is superior to Economic Value Added (EVA) in explaining the change in Market Value Added (MVA).

CALCULATION OF EVA, WACC AND MVA EVA CALCULATION Abdeen & Haight (2002) stated that “In its simplest terms, EVA measures how much economic value in dollars the company is creating, taking into account the cost of debt and equity capital”. In other words, EVA represents the return that the firm must generate to satisfy the capital providers (Chari, 2009). (1) Capital of CostTax Afterofit Operating Net EVA   Pr International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 61 As mentioned previously, to calculate EVA, Stern Stewart & Co. suggested more than 160 adjustments to eliminate distortions in firm NOPAT and capital in an attempt to refine the accounting income to be closer to economic income. The most common adjustments include (Abate, Grant, & Stewart, 2004; Alihodžić, 2013): capitalized R&D, goodwill amortization, LIFO reserve, operating lease, pension expense, provisions for doubtful receivables, one-off cost of restructuring. Sirbu (2012) argued that only five to seven key adjustments are made in practice. Nagarajan (2015) justified this, when he concluded that EVA calculation will be more complicated if all of these adjustments are made. Accordingly, the final version of EVA equation could be represented as follows:

\ (2) Where: : Adjusted net operating profit after tax, : Adjusted invested capital, : Weighted average cost of capital.

The firm is creating value (wealth) for its shareholders if EVA is positive, and is destroying value if EVA is negative.

WACC CALCULATION The WACC represents an average rate of return that a firm must pay to its shareholders and creditors (Alihodžić, 2013), and is calculated by calculating the cost of each source of capital, and then the weights of each source are assigned on the basis of proportion of each source to the total capital employed. The weights can be assigned on book value basis or market value basis, but Stern Stewart & Co. recommended the market value basis (Madhavi & Prasad, 2015). \ (3) Where: : Cost of equity capital, which is calculated according to Dividends Capitalization Model, whi ch is equal to: (dividends per share for the next year ÷ current market share price) + dividends growth rate, : Cost of debt capital (weighted average cost of borrowed capital), : Market value of equity capital, : Market value of debt capital, : Tax rate. Although Stern Stewart & Co. recommended the use of market value basis to calculate the WACC, the book value basis was used in this study because the data of market value of debt is not available in ASE.

) ( 1WACC IC NOPAT EVA it adj it adj it it    NOPAT adj it IC adj it 1  WACC it   T MM M C MM M CWACC D E D D D E E E it      1 C E C D M E M D T 62 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 MVA CALCULATION The MVA is a measure of the wealth a firm has created for its shareholders. It is the difference between the total market value of the firm and the total capital invested in the firm (Kim, Jae-Hyeon, & Yun, 2004). The total market value of the firm is the sum of the market value of its equity and the market value of its debt (De Wet, 2005). \ (4) Where:

: Firm market value, : Invested capital.

In the absence of information about the market value debt capital, MVA could be calculated from the perspective of common shareholders, and it equals the excess of the market value of equity capital over the book value of equity capital (Thenmozhi, 2000; Abu-Wadi & Saqfalhait, 2016).

\ (5) Where: : Market value of equity capital, : Book value of equity capital, As with EVA, the firm is creating value for its shareholders if MVA is positive, and is destroying value if MVA is negative.

RESEARCH METHODS Sample and data Collection The study initial sample consisted of (97) firms, representing all the non-financial firms listed on ASE for the year 2016, (26) firms with insufficient information to compute the study variables were excluded, leaving (71) firms that were examined, representing approximately 73% of the population. Data were collected from firms’ annual reports and ASE online databas e. For each sample firm, the data of net operating profit before tax (NOPBT), net cash flow (NCF), equity capital, borrowed capital, interest rates and the information required to make Stern Stewart & Co. suggested adjustments were obtained from firms’ ann ual reports. The data of firm market value, stock market price, dividends, and dividends growth percentages were obtained from ASE online database. IC FMVMVA it it it   FMV it IC it BM MVA EE it  M E B E International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 63 Measurement of Variables Net operating profit after tax (NOPAT), net cash flow (NCF), and economic value added (EVA) represent the independent variables in this study. NOPAT is calculated as the net operating profit before tax (after adjustments suggested by Stern Stewart & Co.) minus the applicable income tax, taking into account that the tax rates levied on the non-financial firms listed on ASE range between (14%-24%), depending on the nature of industry or service. NCF is obtained directly from the cash flow statement. EVA is calculated using equation (2) above. Taking into account the most common adjustments suggested by Stern Stewart & Co., the only adjustments that were made on NOPAT and invested capital were: Goodwill amortization, capitalized R&D, one-time restructuring charges, operating lease, and pension expense. The other common adjustment could not be performed due to the insufficient disclosures in firms’ financial reports. The change in Market Value Added ( ΔMVA) represents the dependent variable in this study and is calculated as the difference between the MVA at the end and beginning of th e period. Where the MVA is calculated using equation (5) above. According to Kramer and Pushner (1997) and De Wet (2005), the MVA is calculated at a specific moment and in order to assess whether the value has been created or destroyed, the change in MVA from one date to another should be used. RESULTS AND DISCUSSION Table 1 presents summary statistics of NOPAT, NCF, EVA, MVA at the beginning and at the end of the study period, and the change in MVA during the study period for the sample firms. As shown, NOPAT and EVA are positive on average, while NCF is negative. EVA shows a lower average than NOPAT, indicating the influence of the cost of capital on operating profit.

Although NOPAT and EVA show a positive average, the change in MVA shows a negative average. This provides an initial indication that the NCF, which has a negative average, may have the highest effect on the change in MVA. Table 1 Summary Statistics * NOPAT NCF EVA Δ MVA Mean 3,908 (3,320) 453 42,321 32,601 (9,720) Max. 49,839 82,117 41,852 1,207,730 1,040,151 424,068 Min. (61,483) (105,290) (65,712) (559,148) (763,097) (540,773) S.D. 12,024 20,998 11,081 196,177 196,061 88,168 * Numbers in Thousand US Dollars Table 2 presents Pearson correlation matrix among the study variable. As shown, the correlation coefficients indicate the non-existence of multicollinearity. MVA is significantly positively correlated with all the independent variables, where the NCF shows the strongest correlation followed by EVA and then by NOPAT. The results also indicated a positive significant correlation between EVA and NOPAT, while there is no significant correlation between NCF and NOPAT.

MVA t1  MVA t 64 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 Table 2 Pearson Correlations Matrix Variable NOPAT NCF EVA Δ MVA NOPAT 1.000 NCF 0.074 1.000 EVA 0.792 ** 0.271 * 1.000 Δ MVA 0.250 * 0.633 ** 0.462 ** 1.000 * Significant at p < 0.05 level ** Significant at p < 0.01 level To test the study hypotheses a univariate and multivariate regression analysis were performed. The univariate regression aimed to find out the superior independent variable that explains the change in MVA, while the multivariate regression aimed to find out the best set of independent variables that explain the change in MVA. The regression models that were performed and tested are: \ (6) \ (7) \ (8) (9) Table 3 Univariate Linear Regression Results Unstandardized Coefficients R Square Adjusted R Square ANOVA B Std.

Error Beta t Sig. F Sig. Panel A: Model (6) Constant * (16,886) 10,737 - 1.573 .120 .063 .049 4.602 .035 NOPAT 1.834 .855 .250 2.145 .035 Panel B: Model (7) Constant * (899) 8,264 - .109 .914 .400 .392 46.063 .000 NCF 2.657 .391 .633 6.787 .000 Panel C: Model (8) Constant * (11,383) 9,356 - 1.217 .228 .213 .202 18.710 .000 EVA 3.675 .850 .462 4.325 .000 * Unstandardized Coefficients values for constant are in Thousand US Dollars. Panels A, B, and C of Table 3 present the results of univariate regression of NOPAT, NCF, and EVA (respectively) on the change of MVA. As shown, all of these independent variables are statistically significant in explaining the change in MVA (p<.05), but they differ in their explanatory power. The adjusted R square results indicated that NCF has the strongest explanatory power, as it explains (39.2%) of the variance in ΔMVA, followed by EVA with (20.2%) explanatory power, and finally by NOPAT with (4.9%) explanatory power. Also, the Beta results confirm that NCF have the strongest contribution in explaining the dependent ii i NOPAT MVA   10 ii i NCF MVA 10 ii i EVA MVA 10 ii i i i EVA NCF NOPAT MVA   3 2 10 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 65 variable outcomes, followed by EVA then by NOPAT. These results provide additional support to the initially revealed results concerning the strong power of NCF in explaining the change in MVA. The results also show that the regression coefficients for all the independent variables are positive, confirming the Person correlation results regarding the positive relationship between MVA and the independent variables.

Table 4 presents the results of Stepwise Multiple Regression. The method of Stepwise was used to find out the best combination of independent variables that best explain the change in the dependent variable, and to eliminate the independent variables that do not have significant contribution in the explanatory power. As shown, after performing this regression, the independent variable of NOPAT was dropped from the regression model, indicating that NOPAT does not add additional significant explanatory power to the other independent variables. The resulting model that includes the variables of NCF and EVA is significant (p<.05) and have explanatory power of (47.6%).

Table 4 Stepwise Multiple Regression Results Unstandardized Coeffic ients R Square Adjusted R Square ANOVA B Std.

Error Beta t Sig. F Sig. Model (9)** Constant * (899) 8,264 - .109 .914 .400 .392 46.063 .000 NCF 2.657 .391 .633 6.787 .000 Model (9)*** Constant * (3,212) 7,697 - .417 .678 .491 .476 32.824 .000 NCF 2.300 .377 .548 6.094 .000 EVA 2.492 .715 .313 3.485 .001 * Unstandardized Coefficients values for constant are in Thousand US Dollars. ** Predictors: Constant, NCF. *** Predictors: Constant, NCF, EVA. The previous findings provide support for rejecting the first null hypothesis which proposed that “Net Operating Profit after Tax (NOPAT) is superior to Economic Value Added (EVA) in explaining the change in Market Value Added (MVA)”, and accepting the s econd null hypothesis which proposed that “Net Cash Flow (NCF) is superior to Economic Value Added (EVA) in explaining the change in Market Value Added (MVA)”. On the one hand, the result concerning the superiority of EVA over NOPAT in explaining MVA is consistent with the results of the previous studies of (Kramer & Pushner, 1997; Kim, Jae-Hyeon & Yun, 2004; Abu-Wadi & Saqfalhait, 2016) that revealed that EVA is superior to the traditional profitability measures in explaining MVA. On the other hand, the re sult concerning the superiority of NCF over EVA in explaining MVA is consistent with the results of the previous studies of (De Wet, 2005; Visaltanachoti, Luo & Yi Yi, 2008; Khan, Aleemi & Qureshi, 2016) that revealed that the traditional cash flow measure are superior to EVA in explaining MVA.

66 International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 CONCLUDING REMARKS Motivated by the continuous debate about the superiority of Economic Value Added (EVA) over the traditional accounting performance measures in explaining the Market Value Added (MVA), as a proxy for shareholder value, this study investigated if EVA is superior to Net Operating Profit after Tax (NOPAT) and Net Cash Flow (NCF) in explaining the change in Market Value Added (MVA). A sample of (71) non-financial firms listed on Amman Stock Exchange (ASE) for the year 2016 were analyzed. Univariate and multivariate regression analyses were performed in order to empirically test the study hypotheses. The univariate regression results indicated that NCF have the strongest explanatory power in explaining the change in MVA, followed by EVA and finally by NOPAT. This was confirmed by the stepwise multivariate regression, which was performed to find out the best set of independent variables that explain the change in MVA, where the final significant regression model includes only the NCF and EVA, while the NOPAT was dropped because it does not add additional significant explanatory power to NCF and EVA in explaining the change in MVA. In light of the results of this study and previous studies, it could be argued that the debate about the superiority of EVA over the traditional accounting measures will continue. Two possible justifications to the mixed and controversial results could be taken into consideration:

First, MVA is the appreciation of the firm market value over the book value of its invested capital. Where, the firm market value is the sum of the market values of its equity and debt. So, the MVA is affected by firm stock market price, which in turn could be affected by other factors (e.g., economic va riable, investors’ behaviors, supply and demand) that differ across countries.

So, the empirical results concerning the superiority of EVA over the traditional accounting measures will differ. In this regard, Kramer & Pushner (1997) stated that “much of th e determination of MVA remains unexplained”. Second, the developer of EVA (Stern Stewart & Co.) suggested more than 160 adjustments to eliminate the distortions in the accounting profit. These adjustments made the calculation of EVA very complex, as stated by Keys, Azamhuzjaev & Mackey (2001) and Nagarajan (2015), which in turn was reflected on the few numbers of adjustments that were made in practice, as concluded by Sirbu (2012), and because the firms do not disclose all information that is necessary to make these adjustments, the previous studies varied in the degree of considering these adjustments, accordingly they revealed controversial results. Finally, this study recommends the use of EVA along with the traditional accounting measures because they are not substitutes for each other. Instead, EVA should be seen as an enhancement to the traditional accounting measures, which if used properly with them, will provide a more powerful tool to evaluate the performance. Sharma & Kumar (2012) asserted this when they indicated that the investors should use EVA along with the traditional accounting measures for decision making. International Journal of Business, Accounting, and Finance, Volume 13, Number 1 , Spring 2019 67 REFERENCES Abate, J. A., Grant, J. L., & Stewart, B. (2004). The EVA Style of Investing: Emphasizing the Fundamental of Wealth Creation. The Journal of Portfolio Management , 30 (4), 61-72.

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About the Author:

Ahmad N. Obaidat is Associate Professor of Accounting at Tafila Technical University, Jordan. Dr. Obaidat has twelve years teaching experience and his main research interests are in the areas of market related studies. Copyright ofInternational JournalofBusiness, Accounting, &Finance isthe property of International AcademyofBusiness &Public Administration Disciplines(IABPAD), LLCand its content maynotbecopied oremailed tomultiple sitesorposted toalistserv without the copyright holder'sexpresswrittenpermission. However,usersmayprint, download, oremail articles forindividual use.