4. Results and discussion of findings

#### 4.1 Future performance

Table 3 is the result of the multivariate analyses using the Jones Model and shows that the R&D is significant<sup>4</sup> , and follows the traditional relationship with

We also compute the non-discretionary accruals using the Modified Jones Model

Accounting and Finance - New Perspectives on Banking, Financial Statements and Reporting

where ΔRECt = net receivables in yeart less net receivables in yeart � 1 scaled by total assets at t – 1; NDAt = non-discretionary accruals scaled by total assets of prior year. Once we have calculated the discretionary accruals value for each firm in their MJDA and JDA forms, we then measure each firm's value relative to the sample median in percentage terms similar to the methodology adopted by past studies, refer to [18]. Consequently, a positive value refers to a firm who has greater discretionary accruals for that particular year relative to its peer group. The descriptive statistics of our overall data is shown in the following Table 2.

The core methodologies used for our research include the linear regression and logistic regression models. In our linear regression section investigating H1, we conduct OLS regressions for each base year measuring 3-month, 6-month, 1-year, 3-year, and 5-year performance as the dependant variable. In addressing H2,

Average 7.95 21.59 35.16 59.73 80.14 0.06 0.74 2.28 2.66 0.08 Median 7.06 11.53 20.84 33.86 37.94 0.05 0.55 1.69 2.65 0.01 Min �59.69 �100.00 �100.00 �100.00 �100.00 0.00 0.02 0.05 0.27 �4.21 Max 103.87 314.04 1358.18 1089.90 2880.31 0.84 11.01 27.98 5.47 9.07 Std. 20.44 48.84 85.65 148.61 231.81 0.07 0.79 2.21 0.86 0.49 10th per �16.59 �18.92 �34.44 �100.00 �100.00 0.01 0.23 0.43 1.57 �0.06 90th per 32.29 70.69 117.39 214.18 290.98 0.12 1.30 4.44 3.74 0.28 N 866 866 866 866 866 866 866 866 866 866

3m 6m 1y 3y 5y EP BM PS MktCap Salesg

EBITDA Failed\_6m Failed\_1y Failed \_3y Failed \_5y MJDA JDA R&D ETHICS

�0.05 0 0 0 0 �2.41 �2.39 0.02 5.20

0.59 0 0 1 1 3.26 3.10 0.18 5.50

N 866 866 866 866 866 866 866 866 866 The table shows the descriptive statistics of the data set we used. We show the average, median, minimum (min), maximum (max), standard deviation (Std.), 10th percentile (10th per), 90th percentile (90th per), and the total number of sample (N) for our overall data. Our overall data include 3m, 6m, 1y, 3y, 5y, EP, BM, PS, MktCap, Salesg, EBITDA, Failed\_6m, Failed\_1y, Failed\_3y, Failed\_5y, MJDA, JDA, R&D, and ETHICS from 2008 to 2010.

Average 1.16 0.01 0.04 0.15 0.26 0.43 0.39 0.10 5.36 Median 0.00 0 0 0 0 0 0 0.09 5.40 Min �29.32 0 0 0 0 �16.37 �15.71 0.00 5.20 Max 350.67 1 1 1 1 35.87 34.33 0.54 5.50 Std. 13.00 0.11 0.19 0.35 0.44 3.82 3.70 0.07 0.12

þ a2ðΔREVt � ΔRECtÞ þ a3ð Þ PPEt (3)

which is express as:

3.1 Research design

10th per

90th per

Table 2.

66

Descriptive statistics.

NDAt ¼ a<sup>1</sup>

1 At�<sup>1</sup> 

<sup>4</sup> In this paper, we mostly discuss the results that show significantly strong results (i.e., p-values ≤0.05). Weakly significant results (i.e., 0.05 < p-values <0.10) are sometimes aligned with the strongly significant results, but we do not actively discuss these.


#### Table 3. Correlation Table

both survivorship and future performance of tech-firms. Across two of the three years in the study, namely 2008 and 2009, the longer the returns are, the stronger the positive effects from BM, MktCap, MJDA, and R&D become. R&D acts a good predictor of future performance with significant coefficients of 155.73 in 6 months, 265 in 1 year and 335.09 in 3 years respectively in 2008 model. In the 2009 model,

The Roles of Accounting Valuations and Earnings Management in the Survivorship of Technology

Sales growth is negatively significant to the medium-term returns (1y) in 2010

increased growth in year-on-year sales did not necessarily enjoy corresponding positive returns in medium-term. This finding corroborates with past literature suggesting there is a significant association between three-day market returns and Internet firm revenue announcements [19]. This finding and the PS results shed valuable insights into the characterisation of tech stock returns in the crisis periods. Our discretionary accruals (MJDA) variable also exhibits significant linkage to the explanation of increased short- to medium-term returns from 2008. As shown in Table 3 the variable possesses positive coefficients of 1.23 and 4.25 in 2008s 6 month and 3-year outlook respectively which indicates a positive linkage to future returns. Therefore, discretionary accruals is a positive element for the returns which

As a whole, the accounting variables such as BM, MktCap, MJDA, and R&D have stronger positive effects on the longer-term performances in 2008 and 2009. In general, the large firm size (MktCap), undervaluation (EP and BM), more discretionary accruals and R&D are positive drivers for the returns of the technology firms. The negative effects from sales growth occur in 2010 sometime after the crisis. The overvaluation measured by PS seemed to positively affect the long-term

For future survivorship, Table 4 shows that the R&D variable plays a significant

practice of R&D expenditure in the technology sector and why firms who practice higher levels tend to experience positive future returns and a higher likelihood of

Furthermore, our findings suggest that firms with higher MktCap tend to survive and are more likely to outperform in the longer-term. With negative coefficients ranging from 2.17 and 0.48 in 2008, and 0.86 and 0.91 in 2010, the explanatory power for future failure is in line with the argument that undercapitalisation is a core reason to every technology business failure evaluated [20]. The R&D is significantly negative which highlights the importance of R&D expenditure in the technology sector as an investment rather than an asset. Support for this

advocated in reference to [21]. This implies that expenditure in the technology industry leads to improved efficiency, increased sales, and ultimately increasing

The level of discretionary accruals (MJDA) practiced by firms is also a good predictor of future failure in the medium- to long-term in 2008 and 2010. In predicting future failure in Table 4, the coefficients suggest that higher levels of discretionary accruals translate to greater likelihood of failure with positive coefficients of 0.18 in 2008; 0.36 and 0.27 respectively in 2010. Importantly, this conforms closely with our expectation that practising earnings management introduces

's 1-year outlook over the three crises years with negative coefficients

'truer measure of a company

–2010. This reveals key points about the

's pocket in the future

's value because this

' is also

…

16.35 (Table 3). This suggests that firms who reported

the R&D results remain significant at 56.41 and 286.02 respectively.

with a coefficient of

DOI: http://dx.doi.org/10.5772/intechopen.85395

amplifies with longer returns.

4.2 Future survivorship

95.25, and

expenditure figure in providing a

spending often turns out to be money in an investor

role in a firm

88.16,

survivorship.

company value.

69

of

returns but this effect fades out as time goes by.

64 across 2008

\*\*\*Significance

 at 1% level.
