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Review Re view of Account Ac count ing and Finance Finance Customer value disclosure and cost of equity capital Raf Orens Walter Aerts Nadine Lybaert

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To cite this th is document: Raf Orens Walter Aerts Nadine Lybaert, (2013),"Customer value disclosure and cost of equity capital", Review of Accounting and Finance, Vol. 12 Iss 2 pp. 130 - 147 Permanent link to this document: http://dx.doi.org/10.1108/14757701311327696

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Users Use rs who downloaded this article a also lso downloaded: Zaini Embong, Norman Mohd-Saleh, Mohamat Sabri Hassan, (2012),"Firm size, disclosure and cost of equity capital", Asian Review of Accounting, Vol. 20 Iss 2 pp. 119-139 http:// dx.doi.org/10.1108/13217341211242178 Henry Huang, Quanxi Wang, Xiaonong Zhang, (2009),"The effect of CEO ownership and shareholder rights on cost of equity capital", Corporate Governance: The international journal of business in society, Vol. 9 Iss 3 pp. 255-270 http://dx.doi.org/10.1108/14720700910964325 Yves Bozec, Claude Laurin, Iwan Meier, (2014),"The relation between excess control and cost of  capital", International Journal of Managerial Finance, Vol. 10 Iss 1 pp. 93-114 http://dx.doi.org/10.1108/ IJMF-12-2010-0095

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RAF 12,2

Customer value disclosure and cost of equity capital Raf Orens  Department of Accountancy, Finance and Insurance,  KU Leuven – Thomas More, Antwerpen, Belgium

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Walter Aerts

Received 6 March 2012 Revised 13 July 2012 8 October 2012 Accepted 30 November 2012

 Department of Accounting and Finance, Universiteit Antwerpen, Antwerpen, Belgium, and 

Nadine Lybaert  KIZOK, Hasselt University, Diepenbeek, Belgium Abstract Purpose   – This paper seeks to examine the association between a firm’s extent and precision of  customer value disclosure and its implied cost of equity capital. In addition, it aims to investigate whether industry competition intensity attenuates this association. Design/methodology/approach  – The co conte ntent nt of co corp rpor orat atee we webs bsite itess fr from om fo four ur co cont ntine inenta ntall European countries is analysed on the presence and precision of customer value information and empirically test whether content and precision are associated with the firm’s implied cost of equity capital measurement. Findings  – The results show a negative association between cross-sectional differences in the extent of cus custome tomerr valu valuee dis disclo closur suree and cro crossss-sec section tional al diff differe erence ncess in a firm firm’s ’s cos costt of equi equity ty cap capital ital.. In addition, the precision of the customer value information disclosed affects this association. It is observed obser ved that a negati negative ve relationship between quantitative quantitative (or hard) customer value disclosure and a firm’s cost of equity capital, but not for qualitative (or soft) customer value disclosure. As expected, indust ind ustry ry comp competi etitio tion n int intens ensity ity atte attenuat nuates es the ass associ ociatio ation n bet betwee ween n quan quantit titativ ativee cus custome tomerr val value ue disclosures and a firm’s cost of equity capital. Research limitations/implications   – The pape paperr con consid siders ers web plac placeme ement nt of cus custome tomerr valu valuee disclosure although a firm might disclose such information through other information channels as well. Practical implications  – A firm tends to benefit economically from more precise customer value

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disclosure. Originality/value   – The pape paperr ext extends ends exi existi sting ng evi eviden dence ce by con consid sideri ering ng the cap capita itall mark market et implications implic ations of disclo disclosing sing customer value information. In additio addition, n, it examines whether industry competition affects the association between customer value disclosure and the firm’s cost of equity capital.

Keywords Cost of equity capital, Customer value, Disclosure, Web reporting, Financial reporting, Equity capital Paper type  Research paper

Review of Accounting and Finance Vol. 12 No. 2, 2013 pp. 130-147 q Emerald Group Publishing Limited 1475-7702 DOI 10.1108/14757701311327696

1. Introduction This paper examines the association of the extent of a firm’s customer value disclosure and its cost of equity capital. Prior literature contends that customer relationships constitute an important intangible asset of a firm, but these assets are not transparent in traditional financial statements (Gupta   et al., 2004). Hence, firms have incentives

 

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to increase voluntary disclosure on the value of their customer relationships to enable investors inves tors to monitor firm performance and to demonstrate how these intang intangible ible assets create shareholder value (Wies (Wiesel el  et al., 2008; Luo  et al., 2010). Information asymmetry with regard to the value of a firm’s customer relationships could be significantly reduced by conveying information on, for example, customer satisfaction or product value attributes. attributes. Knowing that a firm’s customer resources are key drivers of its value creation process (Kaplan and Norton, 1996; Ittner and Larcker, 1998), disclosure of such resources might reduce estimation risk (Barry and Brown, 1985; Clarkson  et al., 1996), incre in creas asee th thee in inves vesto torr bas basee (M (Mer erton ton,, 198 1987) 7) an and d in incre creas asee st stock ock tra tradin ding g (D (Dia iamon mond d and Verrecchia, 1991), thereby lowering the firm’s cost of equity capital. Similar to Cormier  et al.  (2009) and Plumlee  et al.  (2010), we differentiate the extent of customer value disclosure by coding the precision of the information reported (i.e. quantitative or hard ha rd cu cust stom omer er va valu luee in infor format matio ion n ve vers rsus us qu qual alit itat ativ ivee or so soft ft cu cust stom omer er va valu luee information) since it increases the information content of the disclosure scores and improves insight into the nature of the association between voluntary disclosure and costt of equ cos equity ity cap capital ital.. In add additi ition, on, we inv invest estigat igatee whet whether her ind indust ustry ry com competi petitio tion n atte at tenua nuate tess th thee ass assoc ociat iation ion be betw twee een n th thee firm firm’s ’s ex exten tentt and th thee pre preci cisio sion n of th thee information disclosed and its cost of equity capital. To proxy for customer value disclosure, we analyze the content of the web pages of  firms. the between voluntary disclosure and thel,cost of ; equity equ ityExtant capital capi talliterature usuall usu ally y on relies rel ies association on pape paper-b r-based ased repo reportin rting g (Bo (Botos tosan, an, 1997 1997; ; Hai Hail, 2002; 2002 Espinosa and Trombetta, 2007). We add to this by constructing a disclosure score based on an analysis of the content of the corporate web site, as web-based reporting allows a firm to communicate more directly with its stakeholders in a cost-effective and timely way (Lymer, 1999; Bollen   et al., 2006). In particular, we focus on voluntary repor re portin ting g of cu cust stom omer er val value ue in infor format mation ion ava avail ilabl ablee in HT HTML ML fo form rmat at si sinc ncee su such ch information is comprehensive and accessible to all shareholders at low cost. Focusing on HT HTML ML fil files es ex excl clude udess ma manda ndate ted d co corpo rporat ratee doc docum umen ents ts,, wh whic ich h are li link nked ed to the web sit sitee (e. (e.g. g. audi audited ted finan financial cial statement statementss in PDF) PDF).. The Theref refore, ore, the dis disclo closure sure measure reflects only information that the firm has decided to voluntarily post on their web site. For a total of 217 continental European firms, we find evidence of a significant negative association between the extent of customer value information disclosed and the firm’s cost of equity capital. In addition, the association between customer value disclosure and the firm’s cost of equity capital shows to be stronger for quantitative than for qualitative customer value disclosure, suggesting that the precision of the corpor cor porate ate in infor format mation ion dis disclo closed sed aff affect ectss di discl sclosu osure re cre credi dibil bility ity and and,, thu thus, s, it itss effectiveness in lowering the firm’s cost of equity capital. Finally, the results show thatt comp tha competi etitio tion n int intensi ensity ty wit within hin an ind industr ustry y att attenua enuates tes the asso associa ciation tion bet between ween quantit qua ntitati ative ve cus custome tomerr val value ue inf informa ormatio tion n and a firm’ firm’ss cost of equ equity ity capi capital tal.. Thi Thiss finding suggests that a firm being transparent in a competitive environment is more likely to increase the credibility of its reported information compared to a similar firm in a less competitive industry. The paper proceeds as follows. The following section synthesizes relevant literature and develops the research hypotheses. Section Section 3 elaborate elaboratess on the research design and Section 4 reports the results of the empirical analyses. The final section discusses research results and potential limitations of this paper.

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2. Literature review and hypothesis development The following subsections discuss prior literature on the impact of a firm’s customer value val ue on eco econom nomic ic con conseq sequen uences ces,, the thereby reby dev develo elopin ping g pro propos positi itions ons abo about ut the association of customer value disclosure and a firm’s implied cost of equity capital.  2.1 Customer value disclosure Recognising the increased importance of non-financial assets in the value creation proce pr ocess ss of firm firms, s, Ka Kapl plan an an and d No Nort rton on (1 (1996 996)) de deve velo loped ped th thee ba bala lance nced d sc score orecar card d framewor fram ework k int integra egratin ting g finan financial cial and nonnon-finan financial cial indi indicato cators rs in a com compreh prehens ensive ive perf pe rform ormanc ancee me meas asure ureme ment nt sys syste tem. m. Fou Fourr pe pers rspec pecti tive vess are pu putt fo forwa rward rd to gr group oup performance measures: learning and growth, internal business processes, customer value and financial performance. These perspectives, separately and in combination, allow management management to link short-term short-term action actionss to long-term strategic objectives objectives of value creation in a strategic map. In this paper, we focus on a core perspective of the balanced scorecard framework, i.e. customer value. Prior research has validated empirical links between customer value assets and value val ue crea creatio tion. n. For ins instan tance, ce, cust custome omerr sat satisf isfacti action on or cus custom tomer er loy loyalt alty y have bee been n shown to impact short-term financial performance, measured as return on investment or cash flow growth (Ittner and Larcker, 1998; Smith and Wright, 2004; Gupta and Zeithaml, Other studies investigate investor response on customer value and show sho w that that,2006). , for ins instanc tance, e, cus custom tomer er sat satisf isfacti action on hol holds ds a posi positiv tive e rel relati ationsh onship ip wit with h shareholder value (Anderson   et al., 2004a; Luo and Bhattacharya, 2006; Torres and Tribo´ , 2011), with stock returns (Ittner and Larcker, 1998; Fornell  et al., 2006; Jacobson and Mizik, 2009), and with stock recommendations and consensus in the earnings forecast fore castss of finan financia ciall anal analysts ysts (Luo   et al., 2010). Hence, a considerable number of  studie stu diess poi point nt to a sig signific nificant ant rel relati ationsh onship ip bet between ween sev several eral cus custom tomer er met metrics rics and short-and short-an d long-t long-term erm financi financial al performan performance. ce. Ourr st Ou stud udy y co cont ntrib ribut utes es to th this is li lite terat rature ure by in inves vesti tiga gati ting ng wh whet ether her cu cust stome omerr relati rel ations onship hip tran transpa sparenc rency y is asso associa ciated ted wit with h a firm firm’s ’s cost of finan finance, ce, taki taking ng int into o account the precision of the information conveyed. We differ from prior research by focusi foc using ng on a firm’ firm’ss dis disclo closur suree pol policy icy with rega regard rd to cus custom tomer er val value ue inf informa ormation tion (such as customer information or product quality), instead of examining an association between a firm’s actual score on one specific customer value metric (e.g. customer satisfaction) and its financial performance.

 2.2 Extent of customer value disclosure and cost of equity capital  Taking into account prior research documenting a significant association between cust cu stome omerr val value ue com compo pone nent nt me metri trics cs (e (e.g .g.. cu custo stome merr sa sati tisf sfact actio ion n or lo loyal yalty ty)) and firm val value ue (Ittne (It tnerr and Larc Larcker, ker, 1998; And Anderso erson n et al al.., 20 2004 04a) a),, we ex expe pect ct th that at a fir firm’ m’ss cu cust stom omer er va valu luee transparency transpare ncy will affect its economic performance as well. In gen general eral,, Dia Diamon mond d and Ver Verrecc recchia hia (19 (1991) 91) pre predic dictt that enh enhance anced d dis disclos closure ure lea leads ds to a lower low er requ require ired d ret return urn on cap capital ital prov provide ided d by shar sharehol eholders ders and inv invest estors. ors. Hig Higher her qua qualit lity y informa inf ormatio tion n all allows ows inve investo stors rs to bett better er mon monitor itor man managem agement ent and inc increas reases es awar awarenes enesss to thee ca th capi pita tall ma mark rket et pa parti rtici cipa pants nts abo about ut th thee firm firm’s ’s va valu luee cre creat ation ion pro proce cess ss le leadi ading ng to a lo lowe werr information informa tion risk. risk. The non-di non-diversifiab versifiable le estimation estimation risk is reduced, reduced, allowing allowing investo investors rs to more accurately estimate the parameters underlying future cash flows (Barry and Brown, 1985; Clarkson et al., 1996). Hence, investors are more likely to trade, increasing

 

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the liquidity of firm’s shares and decreasing its cost of equity capital (Diamond and Verrecchia, 1991; Easley and O’Hara, 2004). Empirical studies confirm the negative associ ass ociatio ation n bet between ween a firm’ firm’ss cost of equ equity ity capita capitall and the ext extent ent of dis disclos closure ure (Botos (Botosan, an, 1997; Hail, 2002; Francis  et al., 2005; Espinosa and Trombetta, 2007; Dhaliwal  et al., 2011), although they do not explicitly explicitly consid consider er custom customer er value disclosure. disclosure. As customer value discl disclosure osure may directl directly y affect investor investor informa information tion asymmetry, we expect an inverse association between a firm’s cost of equity capital and the extent of cus custom tomer er valu valuee dis disclos closure. ure. Inc Increas reased ed cus custom tomer er val value ue dis disclos closure ure is expe expecte cted d to engender lower information and estimation risk, so that investors will require a lower investment return. Hence, we hypothesize that a firm with a higher level of customer value information on its corporate web site is more likely to enjoy a lower cost of equity capital compared to a firm with less extensive customer value information and state:

 H1.   A firm’s cost of equity capital is negatively negatively associated associated with the extent of its web-based web-b ased custome customerr value disclosure.  2.3 Precision of customer value disclosure and cost of equity capital  The effectiveness of customer value disclosure in changing investors’ perceptions may significantly depend not only on the extent of disclosure, but also on the nature of the infor in format mation ion di discl sclose osed. d. Cre Credi dibi bilit lity y in infer ferenc ences es con consti stitut tutee th thee ma main in arg argum ument ent to differentiate the effectiveness of information attributes (Cormier  et al., 2009). In this regard, Mercer (2004) contends that information precision is an important attribute underlying disclosure credibility. Disclosures vary in degree of precision, ranging from indicative and qualitative information to specifically quantified and monetary content. Quantitative or hard information may be more credible than qualitative or soft information since such information increases the  ex post  verifiability  verifiability of the information disclosed (Hutton  et al., 2003). Quantification lends itself to scrutiny in a way that more qualitative information does not. Disclosure credibility may also be enhanced by the presumption that hard disclosure is more difficult difficult to mimic by a firm’s competitors than soft disc disclosure losure(Cormi (Cormier er etal., 2009 2009). ). In add additi ition, on, qua quanti ntitat tative ive dis discl closu osure re may be vi viewe ewed d as revealing more proprietary information (Cho and Patten, 2007). Compared to qualitative disclosure, proprietary costs resulting from firm disclosure are likely to be higher for hard disclosure than soft disclosure since the firm may be perceived to reveal more accura acc urate te inf informa ormatio tion n (Ch (Cho o and Pat Patten ten,, 200 2007). 7). To the ext extent ent that quanti quantitat tative ive inf inform ormati ation on contai con tains ns prop proprie rietar tary y in inform formati ation, on, inv invest estors, ors, kno knowin wing g tha thatt dis disclo closi sing ng prop proprie rietar tary y information is costly, may perceive quantitative information to be more credible. Quanti Qua ntitat tative ive informati information on is als also o lik likely ely to be norm normativ ativee in the sense that such information informa tion allows comparability comparability through time or in space by offering the potenti potential al to benchm ben chmark ark wit with h pee peers rs or wit with h ind indust ustry ry profi profiles les.. Giv Given en thi thiss norm normati ative ve pot potent ential ial,, quantit qua ntitati ative ve inf informa ormation tion may sig signal nal suf suffici ficienc ency y of corp corporate orate act action ion and res respons ponses es (Anderson  et al., 2004b) and as such be more persuasive than qualitative information. Finally, quantification may also increase persuasive effectiveness as quantification tends to heighten the perceived competence of the source (Kadous  et al., 2005). Given Giv en the dis distin tincti ctive ve cre credib dibili ility ty and sig signal naling ing prop properti erties es of qua quanti ntitati tative ve and qualitative qualit ative information, information, and their underl underlying ying credibility, credibility, a firm’s cost of equity capital will be lower when a firm provides more quantit quantitative ative customer information information compared to qualitative or indicative customer information. This argumentation leads to the following hypothesis:

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 H2.   The negative association of a firm’s cost of equity capital with the extent of its web-based customer value disclosure is stronger for quantitative customer value disclosure than for qualitative customer value disclosure.  2.4 Industry competition intensity and the association between customer value disclosure and cost of equity capital  The association between the firm’s customer value disclosure and its cost of equity capital could be affected by the extent of market competition. Investors’ uncertainty about future firm performance is likely to be higher in more competitive industries where wh ere hi high gher er le leve vels ls of ri rival valry ry exi exist st am among ong in indu dust stry ry me memb mbers ers and wh where ere a firm would have a harder job retaining customers (Anderson  et al., 2004a; Luo  et al., 2010). Compet Com petit itio ion n red reduce ucess th thee li like keli lihoo hood d of pe persi rsiste stenc ncee in cus custo tome merr rel relati ations onshi hips ps (Seiders  et al., 2005), which increases the volatility in expected cash flows from these relationships relati onships.. In additi addition, on, the costs of retain retaining ing customers are less predictable predictable in more competitive environments (Srivastava et al., 1998). The higher level of customer-related uncertainty in competitive industries may constitute strong incentives for a firm to communicate more about its customer value to the public (Luo and Homburg, 2007). Increasing customer value disclosure in markets with more intense competition should enable investors to reduce their uncertainty and hence they might reward a more transparent firm with a lower cost equity capital. As cus custome tomer-r r-relat elated ed disclos dis closure ureofmig might ht ham hamper per the firm firm’s ’s comp competi etitiv tivee pos positi ition, on, proprietary costs related to voluntary disclosure are likely to be more prevalent in industries with more competition (Graham  et al., 2005; Li, 2010b), potentially potentially driving a firm’s firm ’s dec decisi ision on to wit withhol hhold d cust custome omer-re r-relat lated ed inf informa ormatio tion n in a mor moree comp competi etitive tive environment. On the other hand, given the presumption that customer value disclosure might be more costly in markets with intensive competition, customer value disclosure might mig ht inc increas reasee dis disclos closure ure cred credibi ibilit lity y (Me (Mercer rcer,, 2004 2004)) and and,, thu thus, s, its eff effect ective ivenes nesss in decreasing customer-related information asymmetries. Thes Th esee ar argu gume ment ntss re resu sult lt in th thee as assu sump mpti tion on th that at a fir firm m op oper erat atin ing g in a mo more re competitive competi tive industry industry is more likel likely y to benefit from customer customer value value disclosure disclosure compared to a firm operating in a less competitive industry since credibility perceptions of capital market participants are higher. In addition, we assume that the precision in terms of  hard and soft customer value information has a stronger effect on a firm’s cost of  equity capi equity capital tal in more comp competi etitiv tivee ind indust ustries ries than in les lesss comp competi etitiv tivee ind indust ustrie ries, s, leading to the following hypotheses:

 H3a.  The negative association of a firm’s cost of equity capital with the extent of its web-ba web -based sed cust custome omerr valu valuee dis disclos closure ure is str stronge ongerr in mark markets ets wit with h hig higher her competition than in markets with lower competition.  H3b.   The negative association of a firm’s cost of equity capital with the precision of  its web-based customer value disclosure is stronger in markets with higher competition than in markets with lower competition. 3. Research design 3.1 Sampl Samplee select selection ion This study focuses on the reporting practices of large non-financial firms (based on market mar ket cap capital italiza izatio tion) n) loc located ated in Bel Belgiu gium, m, Fran France, ce, Ger Germany many and The Net Netherl herlands ands..

 

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The These se four cont contine inental ntal Eur Europea opean n cou countri ntries es are typ typica ically lly code law coun countri tries es and share a similar institutional market context. Selecting the largest firms by country increases the likelihood that a substantial number of financial analysts and investors covers the sample sample firms (Bhushan, 1989), which which increases the quality quality of the information information enviro env ironmen nment. t. In add additi ition, on, larg larger er firm firmss ten tend d to have a more dispersed dispersed ownership ownership structure, increasing the incentives to voluntarily disclose information (Depoers, 2000). More specifically, the sample includes all non-financial listed firms belonging to the DAX70/D DAX 70/DAX30 AX30 (Ge (German rmany), y), SBF SBF120 120 (Fr (France ance), ), Euro Euronex nextt Bru Brussel sselss 50 big bigges gestt firm firmss (Belgium) and AEX/MIDKAP (The Netherlands). This selection procedure leads to a samp sa mple le of 25 255 5 fir firms ms fo forr wh whic ich h th thee co corp rpor orat atee we web b si site te in th thee su summ mmer er of ye year ar 20 2002 02 ha hass be been en examined examine d on the presence and properti properties es of custome customer-based r-based information information discl disclosure. osure.

Customer value disclosure

135

3.2 Measurement of customer value disclosure We in inve vest stig igate ate th thee vol volun untar tary y cu custo stome merr val value ue di disc sclo losu sure re av avai aila labl blee on a firm firm’s ’s web si site te in HTML HTM L form format. at. Focu Focusin sing g on HTM HTML L file filess excl exclude udess man mandate dated d corp corporate orate docu documen ments, ts, which are linked to the web site (e.g. audited financial statements in PDF). So, the disclosure measure reflects only information that the firm has decided to voluntarily post on its web site. Additionally, we exclude all web content related to customer direct-sales operations which tend to technically describe individual products/services and an d pri prices ces fro from m a co comm mmerc ercial ial po poin intt of vi view. ew. Ref Refer eren ence cess to pr produ oduct ctss and pri pricece-se sett ttin ing g are only included if framed and communicated as corporate value drivers or as corporate poli po licy cy is issu sues es.. In pa parti rticu cula lar, r, we an anal alyze yze th thee HT HTML ML we web b pag pages es of the sam sampl plee firm firmss us usin ing ga disclosure grid consisting of 16 information items related to customer value. Table I provides an overview of the coded content categories and their respective mean score.

Mean score

Mean score low competitive industry

Mean score high competitive industry

Product description Quality/up-to-date technology Reliability: errors/return Price Delivery time

1.69 0.96 0.23 0.15 0.13

1.81 0.95 0.23 0.19 0.13

1.50 1.05 0.26 0.08 0.13

A wards reprofile/market lated to producsegment/ ts Customer market share/number of customers Pre sales support: information/counsel/ follow up After sales service/insurance Customer satisfaction/complaints management Customer loyalty Awards related to customers Internet service E-business sales E-business productivity (cost efficiency/speed) Impact (award/number (award/number of users or visitors)

0.15

0.19

0.06

1.17

1.36

0.89

0.29 0.35

0.30 0.35

0.31 0.40

0.28 0.08 0.02 0.35 0.12

0.26 0.06 0.01 0.32 0.10

0.35 0.15 0.03 0.42 0.19

0.07

0.04

0.15

0.07

0.07

0.08

Customerr value Custome

Table I. List of information items

 

RAF 12,2

136    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

Each disclosure item gets a weighted score depending on the degree of detail that the firm discusses each item. We assign a weight of 2 for an item that is described in quantitative or monetary terms (hard information) and a score of 1 for an item that is described qualitatively or in non-monetary terms (soft information). Such a coding scale allows integrating different qualities of information into a single figure. In order to ensure consistency across firms when content analyzing the corporate web sites, two research assistants perform the coding of the web pages[1]. Tabl Ta blee I sh shows ows th that at th thee sam sampl plee firm firmss es espe peci cial ally ly re repor portt de deta tail iled ed in infor forma mati tion on aboutt the abou their ir prod product ucts, s, the qua qualit lity y of the their ir prod product uctss and the their ir cus custome tomers. rs. How However ever,, the Pearson correlation matrix (not tabulated) shows that each individual customer value disclosure item is significantly correlated with the total customer value score indicating that a firm reporting more on one specific disclosure item is more likely to provide detailed information related to other disclosure items included in the disclosure index ind ex as wel well. l. Rem Remarka arkably bly,, alt althoug hough h man many y stu studie diess repo report rt a stro strong ng lin link k bet between ween customer satisfaction and firm value, our results tend to indicate that our sample firms are quite reluctant to disclose such information on their corporate web site.

3.3 Measurement of the dependent variable Consistent with previous studies (Li, 2010a; Collins and Huang, 2011; Dhaliwal  et al., 2011), we employ an  ex ante  cost of equity capital implied implied in stock prices and analysts’ earnings forecasts. We use three different models to estimate the implied cost of equity capital cap ital:: the ind indust ustry ry ret return urn of equ equity ity mod model el dev develo eloped ped by Geb Gebhard hardtt   et al.   (2001), the unrestricted abnormal growth model developed by Gode and Mohanram (2003) and the restricted abnormal growth model developed by Easton (2004). The mean of  these th ese th thre reee mo mode dels ls se serv rves es as our pro proxy xy fo forr th thee cos costt of eq equi uity ty cap capit ital al si sinc ncee ea each ch in indi divi vidua duall esti es timat matee ma may y in incl clude ude a pot poten enti tial al me meas asure ureme ment nt er error ror or bi bias as (E (East aston on an and d Mon Monah ahan, an, 200 2005; 5; Dhaliwal et al al.., 201 2011). 1). Th These ese th thre reee me metho thods ds are var varia iati tions ons of ei eith ther er th thee re resi sidua duall in incom comee or thee di th divi vide dend nd di disc scou ount nt mod model el,, bu butt di diff ffer er fro from m ea each ch ot other her on ass assum umpt ption ionss abo about ut short-and short-an d long-term earnings growth and on forecast horizon (Hail and Leuz, 2006)[2]. 3.4 Regress Regression ion models In order to test  H1 , we relate a firm’s cost of equity capital to the total customer value disclosure score (CUS_T), as presented in equation (1a). This score has been partitioned in into toS_QN) a qua quali tativ ive discl sclosu score sco re (CUS_Q S_QL) and ato the quanti qua ntitat tativ e iable discl di sclosu score sco re (CUS_Q (CU N) inlitat order ord ere todi test te stosure (equat (eq uation ion(CU (1b)) (1b )). . In L) addit add ition ionto these se test tes tive varia var bles, s,osure werein inclu clude de  H2 re in these regression equations variables that control for other intervening factors[3]: COEi   ¼  b 0  þ  b1 CUS_Ti  þ  b2 SIZEi  þ  b3 MTBi  þ  b4 ROAi   þ industry dummies þ  country dummies COEi   ¼  b 0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  b3 SIZEi  þ  b4 MTBi  þ  b5 ROAi   þ industry dummies þ  country dummies

ð1aÞ

ð1bÞ

Table II includes a description of the variables used in the regression models. With Wi th reg regar ard d to th thee co contr ntrol ol var varia iabl bles es,, we exp expec ectt a neg negati ative ve as assoc sociat iation ion bet betwe ween en fir firm m si size ze (SIZE) and the implied cost of equity capital (Botosan, 1997; Hail, 2002; Li, 2010a), since capital market participants are better informed about the performance and activities of  larger firms compared to smaller firms (Espinosa and Trombetta, 2007). We further

 

Customer value disclosure

Variables Variabl es Descr Description iption

   )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

 Dependent variable COEi   Implied cost of equity capital for firm i, measured as the mean implied cost of equity capital estimates using the models developed by Gebhardt  et al.  (2001), Gode and Mohanram (2003) and Easton (2004) Test variables CUS_Ti   Extent of web-bas web-based ed customer customer value disclosur disclosuree of firm i CUS_QLi   Extent of qualitative qualitative web-based web-based customer value disclosure disclosure of firm i CUS_QNi   Extent of quantitative quantitative web-based web-based customer value disclosure disclosure of firm i COMi   Industr Industry y competition competition intensi intensity ty measured measured as a dummy variable indicat indicating ing 1 if firm i operates in a more competitive industry, 0 otherwise Control variables SIZEi   Size of firm i, measur measured ed as the the natural natural logarithm logarithm of total assets assets in 2002 MTBi   MarketMarket-to-book to-book ratio ratio of firm firm i, measured measured as the the natural natural logarithm logarithm of the ratio between between market capitalization and book value of equity in 2002 ROAi   Return on on assets assets of firm i,i, measured measured as the ratio between between net net income income scaled scaled by total assets assets in 2002

assume that a firm’s future growth opportunities, measured as the market-to-book ratio (MTB), (MT B), is neg negati atively vely associate associated d wit with h its imp implie lied d cost of equi equity ty capi capital tal sin since ce lowe lowerr market mar ket-t -to-b o-book ook rat ratios ios refl reflec ectt hi high gher er unc uncert ertain ainty ty abo about ut the firm firm’s ’s fut futur uree gro growth wth opportunities (Botosan and Plumlee, 2005; Hail and Leuz, 2006). Profitability (ROA) is meas me asure ured d as th thee firm firm’s ’s ret retur urn n on ass assetsand etsand is exp expect ected ed to sho show w a ne negat gativ ivee ass associ ociati ation on wi with th thee firm th firm’s ’s cos costt of equ equit ity y cap capit ital al (Fr (Franc ancis is et al al.., 200 2005) 5) du duee to inc increa reased sed unc uncert ertai aint nty y abo about ut th thee futur fu turee fina financ ncia iall pe perfo rforma rmance nce (Br (Brown own,, 200 2001). 1).Sim Simil ilar ar to Li (20 (2010a 10a)) and Dh Dhal aliw iwal al et al al.. (2011), we insert industry dummies into our specifications. These dummies are based on the Standards and Poor’s industry classification: consumer goods and services, materials (resources), energy, industrials, health care, utilities, information technology, and telecom and media. Finally, all equati equations ons include country dummy variabl variables. es. In order to further test whether industry competition moderates the association between the firm’s extent and precision of customer value disclosure and its cost of  equity capital, we replace the industry dummies of equations (1a) and (1b) with an industry dummy variable COM having the value of 1 if the firm belongs to a more competitive competi tive industry and 0 otherwi otherwise. se. To test H3a  and  H3b , we include an interaction variable combining the extent of and the precision of customer value disclosure with industry concentration, leading to regression equations (2a) and (2b): COEi   ¼  b 0  þ  b1 CUS_Ti  þ  b2 COMi  þ  b3 CUS_Ti   £ COMi  þ  b4 SIZEi   dummies es þ b 5 MTBi  þ  b6 ROAi  þ  country dummi COEi   ¼ b0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  b3 COMi  þ  b4 CUS_QLi   £ COMi þ b 5 CUS_QNi   £ COMi  þ  b 6 SIZEi  þ  b 7 MTBi  þ  b8 ROAi

ð2aÞ

ð2bÞ

þ country dummie dummiess

We measure competition intensity as the extent of industry concentration (Harris, 1998; Botosan and Stanford, 2005; Verrecchia and Weber, 2006). A low level of industry concen con centrati tration on corr correspo esponds nds with hig high h ind indust ustry ry com competi petitio tion n int intens ensity. ity. In orde orderr to clas classif sify y a firm as belonging to a competitive industry, we first assign each firm to one of the

137

Table II. Description of  the variabl variables es

 

RAF 12,2

138    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

eig eight ht mai main n (no (non-fin n-financ ancial ial)) ind indust ustrie riess of the Sta Standar ndards ds and Poor Poor’s ’s ind indust ustry ry cla classifi ssificati cation. on. For each industry, we measure the level of concentration for each industry based on the percentage of market share held by the largest four firms in that industry (Harris, 1998; Ali  et al., 2009; Bens  et al., 2011). Based on the mean value of industry concentration, we consider materials (resources), health care, utilities and information technology as a high hig h com compet petiti itive ve ind indust ustry ry and con consum sumer er good goodss and ser servic vices, es, ene energy rgy,, ind industr ustrial ials, s, telecom and media as a low competitive industry. Table I additionally outlines the extent to which both group of firms disclose customer value information. For many items,, we do not observe a signific items significant ant difference in transparency between both groups. We onl only y find th that at firm firmss fro from m mo more re com compet petit itiv ivee in indu dust stri ries es are le less ss li like kely ly to be transparent transpare nt about their customer profile, which tend to indicate that competitive costs might drive a firm’s decision to disclose such information. Datastream includes the necessary data to measure all variables. Due to missing values for the computation of the implied cost of equity cost estimates and due to outliers, the sample size reduces from 255 observations to 217 observations.

4. Results 4.1 Descriptive statistics Table III presents descriptive statistics on the dependent and independent variables for the samplevalue firms,information and illu illustrates strates that the sample firms report more qualitative qualitativ (or soft) customer (CUS_QL  )i compared to quantitative (or hard) ecustomer value information (CUS_QNi ). Table III also shows that the average cost of capital is 14.1 percent which is comparable to previous research (Hail and Leuz, 2006; Li, 2010a). Total assets and market-to-book ratio are highly skewed and therefore we use the log transformation for these variables. Table IV reports Pearson correlation coefficients for the variables included in our study. We observe that the implied cost of equity capital is negatively associated associated with thee ex th exten tentt of cus custo tome merr val value ue di disc sclos losur uree (C (CUS US_T _T)) an and d th thee ex exte tent nt of qu quant antit itati ative ve customer value disclosure (CUS_QN), but not with the extent of qualitative customer Mean

Median

Maximum

Minimum

SD

14.1

13.0

38.9

3.3

6.0

6.6 4.3 2.4 0.4

5.0 3.0 2.0 0.0

38.0 20.0 20.0 1.0

0.0 0.0 0.0 0.0

5.3 3.6 2.9 0.5

15,096 2.6 4.0

5,040 1.8 3.3

207,000 0.3 74.7

93 14.7 2 31.8

27,891 2.4 8.5

 Dependent variable COEi   Test variables CUS_Ti   CUS_QLi   CUS_QNi   COMi   Control variables SIZEi  (in th.   e ) MTBi   ROAi   (in %)

Table III. Descriptive statistics

 

Notes:   This table provides descriptive statistics of the variables COE i   – average implied cost of  equity capital; CUS_Ti  – extent of web-based customer value disclosure of firm i; CUS_QL i  – extent of  qualitative web-based customer value disclosure of firm i; CUS_QN i   – exten extentt of quantitative webbased customer value disclosure of firm i; COM i  – industry competition intensity of firm i; SIZE i  – size of firm i; MTBi  – market-to-book ratio of firm i; ROA i  – return on assets of firm I;  n  ¼  217

 

COEi

   )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

COEi   CUS_Ti   CUS_  QLi   CUS_  QNi   COMi   SIZEi   MTBi   ROAi  

 

CUS_Ti   CUS_QLi   CUS_QNi   COMi

 

SIZEi

 

MTBi   ROAi

Customer value disclosure

1.000

2 0.115 *

1.000

2 0.020

0.844 * * *

1.000

2 0.180 * * * 0.768 * * * 0.304 * * * 1.000 0.024   2 0.090   2 0.012   2 0.145 * * 1.000 2 0.066 0.026 0.021 0.021 0.059 1.000 2 0.310 * * * 0.063 0.035 0.070   2 0.088   2 0.176 * * * 1.000 2 0.249 * * * 2 0.059   2 0.034   2 0.064 0.083   2 0.203 * * * 0.175 * * * 1.000

Notes:   Statistically significant at:   *10,   * *5 and   * * *1 percent levels; this table provides the Pearson correlation coefficients between the variables COEi  – average implied cost of equity capital; CUS_T i  –  extent of web-based customer value disclosure of firm i; CUS_QLi  – extent of qualitative web-based customer value disclosure of firm i; CUS_QNi   – extent of quantitative web-based web-based customer value disclosure of firm i; COM i  – industry competition intensity of firm i; SIZE i  – size of firm i; MTB i   –  market-to-book ratio of firm i; ROA i  – return on assets of firm i;  n  ¼  217

value disclosure (CUS_QL). Tablethat IV also demonstrates low correlations between the independent variables indicating problems of multicollinearity are absent.

4.2 Extent of customer value disclosure and cost of equity capital  Table Tab le V rep report ortss the mul multiv tivari ariate ate regr regress ession ion resu results lts on the ass associ ociati ation on bet betwee ween n the ext extent ent of web-based disclosure about a firm’s customer value and its implied cost of equity capital. Findings on equation (1a) suggest that a firm conveying more customer value information on its web site tends to have a significantly lower cost of equity capital compar com pared ed to a firm dis disclo closin sing g les lesss cus custom tomer er val value ue inf informa ormatio tion. n. The These se res result ultss sup suppor portt H1. Table V further notes significant associations between a firm’s cost of equity capital and several control variables. A firm’s cost of equity capital is larger for smaller firms as opposed to larger firms. Profitabi Profitability lity has a negati negative ve relationship with a firm’s implied cost of equity capital. Finally, a negative association exists between a firm’s market-to-book ratio and its implied cost of equity capital. 4.3 Precision of customer value disclosure and cost of equity capital  Table V reports the corresponding regression results when we decompose the total custome cus tomerr valu valuee dis disclos closure ure scor scoree int into o a qua quanti ntitati tative ve and a qual qualitat itative ive com compone ponent nt score and relate these scores to the firm’s cost of equity capital (equation (1b)). These results show an increase in the explanatory power (  R 2 ) of the regression models compared with the models including a single measure of customer value disclosure (from 19.7 to 21.5 percent). Resear Res earch ch res result ultss reve reveal al that the firm firm’s ’s imp impli lied ed cost of equ equity ity cap capita itall sho shows ws a signifi sig nifican cantt neg negati ative ve ass associ ociati ation on wit with h the ext extent ent of quan quanti titat tative ive cus custom tomer er val value ue disclosure disc losure,, but not with the exten extentt of quali qualitativ tativee custo customer mer value discl disclosure. osure. Henc Hence, e, these results confirm   H2 . The finding suggests that investors tend to take into account quantitative or hard customer value information more than qualitative or soft customer value information in their deliberations.

139

Table IV. Correlation matrix

 

RAF 12,2

140    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

Equation

(1a)

Intercept CUS_Ti   CUS_QLi CUS_QNi COMi CUS_Ti   £   COMi CUS_QLi   £   COMi CUS_QNi   £   COMi SIZEi     MTBi ROAi   Industry dummies Country dummies Adjusted  R  2 (%)  F -statistic

(1b)

26.640 * * * 2 0.201 * * *

26.448 * * *

2 0.005 2 0.465 * * *

     

(2a) 30.190 * * * 2 0.147 * *

29.658 * * *

2 0.076 2 0.520 * *

  0.283 0.033

 

(2b)

 

 

2 0.051

2 0.336 * 2 5.764 * * * 2 12.852 *

  2 0.328 * 2 5.748 * * * 2 13.017 *

2 0.581 * * * 2 5.068 * * * 2 16.930 * *

0.249 2 0.573 * * 2 0.557 * * * 2 4.960 * * * 2 16.940 * * *

Ye s Ye s 19.7 6.284 * * *

Yes Yes 21.5 6.379 * * *

Yes 14.9 6.405 * * *

Ye s 17.3 6.032 * * *

Notes: Statistically significant at:   *10,   * *5 and   * * *1 percent levels; this table reports  b  coefficients of  the following regression equations: COEi   ¼ b0  þ  b1 CUS_Ti  þ  b2 SIZEi  þ  b3 MTBi  þ  b4 ROAi  þ  in  industry dustry dummies

ð1aÞ

þ c  country ountry dummies

COEi  ¼   b0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  b3 SIZEi  þ  b4 MTBi  þ  b5 ROAi þ i  industr ndustry y dummies þ  c  country ountry dummies

COEi   ¼ b0  þ  b1 CUS_Ti  þ  b 2 COMi  þ  b3 CUS_Ti  £ COMi  þ  b4 SIZEi  þ  b5 MTBi þ b6 ROAi  þ  c  country ountry dummies

ð1bÞ

ð2aÞ

COEi   ¼ b0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  b3 COMi  þ  b4 CUS_QLi   £ COMi þ b5 CUS_QNi   £ COMi  þ  b6 SIZEi  þ  b7 MTB i  þ  b8 ROAi

ð2bÞ

þ c  country ountry dummies

Table V. Regression results of the implied cost of equity capital on customer value disclosure

with COEi  – average implied cost of equity capital; CUS_T i  – extent of web-based customer value disclosure of firm i; CUS_QLi  – extent of qualitative web-based customer value disclosure of firm i; CUS_QNi  – extent of quantitative web-based customer value disclosure of firm i; COM i   – industry competition intensity of firm i; SIZEi  – size of firm i; MTBi  – market-to-book ratio of firm i; ROAi   –  return on assets of firm i;  n  ¼  217

4.4 Industry competition intensity and the association between customer value disclosure and cost of equity capital  As postulated in  H3, we assume that the impact of disclosure on a firm’s cost of equity capit cap ital al wil willl be st stron ronger ger in mor moree com compe peti titi tive ve in indus dustri tries, es, in indi dicat catin ing g tha thatt in indu dustr stry y competition intensity attenuates the association between the firm’s cost of equity capital and ei eithe therr the ext extent ent of cu custo stomer mer val value ue di discl sclosu osure re (  H3a ) or the precisio precision n of customer value disclosu disc losure re (  H3b ). With respect to the extent of customer-b customer-based ased disclosu disclosure, re, Table V (equati (equ ation on (2a) (2a))) show showss an insi insignifi gnificant cant inte interacti raction on vari variable able,, whic which h is inco inconsi nsisten stentt with H3a. Next, Table V (equation (2b)) reports results of the impact of industry competition intensity on the association between the firm’s cost of equity capital and the precision

 

   )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

of cu cust stom omer er val value ue di disc sclos losur ure. e. Par Partit titio ioni ning ng th thee di disc sclos losur uree sc score oress im impro prove vess th thee explanatory explana tory power of the regression models (from 14.9 to 17.3 percent), indicating indicating that a singl singlee discl disclosure osure score is less informat informative. ive. The interac interaction tion variable CUS_QN   £  COM shows a negative association with the implied cost of equity capital. These findings suggest that a firm belonging to a more competitive industry is more likely to benefit from expanded quantitative customer disclosures compared to a firm belonging to a less competitive industry. The inte interacti raction on variab variable le CUS_QL  £   COM COM doe doess not sho show w a sig signi nifican ficantt ass associ ociati ation on wit with h thee firm th firm’s ’s co cost st of eq equi uity ty.. A firm doe doess no nott be bene nefit fit mo more re fr from om pr prov ovid idin ing g so soft ft in infor format matio ion n in terms of lower cost of equity capital when industry competition intensity is larger. The research findings only support  H3b  for quantitative customer value information.

4.5 Sensitivity analysis: the use of proxies for information asymmetry as dependent  variable We rep repeat eat the ana analys lyses es in the prev previou iouss sec sectio tions ns usi using ng prox proxies ies for inf inform ormati ation on asy asymme mmetry try as dep depend endent ent vari variabl able. e. Com Compar pared ed to the im impli plied ed cost of equ equity ity cap capita itall est estima imates tes,, measur mea sures es of in inform formati ation on asy asymme mmetry try are les lesss sub subjec jectt to mea measur sureme ement nt erro errors rs sin since ce the they y do not rely on accounting-based valuation models or analysts’ forecasts (Li, 2010a). We adopt ado pt bid bid-as -ask k spr spread ead and tra tradin ding g vol volume ume as prox proxies ies for inf inform ormati ation on asy asymme mmetry try (Leuz and Verrecchia, 2000; Zhang and Ding, 2006). Bid-ask spread is measured as the absolute value of the median of the daily difference between bid-price and ask-price scaled by the average of the bid-price and ask-price. Trading volume is specified as the medi me dian an da dail ily y st stoc ock k tur turno nove verr (i (i.e .e.. vol volum umee of sh shar ares es tr trad aded ed mu mult ltip ipli lied ed wi with th st stoc ock k pr pric icee an and d divide div ided d by mark market et cap capita italiz lizati ation) on).. The reg regres ressio sion n equ equati ations ons inc includ ludee the sam samee tes testt variables together with control variables. Based on prior research, we include firm size, owners own ership hip structure structure (me (measu asured red as a dum dummy my vari variabl ablee wit with h the value 1 whe when n one shareholder possesses more than 20 percent of a firm’s shares and 0 otherwise), stock return variability (measured as the standard deviation of the daily stock price returns during one year), country dummy variables and industry dummy variables (but only in the regr regress ession ionequ equati ations ons thatdo not con contro troll for in indus dustry trycom compet petiti ition) on) as con controlvaria trolvariabl bles. es. Research results in Table VI are similar to those reported in Table V. The research findings reveal a negative association between information asymmetry asymmetry and the extent of  customer value information (equation (1a)). Customer value disclosure has a negative assoc ass ociat iatio ion n wit with h bi bid-a d-ask sk spr spread ead and a pos posit itiv ivee ass associ ociat ation ion wi with th tr tradi ading ng vo volum lume. e. Inc Inclu ludi ding ng the precision of customer value disclosure into the regression equations improves the expla exp lanat natory ory pow power er (  R 2 ) of these equations equations consisten consistentt with the improved informativene informativeness ss of the cu custo stome merr va value lue di discl sclos osure ures. s. We not notic icee th that at tra tradi ding ng vol volum umee has a neg negat ative ive association associati on only with quantitative customer disclosure. disclosure. The bid-ask spread is negative negatively ly related to the extent of quantitative customer value disclosure as well as to the extent of  qualitat qual itative ive cust customer omer valu valuee disc disclosu losure re (equ (equatio ation n (1b) (1b)). ). Tabl Tablee VI shows a sig signific nificant ant interaction variable CUS_T   £ COM in the specification regressing the bid-ask spread (equati (equ ation on (2a) (2a)), ), indi indicati cating ng that a more morecomp competi etitiv tivee env environ ironmen mentt incr increase easess the effe effect ct of more intense customer value disclosure on the bid-ask spread. This interaction variable is howeve how everr ins insig igni nifica ficant nt whe when n tra tradin ding g vol volum umee is in incl clude uded d as de depen pende dent nt var variab iable le.. Con Consi siste stent nt with the cost of equity specifications, we observe that industry competition enlarges the negative association between the level of information asymmetry and customer value disclosure, but only when a firm discloses hard information (equation (2b)).

Customer value disclosure

141

 

RAF 12,2

142    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

Equation

(1a)

 Panel A: bid ask spread (n  ¼  202) Intercept 3.119 * * * CUS_Ti   2 0.028 * * CUS_QLi   CUS_QNi   COMi   CUS_Ti   £   COMi CUS_QLi   £   COMi CUS_QNi   £   COMi Control variables Ye s Adjusted  R  2 (%) 31.1  F -statistic 19.151 * * *  Panel B: trading volume (n  ¼  209) Intercept   2 2.538 * CUS_Ti   0.081 * * * CUS_QLi   CUS_QNi   COMi   CUS_Ti   £   COMi CUS_QLi   £   COMi CUS_QNi   £   COMi Control variables Ye s 2 Adjusted  R  (%) 32.0  F -statistic 20.545 * * *

(1b)

(2a)

3.966 * * *

(2b)

3.206 * * * 2 0.207 * * *

2 0.034 * * 2 0.033 * *

2 0.013 2 0.029 * *

 

3.151 * * *

2 0.017 *  

2 0.002 2 0.064 * *

    Yes 35.2 19.655 * * *

2 2.520

2 0.029 * * * 2 0.037

Yes 31.8 14.419 * * *

 

2 2.561 *

0.076 * * *

0.170 0.024

2 0.092

    Yes 32.4 17.622 * * *

2 2.517 0.082 * * 0.068 * * 0.314

0.040 0.134 * * *  

Ye s 32.2 11.591 * * *

Yes 31.5 14.685 * * *

0.313 * * Ye s 34.9 13.365 * * *

Notes: Statistically significant at:   *10,   * *5 and   * * *1 percent levels; this table reports  b  coefficients of  the following regression equations: IAi   ¼  b 0  þ  b1 CUS_Ti  þ  co  control ntrol variabl variables es

ð1aÞ

IAi   ¼  b 0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  c  control ontrol variable variabless

ð1bÞ

IAi   ¼  b 0  þ  b1 CUS_Ti  þ  b2 COMi  þ  b3 CUS_Ti  £ COMi  þ  co  control ntrol variable variabless

ð2aÞ

IAi   ¼ b0  þ  b1 CUS_QLi  þ  b2 CUS_QNi  þ  b3 COMi  þ  b4 CUS_QLi   £ COMi þ b5 CUS_QNi  £ COMi  þ  c  control ontrol variabl variables es

Table VI. Sensitivity analysis: information asymmetry on custome customerr value disclosure

 

ð2bÞ

with IAi  – the extent of information asymmetry of firm i proxied with the bid-ask spread (Panel A) and trading volume volume (Panel B); CUS_Ti  – extent of web-based customer value disclosure of firm i; CUS_  QLi   – ext extent ent of qual qualitat itative ive web-based web-based customer customer valu valuee dis disclo closur suree of firm i; CUS CUS_QN _QNi   – ex exte tent nt of  quantitative web-based customer value disclosure of firm i; COMi  – industr industry y competition competition intensity of  firm i; The control variables include firm size, firm’s ownership structure, firm’s volatility in stock price returns, country dummies and industry industries (the latter only in equations (1a) and (1b))

5. Discussion and conclusion This Th is pap paper er exp explor lores es th thee ass assoc ociat iation ion bet betwee ween n a firm firm’s ’s ext extent ent of web web-ba -based sed dis disclo closur suree of it itss cust cu stom omer er va valu luee an and d it itss co cost st of eq equi uity ty ca capi pita tal. l. Fo Forr a sa samp mple le of co cont ntin inen enta tall Eu Euro rope pean an fir firms ms,, we find a significant negative association between a firm’s cost of equity capital and

 

   )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

customer value information disclosed on its web site. Additionally the precision of  customer value disclosure has a moderating effect on this association, suggesting that capital market participants perceive quantitative or hard customer value information as moree use mor usefu full and mor moree cre credib dible le.. Th These ese find findin ings gs sug sugge gest st tha thatt inv inves estor torss see seem m to rec reckon konmor moree quantitative customer value information in their decision making process compared to quali qua litat tativ ivee cu custo stome merr val value ue in infor format matio ion. n. Th They ey per percei ceive ve har hard d inf inform ormati ation on as mor moree cre credi dible ble information which allows them to require a lower return on the resources they invest. We also note that industry competition intensity impacts the association between customer value disclosure and the cost of equity capital. The negative association between quantitative disclosure and a firm’s cost of equity capital is stronger when the firm operates in a market with fierce competition compared to a firm in a market with less intensive competition. This finding suggests that capital market participants tend to consider quantitative customer value disclosures as strong and credible signals of  custome cus tomerr val value, ue, esp especi eciall ally y in a hig high h com compet petiti ition on env enviro ironmen nmentt wher wheree the prop proprie rietary tary cost of quan quantit titati ative ve dis disclos closures ures is deem deemed ed to be hig higher her than in les lesss comp competi etitiv tivee env environ ironmen ments. ts. The results respond to prior studies arguing that a firm has incentives to pay attention to their communication about the value of customer relationships. The results document that investors judge the value of customer relationships and reward a firm being bei ng more tran transpar sparent ent in its comm communi unicati cation on abou aboutt its cust custome omerr rel relati ationsh onships ips by requiring return on the they invest. Hence, the highlight the impor im porta tanc nceae lower of th the e av avai aila labi bili lity tyresources of pre preci cise se in infor forma mati tion on ab about outresults a firm firm’s ’s cu cust stom omer er relationships when investors assess a firm. So, investor relations managers should active act ively ly sol solici icitt cus custome tomerr val value ue inf informa ormatio tion n and, mor moree spe specific cificall ally, y, hig high h qua qualit lity y information for inclusion in their disclosure policy. The results are also consistent with thee ef th effo forts rts of th thee Fi Finan nanci cial al Ac Accou count ntin ing g St Stan andar dards ds Bo Board ard and th thee In Inte terna rnati tiona onall Accounting Standards Board to recommend firms to increase voluntary disclosure on their intangible intangible resource resourcess that do not transpire the mandatory financial statements. statements. This study is subje subject ct to some limi limitations. tations. We only only observe observe voluntar voluntary y web placem placement ent of customer value information, which means that the information on the corporate web site does not necessarily include new information. A firm may also consider reporting customer value information by means of other communication sources, but we do not control for this. Next, we relate cross-sectional differences in the cost of equity capital with wit h cros cross-s s-sect ectiona ionall dif differe ference ncess in cus custom tomer er valu valuee dis disclos closure ure,, and hen hence ce we are unab unable le to draw causal inferences. Notes 1. The data collection phase of the project was performed by five research assistants assistants (graduate students) simultaneously and extended over a three weeks period in order to avoid temporal differences in web site content as much as possible. They printed all identified web pages for each eac h fir firm. m. Th Thee ac actu tual al co cont nten entt cod codin ing g of th thee pr prin intedpage tedpagess of a pa parti rticu cular lar fir firm m wa wass pe perfo rform rmed ed in a second phase by two research research assistants assistants who were were not involv involved ed in the initial data collection collection for that firm. Coding instructions (including category definitions and coding rules), as well as standardized coding worksheets, were prepared beforehand. Each coder then applied the followi foll owing ng cod coding ing seq sequen uence: ce: (1) ind indepen ependen dentt iden identifi tificati cation on of the occu occurren rrence ce of item itemss rela relativ tivee to thee cod th codin ing g cat categ egori ories es on th thee pr prin inted ted we web b pa page ges; s; (2) in inde depe pend nden entt co codi ding ng of th thee ite items ms ac accor cordi ding ng to th thee qu quali ality ty le leve vell of con conte tent nt;; an and d (3)time (3)timed d re recon conci cilia liatio tion n on a su subs bset et of com compa pany ny re repo ports rts.. Th Thee coders were trained by one of the co-researchers in applying coding instructions and in using the coding worksheets. worksheets. The trainin training g went over a few weeks as the coders and the researche researcherr

Customer value disclosure

143

 

   )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

RAF 12,2

mutually verified their coding on a subsample of test cases, typically two firms by industry. Coders were unaware of the research hypotheses. Initial differences in identifying grid items accounted for an average of 7 percent of the maximum number of items identified. Of the information quality level coding, less than 10 percent had to be discussed for reconciliation. Disagreement Disagre ement between coders mostly happened at the beginning beginning of the coding process. The researcher reconciled coding disagreements exceeding 5 percent of the highest total score

144

between the two coders. Smaller disagreements were resolved by the two coders themselves. 2. Gebhardt Gebhardt et al. (2001), makes use of the residual income valuation model. The implied cost of  equity equ ity cap capital ital is mea measure sured d foll followi owing ng a thr three ee stag stagee app approac roach. h. Fir First, st, ana analys lysts’ ts’ earn earning ingss forecasts of the first three years are measured. Second, for the next nine years, earnings forecasts are obtained by linearly fading the earnings forecast of the third year to the industry median return on equity. Third, beyond the forecast horizon, the residual income remains constant in perpetuity. The following model is specified: n

P0   ¼  bps 0  þ

X t¼1

þ

T

ðxtþt 2 re · bp bpsstþt21 Þ ðxtþt 2 re · bp bpsstþt21 Þ   þ t ð1  þ  re Þ ð1  þ  r e Þt t¼nþ1

X

^

^

xtþTþ1 2 re · bp bpsstþT ^

re ð1  þ  r e ÞT

with: P0  – share price price of at the end of period t; bps0   – account accounting ing book value per share share at the begi be ginn nnin ing g of th thee fis fiscal cal ye year; ar; xtþt – expected future accounting earnings for period (1  þ  t 2 1, 1  þ  t ) either explicitly forecasted, generated by a linear fading rate or assumed constant; re   – est estim imat atee of the   ex ante   cost of equity capital; bpstþ   – exp expecte ected d fut future ure accounting book value of equity at date t  þ  t , where bpstþ  ¼   bpstþ  2   1  þ xtþt 2 dtþt wheredtþt  – expected future net dividends for period (1  þ  t 2 1, 1  þ  t ), derived from the dividend payout ratio k times the earnings forecastxtþt . Gode and Mohanram (2003) uses an inverse proxy of the abnormal earnings growth model to estimate the implied cost of equity capital. The metric assumes that the abnormal growth beyond the forecast horizon equals the risk free rate minus 3 percent instead of  estimating this growth rate. Cost of equity capital is measured as follows:  

^

t

  ^

t

t

  ^

^

^

y21 re   ¼   þ 2

s  ffiffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi y21 2

2

þ

epstþ1 ð g 2 2 ðy 2 1ÞÞ Pt

with: re  – of (eps the ex ante cost of equity capital; y – one plus the perpetual growth rate for theestimate firm; g 2  – tþ 2 2 epstþ 1 )/epstþ 1; epstþ 2  – mean analysts’ earnings per share forecasts of year t  þ  2; epstþ 1  – mean analysts’ earnings per share forecasts of year t  þ  1; Pt  – share price at the end of period t. Gode and Mohanram (2003) make the assumption that abnormal growth in earnings after the forecast horizon is the same for all firms, which is an estimate of the long-term growth rate in the economy economy.. In our study, the perpetual growth growth rate is set at 4 percen percent. t. Easton (2004) estimates firm’s cost of equity capital by means of the square root of the inverse of the price-earnings-growth (PEG) ratio: re   ¼

r  ffiffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi ffi epstþ2 2 epstþ1 Pt

with: re  – estimate of the ex ante cost of equity capital; capital; epstþ 2  – mean analysts’ earnings per share forecasts estimated at fiscal year t  þ  2; epstþ 1  – mean analysts’ earnings per share forecasts estimated at fiscal year t  þ  1; Pt  – share price at the end of fiscal year t.

 

The PEG-method concentrates on firm’s earnings growth, but makes the assumption that abnormal earnings do not grow after the forecast horizon. 3. As a sensitivity analysis, analysis, we also control for other potential potential factors on a firm’s cost of equity capital such as the presence of negative earnings, leverage and analyst following but we opt to exc exclud ludee the these se con control trol var variab iables les from the main estimation estimation equations equations due to pot potenti ential al multicollinearity problems with the remaining control variables. The regression results with    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

respect to the test variabl variables es (i.e. the extent and the precision of customer value disclosure) disclosure) do not alter including these variables into the equations.

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Canadian Journal of Administrative Sciences, Vol. 26 No. 1, pp. 71-88.

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146    )    T    P    (    5    1    0    2   r   e    b   m   e    t   p   e    S    6    1    1    2   :    3    2    t    A    A    G    A    J    I    L    A    K    N    A    N    U    S    I    R    E    G    E    N      M    A    L    S    I    S    A    T    I    S    R    E    V    I    N    U   y    b    d   e    d   a   o    l   n   w   o    D

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Corresponding author Raf Orens can be contacted at: [email protected]

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