Intangible Values In Financial Accounting And Reporting An Analysis From The Perspective Of Financial Analysts.pdf

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Intangible Values in Financial Accounting and Reporting An Analysis from the Perspective of Financial Analysts DISSERTATION of the University of St Gallen, School of Management, Economics, Law, Social Sciences and International Affairs to obtain the title of Doctor of Philosophy in Management submitted by Stephan Grüber from Germany Approved on the application of Prof Dr Peter Leibfried and Prof Dr Dirk Schäfer Dissertation no 4274 Springer Gabler, Wiesbaden 2014 The University of St Gallen, School of Management, Economics, Law, Social Sciences and International Affairs hereby consents to the printing of the present dissertation, without hereby expressing any opinion on the views herein expressed St Gallen, May 19, 2014 The President: Prof Dr Thomas Bieger Intangible Values in Financial Accounting and Reporting Stephan Grüber Intangible Values in Financial Accounting and Reporting An Analysis from the Perspective of Financial Analysts With a Foreword by Prof Dr Peter Leibfried Stephan Grüber St Gallen, Switzerland Dissertation, University of St Gallen, Switzerland ISBN 978-3-658-06549-2 DOI 10.1007/978-3-658-06550-8 ISBN 978-3-658-06550-8 (eBook) The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.d-nb.de Library of Congress Control Number: 2014944657 Springer Gabler © Springer Fachmedien Wiesbaden 2015 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer Permissions for use may be obtained through RightsLink at the Copyright Clearance Center Violations are liable to prosecution under the respective Copyright Law The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made The publisher makes no warranty, express or implied, with respect to the material contained herein Printed on acid-free paper Springer Gabler is a brand of Springer DE Springer DE is part of Springer Science+Business Media www.springer-gabler.de Foreword V FOREWORD Even though intangible values have continuously become significant value drivers of companies in today’s economy, financial accounting and reporting still lacks to properly incorporate and to report such values Despite the ongoing debate throughout the past decades, a universal solution inside or outside of the traditional information means has not yet been developed As a consequence, financial accounting and reporting still provides an incomplete picture of an entity’s true resources and claims While it is necessary to acknowledge that financial accounting and reporting has inherent limitations and is not supposed to present absolute data, further analysis is required to better understand and to potentially close the information gap In this thesis, Stephan Grüber focuses on the information use of financial analysts, one of the primary users of IFRSs He investigates how financial analysts utilize and incorporate information on intangible values in their decision-making processes and whether such information influences decisions In addition, the study examines the preferences of financial analysts in regard to accounting for and reporting intangibles in the future Upon outlining the fundamentals of financial accounting and reporting, Stephan examines the foundations and challenges of intangible values and provides an overview of concepts introduced to improve the accounting and reporting of intangibles As a next step, he distinguishes various groups of financial analysts and their decision-making objectives, such as buy- and sell-side analysts and equity and fixed income analysts Chapter represents the main body of this thesis, presenting and discussing two empirical studies The first part describes the results of a content analysis of sell-side research reports, offering insights into the information use of sellside analysts The second part analyzes the results of a web-based experimental survey with over 1,100 financial analysts, focusing on the importance of information of intangibles for their decision-making The present analysis offers detailed and comprehensive evidence on the actual information use and preferences of financial analysts, contributing to an improved understanding of the user perspective in financial accounting and reporting, i.e what users effectively require with respect to information on intangible values Hence, this thesis may not only be valuable to individuals in academia, but is also useful for VI Foreword practitioners and executives focusing on corporate communication In addition, the results may further provide financial analysts with stimulating self-insight regarding their decision-making I therefore wish this thesis to be widely read and accepted by a broad audience St Gallen, June 2014 Prof Dr Peter Leibfried, CPA, MBA Managing Director of the Institute of Accounting, Control and Auditing (ACA-HSG) at the University of St.Gallen and doctoral advisor of Stephan Grüber Acknowledgements VII ACKNOWLEDGEMENTS The present thesis is the result of my Ph.D studies at the University of St Gallen (HSG) in Switzerland It was submitted and approved to obtain the title Doctor of Philosophy in Management Throughout the course of my studies, there has been much support from many different people and I would like to take this opportunity to thank all of them First and foremost, I am particularly indebted to my doctoral advisor, Prof Dr Peter Leibfried, who made this research possible, continuously providing me with guidance and encouragement over many years His insights and advice significantly helped me to complete this work I would further like to express my sincere gratitude to Prof Dr Dirk Schäfer, who served as co-advisor and supported this project with valuable thoughts and ideas I have written this thesis while being a full-time employee at KPMG LLP in New York In order to participate in the Ph.D program in St Gallen and to draft my thesis I was granted several study leaves I would therefore like to express my genuine thanks to Dr Norbert Fischer and Jan Storbeck for their trust and flexibility Moreover, I also thank Ingo Zielhoff, who supported me during the final phase of this project I would also like to specifically thank Dr Torsten Jaskolski for discussing and exchanging our ideas throughout the years Special thanks go to Nicholas Jungovic for supporting me and reading the draft of this thesis In addition, I further extend my thanks to my family and friends, who have always been there for me despite my limited time My deepest gratitude goes to my love Sophie for her unbounded patience, understanding and sacrifices along the way, as well as for her motivating and encouraging words during difficult times Last but not least, I would also like to extend my appreciation and thanks to my parents for their love and unconditional support This thesis is dedicated to them – it would not have been possible without them Zurich, June 2014 Stephan Grüber 218 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles the sample in half and is more robust to outliers, only amounted to 30 years Thus, there seemed to be potential outliers in the upper and lower parts of the sample, which was supported on the one hand by the relatively high maximum of 342 years.1139 On the other hand, the standard deviation ( ) was considerably high with 56.7 years In addition, several companies were also very young with a firm age of one year in the publication year of the respective report Table 6: Additional Firm Characteristics of Sample N Mean Median SE SD Min Max 55.1353 30.0000 3.9399 56.6859 1.0000 342.0000 Market Cap (in millions) 207 3439.1604 393.1880 640.8482 9220.1998 6.8391 55225.9779 Market-to-Book-Value 207 1.5302 22.0157 0.3184 315.0497 Total Assets (in millions) 207 8231.7739 340.6120 2053.5109 29544.8774 Return on Assets (ROA) 207 Maturity 207 4.0614 0.0610 1.7992 0.0667 0.0096 4.3447 234676.0004 0.1376 -0.7002 0.7881 The market capitalization was computed by multiplying the closing stock price of the year ending before the publication year of the report with the common shares outstanding at that time As Table depicts, the average market capitalization of the sampled companies amounted to approximately 3,439 million (Euro), whereas the median was only 393 million With approximately 9,220 million, the standard deviation was again relatively high, suggesting a high dispersion across the sample Accordingly, the maximum amounted to 55,225 million and the lowest was 6.8 million.1140 Moreover, the market-to-book-value was defined as the market capitalization divided by the book value of common equity Its arithmetic mean amounted to approximately 4.1, indicating that on average, the market capitalization of the companies in this sample was four times greater than the respective book value Again, the median was lower, amounting to only 1.8 The high market-to-book-value was attached to a company in the Software sector; the second largest value only amounted to approximately 46.41 Interestingly, the lowest market-to-book value belonged to a company in the Technology sector In addition to the market capitalization, firm size may also be measured by a company’s total assets In line with the other characteristics, the arithmetic mean of 1139 1140 The maximum related to Merck KGaA, which had its origins as early as 1668 The maximum and minimum pertained to Siemens AG and Intica Systems AG, respectively Content-Analysis of Sell-Side Research Reports 219 total assets was relatively high; whereas the median was substantially lower (see Table 6) Some companies with the highest total assets included Deutsche Post, Daimler and Volkswagen The return on assets (ROA) was used as a measure of profitability and was calculated as net income divided by the company’s total assets of the year ending before the publication year of the respective research report As shown, the values for the arithmetic mean and median of this ratio were relatively close to each other, with 0.061 (or 6.1 percent) and 0.0667 (or 6.7 percent) Still, the standard deviation was relatively high with 0.1376 (or 13.76 percent) Moreover, some companies also showed negative profitability 5.2.7.2 Preferred Valuation Methods As discussed, the valuation methods are one of the key determinants of the decisionmaking processes of financial analysts Thus, they were also studied as part of the content analysis This section provides the descriptive results of the analysis related to the preferred valuation methods According to the previous discussion, sell-side research reports typically include a separate section that discusses the valuation of a company Based on this analysis, the analysts usually define a target price, which is also included in the research report and is an integral part of the overall recommendation While analysts were expected to employ different valuation methods, they were further assumed to have a preferred method To identify the preferred methods in the research reports of this study, the following approach was employed: (1) in general, analysts explicitly stated their preference in the report, i.e in the valuation section; (2) if such statement was not available, it was assumed that analysts preferred the method that they used to compute the target price; (3) in a total of 24 cases, however, it was not clear, which method was favored by the analysts and thus, all methods were counted as their preferred valuation methods Figure 23 illustrates that a DCF-based method was the most preferred valuation method analysts employ to value a company and to eventually determine its target price and to provide a recommendation to buy, hold or to sell the respective stocks On 220 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles one hand, this finding supports the assumption that the DCF method is one of the most widely used valuation methods among academics and practitioners.1141 Figure 23: Preferred Valuation Methods (Content Analysis) (Source: Own Illustration) In addition, it is consistent with some of the empirical findings from prior studies that the DCF has become one of the most favored valuation methods for financial analysts.1142 However, the DCF was not expected to be as dominant, since other studies also showed that other methods existed that were at least equally important, such as the price-to-earnings ratio.1143 Yet, the DCF model is still the most accurate and flexible method to value companies;1144 and thus, it might be compelling to analysts to employ a DCF, in particular when they start to cover a company The second most preferred valuation methods were enterprise value (EV)-based multiples As opposed to the equity value that represents the portion attributable to the shareholders, the EV measures the entire market value of a company,1145 and thus, also includes the market value of debt.1146 Moreover, EV ratios are independent of the 1141 1142 1143 1144 1145 1146 Cf KOLLER, T./GOEDHART, M./WESSELS, D (2010), p 103 Academics, in particular argue that a multi-period valuation model is superior than a valuation based on single-period comparatives (DEMIRAKOS, E G./STRONG, N C./WALKER, M (2004), p 222) Cf IMAM, S./BARKER, R./CLUBB, C (2008), p 503 et seqq Cf ARNOLD, J./MOIZER, P (1984), p 195; BARKER, R G (1999), p 197 with additional references Cf KOLLER, T./GOEDHART, M./WESSELS, D (2010), p 313 Cf KOLLER, T./GOEDHART, M./WESSELS, D (2010), p 273 Cf PENMAN, S H (2010), p 11 More specifically EV is typically computed as the market capitalization plus market value of preferred stock plus the market value of debt minus cash/cash equivalents and shortterm investments (cf ROSENBAUM, J./PEARL, J (2009), p 32; PINTO, J E ET AL (2010), p 322; NAGORNIAK, J J./WILCOX, S E (2012), p 297) Content-Analysis of Sell-Side Research Reports 221 capital structure of a company and other factors, such as differences in tax regulation or certain accounting policies.1147 The main EV ratios included in the reports were EV/EBIT, EV/EBITDA as well as EV/Sales Interestingly, price-based multiples were only included in 29 reports as the most preferred valuation method The main ratio was the price-to-earnings ratio, which is one of the most widely used valuation measures.1148 As the name suggests, the price-to-earnings-ratio expresses the relationship between the share price and the earnings of a company 1149 Moreover, analysts also used an average of various methods or the so-called sum-ofthe-parts method in order to determine a target price and to provide a buy, hold or sell recommendation With respect to the average method, analysts employed more than one valuation method to compute several values or prices for a company and then calculated their arithmetic mean as the final target price The valuation methods used for the average method did not vary from the ones already mentioned In regard to the sum-of-the-parts method, the analysts value a company’s business segments or units separately and then derive a total value based on the individual valuations This method may be appropriate for companies that operate in various areas that are too different from each other to use one overall method For instance, Siemens in this sample was valued as an average of the sum-of the-parts method and a DCF approach The valuation methods in the category Other were not used as often as the ones mentioned before They included methods based on the free cash flow yield and the dividend yield as well as the return of equity or net asset values 5.2.7.3 Results for the Total Sample This section discusses the findings for the total sample First, the following paragraphs present the results for the (total) Intangible Score and for the scores of the respective sub-categories The subsequent sections provide an overview of the frequency distributions of the intangible themes that were included in each of the different subcategories 1147 1148 1149 Cf ROSENBAUM, J./PEARL, J (2009), p 11 Also refer to PINTO, J E ET AL (2010), p 320 et seq for additional rationales for using EV/EBITDA Cf KOLLER, T./GOEDHART, M./WESSELS, D (2010), p 317; ROSENBAUM, J./PEARL, J (2009), pp 11 and 44; NAGORNIAK, J J./WILCOX, S E (2012), p 288 Cf PENMAN, S H (2010), p 49 222 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles As shown in Table 7, the arithmetic mean of all Intangible Scores amounted to 23.41 That means, on average 23.41 percent of the information items were included in the respective reports, which was higher than the total scores in other studies.1150 Accordingly, on average about 12.40 information items of all intangible themes were included in an analyst report The median was even slightly higher, amounting to 24.53 One of the possible reasons might be that sell-side analysts use more information on intangible values in their initiating coverage reports than in their follow-up (or results) reports.1151 As discussed earlier, initiating coverage reports typically include an in-depth analysis of the respective company and its industry.1152 Also, analysts might try to use information on intangible values to support their recommendation.1153 The lowest Intangible Score found for the reports amounted to 3.77; the maximum score was 41.51 Therefore, all research reports of this sample included at least some information on intangible values However, no report included more than 22 items Table 7: Overview of Mean Scores (Total Sample) N Mean Median SE SD Min Max Total Intangible Score 207 23.41 24.53 54383 7.82431 3.77 41.51 Human Capital 207 15.06 18.18 81491 11.72457 0.00 54.55 Internal Capital 207 27.11 26.92 75783 10.90334 0.00 53.85 External Capital 207 23.13 25.00 61092 8.78968 6.25 50.00 Internal Capital Strategy 207 40.58 40.00 1.43599 20.66027 0.00 80.00 Organizational Capital 207 36.81 40.00 1.14286 16.44285 0.00 70.00 Innovation Capital 207 12.17 9.09 1.01382 14.58633 0.00 63.64 External Capital Customer Capital 207 26.09 22.22 91465 13.15952 0.00 66.67 Supplier Capital 207 6.44 0.00 1.04949 15.09954 0.00 66.67 Investor Capital 207 28.99 25.00 68205 0.00 75.00 9.81305 Table also provides an overview of the sub-categories for the two levels below the Intangible Score As presented, the value of the Intangible Score was especially driven 1150 1151 1152 1153 For instance, refer to ARVIDSSON, S (2003), p 152; GARCIA-MECA, E (2005), p 431; FLÖSTRAND, P./STRÖM, N (2006), p 586; GARCIA-MECA, E./MARTINEZ, I (2007), p 69 Cf ABHAYAWANSA, S A (2010), p 169 Cf Section 5.2.5.1 Cf Section 5.2.3 Content-Analysis of Sell-Side Research Reports 223 by the Internal Capital category, which had the highest score of the first-level categories with an arithmetic mean of 27.11 The score for Human Capital amounted to only 15.06 and the External Capital category had a score of 23.13, which was relatively close to the arithmetic mean of the Intangible Scores While all research reports contained at least one information item in regard to the External Capital category, in some instances, they did not include any items for the other two categories, i.e Human Capital and Internal Capital Hence, their minimum scores amounted to Yet, the range of the scores in these two categories was higher, with maximum scores of 54.55 and 53.85 for Human Capital and Internal Capital, respectively Accordingly, their standard deviations were also higher than for the External Capital category (see Table 7) As discussed, the Internal Capital and External Capital category could also be divided into the more detailed sub-categories Strategy, Organizational and Innovational Capital as well into Customer, Supplier and Investor Capital.1154 The Human Capital category was not further distinguished In order to obtain a better overview of the differences, Figure 24 illustrates the mean scores for these sub-categories in addition to the overview in Table Accordingly, the results show that the relatively high score in the Internal Capital category was particularly due to high scores in the Strategy and Organizational Capital sub-categories with arithmetic means of 40.58 and 36.81, whereas the mean of the Innovation Capital category only amounted 12.17 In fact, Strategy had the highest value across all sub-categories on the second level, including Human Capital This finding is consistent with results from studies conducted in Spain, where GARCIA-MECA/MARTINEZ and GARCIA-MECA showed in two separate studies that Strategy was the category that most frequently occurred in sell-side research reports.1155 Especially GARCIA-MECA found that each analyst report contained at least one information item that related to the Strategy category.1156 Thus, this category appears to be particularly important to sell-side analysts Nevertheless, some of the reports in this sample did not include any of the pre-defined items related to Strategy 1154 1155 1156 Cf Section 5.2.5.3 Cf GARCIA-MECA, E (2005), p 432; GARCIA-MECA, E./MARTINEZ, I (2007), p 69 Cf GARCIA-MECA, E (2005), p 432 224 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles However, this applied to all of the sub-categories, expressed by their respective minimums of (see Table 7) Also, prior studies showed that information on Human Capital was fairly underrepresented in sell-side research reports.1157 In this category, only certain items occurred rather frequently and thus, were assumed to be important to sell-side analysts That is why the relatively low score of 15.06 in this study was not surprising However, Organizational Capital was comparatively high, as opposed to the results of other studies.1158 Figure 24: Mean Occurrences of Sub-Category Scores (Total Sample) (Source: Own Illustration) Table and Figure 24 further show that the remaining scores amounted to 28.99 and 26.09 for Investor (InvC) and Customer Capital (CC), respectively The lowest score was attached to Supplier Capital (SC) with only 6.44, i.e on average only 6.44 percent of the information items of this category were included in the research reports Thus, information on supplier-related topics appeared to be as the least important to analysts, in particular when compared to the other External Capital categories, Customer (CC) and Investor Capital (InvC) As such, sell-side analysts seemed to be more concerned with the market side of a company as well as with its capital providers In regard to the maximum scores of the more detailed sub-categories, the highest value was again attached to the Strategy category (STRAT) That is, in some instances sell1157 1158 Cf Sections 5.2.3 and 5.2.4 Also refer to GARCIA-MECA, E./MARTINEZ, I (2007), p 69; FLÖSTRAND, P (2006), p 469 For instance, cf ARVIDSSON, S (2003), p 152 Content-Analysis of Sell-Side Research Reports 225 side reports included up to 80 percent of the pre-defined information items related to Strategy Yet, the maximum scores for all other sub-categories were also comparatively high with values ranging from 63.64 to 75.0 (see Table 7) In addition, all standard deviations in the sub-categories seemed to be rather high, indicating a high variation of the occurrences of information items within a subcategory This means, the reports most likely contained either a fairly high or low number of information items related to a sub-category This would support the assumption that analysts placed varying emphases on the sub-categories across their reports The next sections describe the results in more detail, presenting the overall frequencies of the individual information items or intangible themes within each of the different sub-categories The analysis begins with Human Capital, followed by the Internal Capital and External Capital categories 5.2.7.3.1 Human Capital Information Items The score for the Human Capital category included a total of eleven information items or intangible themes As presented in the last section, on average approximately 15 percent of these pre-defined information items were included in the research reports Table lists the absolute and relative frequencies, whereas the latter was calculated as the actual overall occurrence of an information item divided by the possible occurrence, i.e 207 reports With 118 occurrences or 57 percent, Employee Structure was most frequently mentioned in the analyst reports, followed by Management Experience & Quality (108 occurrences or 52.17 percent) The third most frequent item was Employee Efficiency & Productivity Yet, the information items only had a total of 47 occurrences (22.71 percent) Statements related to Career Opportunities were not included at all in the sample The information item Employee Structure particularly included references related to the number of employees and changes in employees as well as additional statements or overviews of the employee structure, such as a breakdown of employees by age, business units and the like The description of changes in the employee structure could also include changes in the management team or in the lower-level management 226 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles Table 8: Total Frequencies of Human Capital Themes Human Capital Information Items N Management Experience & Quality 207 Frequency 108 Percent 52.17 Employees Experience & Quality 207 3.86 Employee Structure 207 118 57.00 Value Added per Employee 207 0.48 Employee Efficiency & Productivity 207 47 22.71 Education and Training of Employees 207 1.93 Remuneration System 207 26 12.56 Pensions Plans & Benefits 207 14 6.76 Career Opportunities 207 0.00 Recruitment Policy & Strategy 207 3.86 Dependence on Key Personnel 207 4.35 In general, the analysts limited their statements to information on the employee numbers and their changes, which were typically rather brief For instance, after discussing personnel expenses as the main fixed cost position for Wirecard AG, the analysts further specified that “personnel had risen to 410, an increase of 49 (14%) from the end of 4Q06.”1159 In addition, the analysts explicated that they would expect Wirecard AG to further increase its headcount at a similar rate, even though the growth in per-employee costs should slow down With regard to Cancom AG, for example, the analysts stated that in a recent acquisition “Cancom [sic] dismissed 10 employees in admin”1160, which resulted in lower personnel costs for the company Thus, in both cases, the description of the changes in employees was directly connected to an assessment of the impact on the financial situation of the covered companies, i.e the impact on personnel expenses or on synergy effects and savings Although the majority of analysts usually linked employee changes to financial data, some analysts also described such fluctuations with a more qualitative approach, focusing on how companies handle their workforce Upon discussing a significant decrease of the staff at Südzucker AG, the covering analysts commented that the “reduction at the Sugar division was accomplished in a socially acceptable manner Tải FULL (564 trang): https://bit.ly/3C6g0IZ 1159 1160 MORGAN STANLEY (2007), p 17 HAUCK & AUFHÄUSER (2010), p 10 Content-Analysis of Sell-Side Research Reports 227 (e.g group-internal reassignment of employees from the Sugar division).”1161 Hence, the analysts might have seen the importance of how a company deals with difficult issues, especially in regard to the workforce or human capital Such statement may serve as an indicator of how a company approaches other similar issues in the future and thus, might be important to capital providers However, some analyst reports also included more information about the employee structure This appeared to especially apply to cases where the employee structure was relatively heterogeneous, e.g the employees possessed significantly different qualifications Two examples would be the analyst reports covering MeVis Medical Solutions AG (MeVis) and Rhön Klinikum AG (Rhön) which operate in the software and healthcare sectors, respectively In both reports, analysts used pie charts in addition to written statements in order to describe the employee structure based on the employees’ educational qualifications and on personnel categories.1162 In general, the two reports were examples that seemed to analyze the information items related to the Human Capital category in more depth, which was supported by relatively high scores in this category, amounting to approximately 45.45 and 36.36 for MeVis and Rhön.1163 The analysts for MeVis, for instance, referred to the company’s highly qualified workforce, stating that the team “has an international focus with a strong academic and commercial network and enjoys a high degree of reputation among experts MeVis supports close cooperation with globally leading radiologists and surgeons for the transfer of knowledge from clinical practice [ ] The personal identification with the MeVis Group is high, which is reflected in the very low fluctuation rate This is a competitive advantage critical for success in highly dynamic markets.”1164 The analysts further pointed out that the personnel was multidisciplinary with a substantial academic share The entire statement was counted as Employees Experience & Quality, which could contain references about experience, education and skills Information about the quality of the workforce appears to be important to 1161 1162 1163 1164 CHEUVREUX (2009), p 24 Cf MM WARBURG/SES RESEARCH (2008), p 10; RBS (2010), pp 24-25 Note that the average score (arithmetic mean) in the Human Capital category amounted to only 15.06 MM WARBURG/SES RESEARCH (2008), p 10 228 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles investors, in particular in industries that require highly qualified employees While the quality and experience of the workforce are not directly linked to the (financial) success of a company, they are at least part of its basis, as qualified and experienced personnel may be better able to implement management’s strategy Potential weaknesses might lead to significant issues in the future Thus, experience and quality are important characteristics that financial analysts consider in their research reports The analyst team for Rhön particularly referred to the company’s remuneration system, commenting that the company negotiates its wage contracts on a house-byhouse basis and that its employees are incentivized by a bonus system on net income growth Based on Rhön’s perceptions, the analysts assessed that overall “its total compensation packages are above market average.”1165 The analysts further highlighted the professional training capacities at the company by providing a breakdown of the number of trainees by job category The two statements were classified as Remuneration System and Education and Training of Employees, respectively The former information item included a description of the companies’ compensation system and potential incentive programs On the one hand, such information may indicate whether companies are able to pay competitive salaries and to attract and retain talent On the other hand, it might point to potential issues In either case, the information characterizes the human capital of companies and thus, appears to be relevant to investors Again, Education and Training of Employees may indirectly inform investors about the quality and potential of the company’s human capital In general, this information item included references related to the education and training policies and its quality In addition, it also contained ratios, such as training expenses divided by the number of employees The Human Capital category appeared to be especially important in the case of healthcare providers, as Rhön’s immediate competitor, Marseille-Kliniken, also had a relatively high score in this category, amounting to 54.55 The second most frequently mentioned information item, Management Experience & Quality, covered information in regard to the management’s overall experience or within a particular industry, education of the individuals as well as other comments about the ability, quality and credibility of the management team The reports typically 1165 RBS (2010), p 24 Content-Analysis of Sell-Side Research Reports 229 included a brief paragraph about the education of the respective management team; a detailed discussion was rare In some instances, pie charts were employed to illustrate the management board structure For example, the research report for Krones AG, a company in the industrials sector, included a rather detailed analysis: “Krones´ management team consists of five members All of them have spent considerable time with the company and have held different positions in the past Thus, we believe the company has a very experienced management.”1166 The analysts continued to describe the experience and education of each of the board members, highlighting the number of years with the company and their academic degrees in engineering, business administration, and commercial informatics In contrast, the analysts for Fresenius Medical Care AG only provided brief statements in regard to the company’s C-levels, the CEO and CFO Accordingly, the former “has more than 40 years experience in the field of dialysis”1167 and the latter “held senior positions at Polaroid corporation and was an audit partner”1168 with a Big4 accounting firm Moreover, the analysts for ThyssenKrupp AG assessed that the company “will need to find a worthy replacement”1169, as two individuals stepped down as members of the company’s management board As mentioned, prior studies found that analysts considered information about a company’s management as relatively important.1170 That is because they are the key people, who specify the business model and the strategy of the respective company and have to respond to current and upcoming issues While an excellent education or past track record is not a guarantee for future (financial) success, such information and the analysts’ assessments still indicate the potential of a management team By providing such information, investors may be better equipped to evaluate a company’s current and future position In particular, investors might be reluctant to invest in a company with a management that is considered to be average or even below Yet, entirely negative statements about management were not be identified for this sample A potential reason could be that sell-side analysts depend to some degree on 1166 1167 1168 1169 1170 DEUTSCHE BANK (2007a), p 20 JEFFERIES INTERNATIONAL (2010a), p JEFFERIES INTERNATIONAL (2010a), p ING (2010a), p 16 Cf Section 5.2.3 230 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles management teams as information source and thus, the respective comments are positively biased.1171 Nevertheless, analysts cannot afford to publish information, which is in complete contradiction to reality and therefore, the absence of negative statements should signal investors that the management team is at least average within the industry The differences in the level of detail that was used to describe this information item cannot be resolved at this point; reasons might lie in firm size, industry or the characteristics of the covering banks The third most frequently mentioned information item, Employee Efficiency & Productivity, contained references related to the efficiency and productivity of employees, which could be qualitative statements or ratios, such as net income (or EBIT and EBITDA) divided by the number of employees, sales by employee or employee expenses by the number of employees Hence, this information item describes the relationship between a company’s workforce and its financial performance By comparing the ratios within the company’s industry or across time, the investors may be able to determine the company’s relative performance and to assess how well or how efficient the company employs its human capital to transform its assumed quality into financial performance In addition, such ratios may indicate how expensive the human capital is for companies While most reports included the information as part of a table, some analysts further commented on the ratios In the case of Altana AG, for instance, the analysts characterized a business segment as having “an EBITDA/employee figure of >EUR100,000 that ranks among the top in the chemical industry”1172 For burgbad AG, the analyst report included: “Sales per employee have risen continuously from €102,000 in FY 2000 to €118,000 at present We regard higher productivity as evidence of burgbad’s restructuring success.”1173 As mentioned, the analysts compared the ratios with industry standards and across time to identify trends In some instances, analysts would also employ graphs and charts to illustrate ratios The report on itelligence AG, for example, included a bar 1171 1172 1173 For empirical evidence in regard to the information sources of financial analysts, refer to Section 5.3.5.2 HSBC (2007), p WEST LB (2006), p 10 Content-Analysis of Sell-Side Research Reports 231 chart that compared the company’s sales per employee with five other companies in the industry for a particular year.1174 However, such illustrations were relatively rare among the reports The other information items related to the Human Capital category did not occur as often, as depicted by Table An example would be Dependence on Key Personnel, which was only included in a total of nine reports (4.35 percent) The information item included references to key employees other than the general management teams Such information might especially be important when investing in a less mature start-up or in companies that rely on the creative capacity or on the research capabilities of individuals For example, in the case of adidas AG, the sell-side report published by Credit Suisse in 2006 stated: Tải FULL (564 trang): https://bit.ly/3C6g0IZ “On March 2006 adidas announced the departure of design chief Michael Michalsky to pursue other business interests […] adidas has reacted promptly by appointing Hermann Deininger, a 20-year adidas veteran, as new head designer with additional marketing responsibilities Michalsky had been the key creative head at adidas since 2003 and had played an important role in the adidas brand success, in particular in lifestyle designs.”1175 The paragraph continued with an assessment that the departure would not have a lasting negative impact for the group Yet, the analysts believed that it was necessary to comment on the departure of such key personnel Accordingly, the entire paragraph was considered as an information item and counted with 1.1176 5.2.7.3.2 Internal Capital Information Items As discussed, the score of the Internal Capital category had the highest arithmetic mean among the three main categories, amounting to 26.67 The information items or intangible themes of this category were further distinguished into three more detailed sub-categories, i.e Strategy, Organizational Capital and Innovation Capital The high score for the Internal Capital category was mainly driven by the scores for Strategy and Organizational Capital with arithmetic means amounting to 40.48 and 36.71, 1174 1175 1176 Cf MORGAN STANLEY (2006), p 13 CREDIT SUISSE (2006), p 23 Note that in this particular case, the paragraph was further counted as a description of the changes in employees 232 Empirical Analyses of the Perspective of Financial Analysts on Information about Intangibles respectively; Innovation Capital played a rather minor role, with an average score of 11.67.1177 Consistent with the prior section, Table lists the frequencies of the individual information items (intangible themes) within each of the more detailed sub-categories As discussed earlier, the sub-category Strategy included five items, Organizational Capital ten items and Innovation Capital was comprised of eleven information items Table 9: Total Frequencies of Internal Capital Themes Internal Capital Information Items Strategy Business Model Frequency Percent 207 139 67.15 Objectives & Consistency of Strategy 207 118 57.00 Social Responsibility 207 0.97 Strategic Alliances 207 88 42.51 M&A Activity 207 73 35.27 Organizational Capital Operational Efficiency 207 108 52.17 Installed Capacity 207 51 24.64 Current IT Systems 207 13 6.28 Current Infrastructure 207 131 63.29 Quality of Major Business Processes 207 91 43.96 Communication within the Firm 207 0.48 Working Environment 207 1.93 Organizational Structure 207 134 64.73 Investments in Recent Infrastructure 207 55 26.57 Portfolio of Products & Services 207 174 84.06 11.11 Innovation Capital Patents and Licenses 1177 N 207 23 Patents Pending 207 1.93 Objectives of Innovation and R&D 207 58 28.02 Basic Research 207 16 7.73 Product Design & Development 207 30 14.49 Future Projects 207 0.97 R&D Employee Structure 207 22 10.63 R&D Productivity & Efficiency 207 72 34.78 Sales from New Products 207 3.38 New Products in Pipeline 207 42 20.29 Age of Product Portfolio 207 0.48 Cf Table in the prior section 4046852 ... preferences of financial analysts in regard to accounting for and reporting intangibles in the future Upon outlining the fundamentals of financial accounting and reporting, Stephan examines the foundations... provides an overview of the foundations and challenges of 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