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The impact of customer capital on company's market value: An empirical study from 100 U.S. stock market leaders


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Figure 1

Correlation matrix of Model 2. GW, goodwill; IAcust, intangible assets that characterize customer capital.
Correlation matrix of Model 2. GW, goodwill; IAcust, intangible assets that characterize customer capital.

Figure 2

Correlation matrix of Model 3. FinLev, financial leverage; GW, goodwill; IAcust, intangible assets that characterize customer capital; Int, intensity of research & development.
Correlation matrix of Model 3. FinLev, financial leverage; GW, goodwill; IAcust, intangible assets that characterize customer capital; Int, intensity of research & development.

The variants of regression models of the impact of customer capital on company's MV

Model 1 Model 2 Model 3

Dependent variable

MV

Independent variable Independent variables Independent variables
IAcust Intangible assets that characterize customer capital IAcust Intangible assets that characterize customer capital IAcust Intangible assets that characterize customer capital
IAother Other intangible assets IAother Other intangible assets
GW Goodwill GW Goodwill
RD Research and development costs RD Research and development costs
TA Total assets
Int Research and development intensity
FinLev Financial leverage

Examples of articles on the impact of customer capital on company's MV

Year of publication Author/Authors Findings/results

Regarding all intangible assets Regarding customer (relational, relationship) capital
2005 M.C. Chen, S.J. Cheng, and Y. Hwang The firms’ intellectual capital has a positive impact on MV and financial performance, and may be an indicator for future financial performance The object–advertising expenditure.The authors suggested that companies with greater advertising expenditure tend to have higher market-to-book value ratios, but according to the results of correlation analysis it was found that the coefficient on advertising expenditure is not significant
2005 C.-Y. Tseng and Y.-J.J. Goo The results generally support the hypothesis regarding the relationship between intellectual capital and corporate value The object–relationship capital.The findings of this study suggest that relationship capital directly influence corporate value
2013 M.B. Taghieh, S. Taghieh, and Z. Poorzamani It can be concluded that customer capital, which is considered as bridge or catalyst in intellectual capital activities, is the dominant and determining factor to change intellectual capital to the MV, accordingly, the company's business performance The object–relational capital.Based on the results of testing hypotheses, relational capital has significant and positive effect on firm value
2015 B. Bchini Based on the survey data in Tunisia, the authors find that the link between intellectual capital and value creation is linear and positive in manufacturing companies The object–relational capital.The results of these regressions are presented that the relationship between relational capital and value creation in the Tunisian manufacturing companies is statistically significant
2017 F. Sardo and Z. Serrasqueiro Concerning firms’ MV, the current study shows that human capital and structural capital have higher contribution to firm's MV. Therefore, human capital can be seen as the main driver of firms’ future growth and innovativeness The object–relational (or customer) capital.As a result of the regression analysis, it was found that the hypothesis that relational capital has a positive effect on firms’ MV was rejected
2018 I. Yilmaz and G. Acar Amongst the components of multiple factors model, the most influential explanatory variable was capital employed, then comes human capital, and relational capital. Structural capital has the lowest effect on explaining both company's value and performance The object–relational capital.The relational capital has positive and significant effect on M/B ratio

Summary statistics, using the observations 1–100 (Model 3)

Variable Mean Median Standard deviation Min Max
MV 1,40,107 92,998 1.65e+0.05 26,262 9,56,625
IAcust 3,481 432 7,537 0 45,358
IAother 8,461 1,367 20,395 0 1,38,005
GW 17,092 8,801 21,745 0 1,46,370
RD 2,480 915 3,858 0 21,419
TA (log) 10.95 10.93 0.96 8.55 13.18
Int 1.92 2.00 0.88 1.00 3.00
FinLev 14.53 1.69 85.12 −8.03 805.6

Summary statistics, using the observations 1–100 (Model 2)

Variable Mean Median Standard deviation Min Max
MV 1,40,107 92,998 1.65e + 0.05 26,262 9,56,625
IAcust 3,481 432 7,537 0 45,358
IAother 8,461 1,367 20,395 0 1,38,005
GW 17,092 8,801 21,745 0 1,46,370
RD 2,480 915 3,858 0 21,419

Correlation coefficients for independent variables of Model 3, using the observations 1–100

IAcust IAother GW RD TA Int FinLev Variables
1.0000 0.3239 0.6493 0.0127 0.3903 −0.0998 −0.0621 IAcust
1.0000 0.6346 −0.0696 0.4128 −0.0884 −0.0571 IAother
1.0000 0.0985 0.5850 0.0021 −0.0962 GW
1.0000 0.3290 0.4661 0.0176 RD
1.0000 −0.0794 −0.1267 TA
1.0000 −0.0585 Int
1.0000 FinLev

Coefficients of determination

R2 IAcust 0.45
IAother 0.45
GW 0.68
RD 0.40
TA 0.49
Int 0.31
FinLev 0.03

100 U.S. stock market leaders (the list was relevant as of January 10, 2020)

No Company No Company
1 3M Co. 51 Illinois Tool Works Inc.
2 Abbott Laboratories 52 Intel Corp.
3 AbbVie Inc. 53 International Business Machines Corp.
4 Accenture PLC 54 Intuit Inc.
5 Adobe Inc. 55 Intuitive Surgical Inc.
6 Allergan PLC 56 Johnson & Johnson
7 Alphabet Inc. 57 Kimberly-Clark Corp.
8 Altria Group Inc. 58 Kinder Morgan Inc.
9 Amazon.com Inc. 59 Kraft Heinz Co.
10 Amgen Inc. 60 Linde plc
11 Apple Inc. 61 Lockheed Martin Corp.
12 Applied Materials Inc. 62 Lowe's Cos. Inc.
13 AT&T Inc. 63 Marriott International Inc.
14 Automatic Data Processing Inc. 64 McDonald's Corp.
15 Becton, Dickinson & Co. 65 Medtronic PLC
16 Biogen Inc. 66 Merck & Co. Inc.
17 Boeing Co. 67 Microsoft Corp.
18 Booking Holdings Inc. 68 Mondelēz International Inc.
19 Boston Scientific Corp. 69 Netflix Inc.
20 Bristol-Myers Squibb Co. 70 Nike Inc.
21 Broadcom Inc. 71 Northrop Grumman Corp.
22 Caterpillar Inc. 72 NVIDIA Corp.
23 Charter Communications Inc. 73 Occidental Petroleum Corp.
24 Chevron Corp. 74 Oracle Corp.
25 Cisco Systems Inc. 75 PepsiCo Inc.
26 Coca-Cola Co. 76 Pfizer Inc.
27 Colgate-Palmolive Co. 77 Philip Morris International Inc.
28 Comcast Corp. 78 Phillips 66
29 ConocoPhillips 79 Procter & Gamble Co.
30 Costco Wholesale Corp. 80 Qualcomm Inc.
31 CSX Corp. 81 Raytheon Co.
32 CVS Health Corp. 82 Regeneron Pharmaceuticals Inc.
33 Danaher Corp. 83 salesforce.com Inc.
34 Delta Air Lines Inc. 84 Schlumberger Ltd.
35 DuPont de Nemours Inc. 85 Starbucks Corp.
36 Eli Lilly & Co. 86 Stryker Corp.
37 Emerson Electric Co. 87 Target Corp.
38 EOG Resources Inc. 88 Texas Instruments Inc.
39 Estée Lauder Cos. Inc. 89 Thermo Fisher Scientific Inc.
40 Exxon Mobil Corp. 90 TJX Cos. Inc.
41 Facebook Inc. 91 T-Mobile US Inc.
42 FedEx Corp. 92 Union Pacific Corp.
43 Ford Motor Co. 93 United Parcel Service Inc.
44 General Dynamics Corp. 94 United Technologies Corp.
45 General Electric Co. 95 UnitedHealth Group Inc.
46 General Mills Inc. 96 Verizon Communications Inc.
47 General Motors Co. 97 Walgreens Boots Alliance Inc.
48 Gilead Sciences Inc. 98 Walmart Inc.
49 Home Depot Inc. 99 Walt Disney Co.
50 Honeywell International Inc. 100 Zoetis Inc.

Correlation coefficients for independent variables of Model 2 using the observations 1–100

IAcust IAother GW RD Variables
1.0000 0.3239 0.6493 0.0127 IAcust
1.0000 0.6346 −0.0696 IAother
1.0000 0.0985 GW
1.0000 RD