The effects of an articulated customer value proposition (CVP) on promotional expense, brand investment and firm performance in B2B markets: A text based analysis

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Industrial Marketing Management journal homepage: www.elsevier.com/locate/indmarman

Research paper

The effects of an articulated customer value proposition (CVP) on promotional expense, brand investment and firm performance in B2B markets: A text based analysis Sagarika Mishraa, Michael T. Ewingb, Leyland F. Pittc,d,

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a

Department of Finance, Deakin Business School, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125, Australia Faculty of Business & Law, Deakin University, 221 Burwood Hwy, Burwood, VIC 3125, Australia c Beedie School of Business, Simon Fraser University, 500 Granville St., Vancouver V6C 1W6, Canada d Hanken, Helsinki, Finland b

A B S T R A C T

Using text-based analysis, we search for evidence of articulated customer value propositions (CVP), in annual reports of US B2B firms, and then demonstrate that B2B firms that explicitly emphasize a CVP invest more in their brands, have higher future sales and sales per customer. We also find that CVP has a negative effect on the size of their customer base, perhaps because firms who care about a CVP appear to attract more long-term, loyal customers. Firms that pay more attention to CVP also tend to spend less on advertising and promotion. Future performance, particularly among small to mid-size firms, is positively affected when these firms emphasize CVP, and this also holds especially in less competitive markets. Our findings are based on a large dataset of around 12,000 firm year observations for a 14-year period from 2004 to 2017.

1. Introduction Marketing offerings in business-to-business (B2B) markets is arguably more challenging than in consumer markets. Being more rational than end consumers, and driven by profit and/or efficiency goals, B2B buyers focus more on the price and performance of the products they procure. By purchasing goods and services at lower prices, firms know that they can lower their own costs. However, beyond simply lowering their prices, a better solution for B2B marketers is to persuade their buyers to pay premium prices for offerings that are perceived to provide greater value. The way to do this, according to Anderson, Narus, and Van Rossum (2006), is to “craft a compelling customer value proposition” (p. 91). By fully understanding a B2B customer's unique requirements, making it clear to that customer that they will be gaining benefits not obtainable elsewhere, and articulating the cost savings and profits that will ensue from being willing to pay the higher price, a B2B firm can gain an advantageous foothold in the markets it serves. In that way its customers will gain what has been referred to as “value-in-use” (Ballantyne, Frow, Varey, & Payne, 2011; Eggert, Ulaga, Frow, & Payne, 2018; Kowalkowski, 2011), rather than simply value-in-exchange. In this paper we employ the definition of a customer value proposition (CVP) as formulated by Payne, Frow, and Eggert (2017) as “… a strategic tool facilitating communication of an organization's ability to share resources and offer a superior value package to targeted

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customers” (p. 472). Along with market orientation, the notion of the customer value proposition (CVP) is widely embraced in both the practitioner- and academic marketing literatures. We follow the Payne et al. (2017) conceptualization of CVP as a strategic device enabling the enunciation of an organization's ability to share resources and provide a better and differentiated value to the market it serves. Whether or not it forms a part of the general language in corporate environments on a widespread level is less apparent. While many firms espouse a CVP, far fewer firms explicitly articulate a CVP and communicate it externally and even internally. Moreover, for a term so widely used in the literature, many of the effects of its incorporation into overall corporate strategy are largely unexplored and undocumented, particularly in B2B markets. In simple terms, an important question is this: Is giving serious attention to the crafting and incorporation of a statement of CVP in a firm's strategy significantly related to important outcomes such as future financial performance, brand value, and promotional expenditures? There is a paucity of empirical research in the area of CVP (Payne et al. (2017), particularly in the B2B arena. Since a CVP is central to marketing and difficult to measure, we have devised a novel (albeit imperfect) approach to not only measure CVP, but to link it to other outcomes. We proceed as follows: First we provide a brief review of the extant literature on CVPs, with particular emphasis on the B2B context. This permits the formulation of a number of performance related

Corresponding author at: Beedie School of Business, Simon Fraser University, 500 Granville St., Vancouver V6C 1W6, Canada. E-mail addresses: [email protected] (S. Mishra), [email protected] (M.T. Ewing), [email protected] (L.F. Pitt).

https://doi.org/10.1016/j.indmarman.2019.10.005 Received 29 March 2019; Received in revised form 24 September 2019; Accepted 1 October 2019 0019-8501/ © 2019 Elsevier Inc. All rights reserved.

Please cite this article as: Sagarika Mishra, Michael T. Ewing and Leyland F. Pitt, Industrial Marketing Management, https://doi.org/10.1016/j.indmarman.2019.10.005

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strategic importance of the CVP, grounded in the resource-based view of the firm (Barney, 1991; Wernerfelt, 1984). The antecedents in this framework are first, firm-based resources (including leadership support for the CVP, formalized structures and structures for the crafting of the CVP, and extensive offering (product or service) knowledge. Second, there are market-based resources, which include market knowledge (knowing customers and competitors), innovation (finding new ways to solve customer problems), customer relationships, and brand reputation (a pledge that binds the firm to the CVP). These firm- and marketbased resources are the antecedents to strategy decisions, which incorporate the CVP itself and its design characteristics (including its explicitness, granularity and focus). The consequences of these strategic decisions are twofold: For the firm, the CVP implements market orientation and provides guidance and a sense of purpose. For customers, the CVP augments perceptions of value and enables their judgment certainty, thereby giving the firm a competitive advantage. The authors develop a number of research propositions based on this framework, some of which formed the basis for hypotheses formulated for investigation in the study reported here.

hypotheses. Next, we describe a study that employed textual analysis of the corporate communications of a large sample of B2B firms to determine whether what these firms were communicating about CVP was related to aspects of firm performance, brand value and promotional expenditures. The results are presented and discussed. The paper concludes by drawing the managerial implications from the results, acknowledging the limitations of the approach and identifying avenues for future research. 2. Literature review As Payne et al. (2017) point out in their review of the CVP literature, the concept has developed over more than a hundred years, albeit under different names. These have ranged from the simple notions of a “proposition” in advertising (e.g. Starch, 1914), through the wellknown “unique selling proposition” or “USP” (Reeves, 1961), to the “emotional selling proposition” or “ESP” (e.g. Tuck, 1976), to the “core benefits proposition” in the early 1980s (Urban & Hauser, 1980). At the heart of all these propositions is the philosophy that in order for a firm to excel in its chosen market, it needs to promise the customer something that is different, in a way that they value and would be prepared to pay for. B2B marketing scholars have recently begun to acknowledge the CVP, mostly in the context of service-dominant logic (Vargo & Lusch, 2004), with its focus on value co-creation (e.g. Frow, McColl-Kennedy, & Payne, 2016; Kohtamäki & Rajala, 2016; Patala et al., 2016). Truong, Simmons, and Palmer (2012) argue that the value proposition concept has been treated ambiguously, and that its application and implementation have not been studied extensively in practice. Their work explores how reciprocal value propositions are developed in a digital market setting, using a series of in-depth interviews with marketing executives. Interorganizational management accounting provided a lens through which Wouters and Kirchberger (2015) investigated the potential of placing a financial worth on the customer “value” proposition that B2B customers would receive from the offerings of their suppliers. These authors conducted case studies in three new technology-based firms in order to derive actual monetary value perceptions of the customers of these firms. However, Baumann, Le MeunierFitzHugh, and Wilson (2017) caution that while both buyer and seller might enunciate value propositions, there are frequently differences in the value dimensions articulated by each. After conducting > 30 indepth interviews with both buyers and sellers, they found that while the customer's proposition of value might be sought by the seller, the value proposed by the seller might not always accord with that desired by the buyer. The consequences of this in a B2B setting can be seriously disadvantageous to the marketer. The work summarized has either been conceptual, or has been qualitative in nature. While qualitative research provides the depth, context and richness that the researcher might be seeking, it does not enable the generalization that work with large samples provides. This paper seeks to enable a more general view of the consequences of articulated customer value propositions by utilizing an extremely large dataset. The CVP has often been confused with other managerial concepts according to Payne et al. (2017), including positioning, business models and value discipline. Noting that the notion has also never been really well defined, these authors suggest viewing the CVP as a strategic tool that enables an organization to communicate its ability to share resources and offer superior value to its chosen market. They also argue that much of the literature on CVPs focuses on the supplier's side, and tends to overlook the customer's contribution to the value creation process, although the recent work in B2B markets referred to above has certainly attempted to redress this. Their paper includes illustrations of the CVPs of major international firms including Uber, Google, and the B2B firms Rio Tinto and PricewaterhouseCoopers. Payne, Frow and Eggert (PFE) (2017) then go on to construct a conceptual framework that permits a greater appreciation of the

3. Hypothesis development PFE (2017) in their P3 articulate that a CVP can have a positive impact on a B2B firm's market orientation and employee's attitudes and behaviors, as well as on physical resource acquisition and deployment. We extend this in two ways. First, we contend that not only would a CVP guide a firm in its decisions on physical resource acquisition and deployment, it would also direct a firm's spending on intangible assets such as knowledge capital, patents and software, all of which represent investments in the firm's brand. Second, there has been significant recent interest in the marketing literature in the notion of stakeholder brand engagement (e.g. Baldus, Voorhees, & Calantone, 2015; Brodie, Hollebeek, Jurić, & Ilić, 2011; Hollebeek, 2011; Hollebeek, Glynn, & Brodie, 2014). The emphasis is on stakeholders, for while customers are obviously the target of most brand engagement strategies, Kumar and Pansari (2014, 2015, 2016) admonish that engaging other stakeholders, including suppliers, investors and employees (e.g. Pitt, Plangger, Botha, Kietzmann, & Pitt, 2017) is critical too. Kowalkowski, Kindström, and Carlborg (2016) consider relationships among actors in a manufacturer–dealer–user triad, and argue for the development of a triadic value proposition over time. As this value proposition, articulated by all three members of the triad, evolves over time, the network ties as well as the interdependence among the members of the triad, strengthen to the advantage of all. Therefore, B2B firms that focus explicitly on their CVP could find it not only impacting their market orientation and their acquisition and deployment of physical resources, but also their investment in intangible assets such as networks and brand engagement strategies. One way of gauging this effect empirically would be to resort to the small sample qualitative studies referenced above, in which strategies are enunciated, and their effects reported. Another way would be to determine to what extent a very large sample of B2B firms are actually saying in terms of CVPs, and to gauge the impact of this on their actual investment in brands. This would obviously require the researcher first, to obtain a hard measure of the extent to which firms were articulating CVP or not, and second, to obtain hard measures of investment in brands and brand relationships. We therefore hypothesize that: H1. B2B firms with a higher articulation of CVP will make higher brand related investments. In their P4, PFE (2017) contend that customers' value perceptions and subsequent satisfaction levels are favorably shaped by CVPs. This is because customer expectations are effectively shaped, and the superior benefits afforded by the supplier are made manifest (Eggert & Ulaga, 2002). A clearly articulated CVP will make it clear to customers what they will receive, and according to some scholars (e.g. 2

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Accounting scholars have also used10-K reports as the primary data sources to explore a range of issues. For example, Gamble, Hsu, Kite, and Radtke (1995) conducted a longitudinal study of the quality of environmental disclosures among firms (such as petroleum refineries) whose operations could have devastating environmental impacts. While their time period studied was relatively short (the 5 years between 1986 and 1991), these authors found that environmental information increased significantly after 1989, although the overall quality of these disclosures remained low. In the area of operations management, Lee and Hong (2016) text-mined 10-K reports and used the information on corporate operating segments to identify service portfolios and thus detect the servitization trends within various industries; which can aid service development planning. We constructed the CVP variable by searching for 5 CVP related words or terms, namely “value proposition(s)”, “value promise(s)”, “value to/for customer(s)”, and “value for/to user(s)” in all the 10-Ks filed for the entire sample period. These terms were derived from some of the marketing literature on customer value propositions, making a list of 10 of these terms/words that occurred frequently and then requesting three independent, skilled marketing academics to simply decide whether these terms/words pertained to customer value proposition or not. Only these five word/terms were agreed to by all three judges. The appearance of any one or more of these terms/words in a 10-K report for a particular firm would contribute toward its overall CVP score. Since our CVP measure is annual, we used annual data to conduct the analysis. We collected data on firm characteristics from COMPUSTAT and provide details about the construction of the CVP and brand capital variable in the next section. The final sample was for around 12,000 firm-year observations. We provide the details of the variables and the SCI categories used in this paper in Appendix A 1.

Chandrashekaran, Rotte, Tax, & Grewal, 2007; Park, MacInnis, Priester, Eisingerich, & Iacobucci, 2010) this will reinforce positive customer attitudes, as well as commitment to the supplier firm (Ulaga & Eggert, 2006a, 2006b). In their P7 (and related to H1 above), PFE (2017) also argue that brand reputation and customer relationships strengthen the impact of CVPs on customers. We submit that if this were done effectively a B2B firm would need to spend less on advertising and promotion. Stated differently, if a B2B firm successfully articulates a CVP over the long-term, and this CVP is well understood and retained by its customers, the firm would need to make small advertising and promotional investments in an effort to sway customers. We therefore hypothesize that: H2. B2B firms with a higher articulation of CVP will invest less in advertising and promotion. In terms of the relationship between the articulation of a CVP by top management and the performance of the firm, PFE (2017) do not make a specific research proposition, although they do suggest this indirectly: “…CVPs enhance firm's competitive advantage, which is the proximate reason for superior performance… (p. 477)”. This harks back to early work by Day and Wensley (1988) for example, in which it was argued that one of the outcomes of a process of competitive advantage, achieved through either of Porter's generic positions of competition, namely low cost or differentiation, would be superior firm performance. Because, as already referred to under H1 and H2 B2B firms with a higher articulation of CVP will make the investments in brands that sustain their superiority and therefore need to invest less in advertising and promotion, we also suspect that there may also be a direct positive impact on the performance of these firms in terms of sales, sales per customer and number of customers. We therefore hypothesize as follows:

4.1. Measures of intangible and brand investment

H3. B2B firms with a higher articulation of CVP will also enjoy better future performance as measured by sales, sales per customer and number of customers.

We followed Peters and Taylor (2017) in our measuring of intangible investment. Intangible assets created within the firm are normally expensed in the income statement. For example, firms' investment in knowledge capital, patents and software is expensed as research and development (R&D). Advertising expenditures are regarded as a selling expense under selling and general administrative (SGA). Employee training (to build human capital) is also general and an administrative expense within SGA. There are a few intangibles that are created within the firm that are considered as assets on the balance sheet. These include blueprints or building designs, copyrights, covenants not to compete, design costs, distribution rights and agreements, engineering drawings, excess of cost or premium of acquisition, franchise and franchise fees, goodwill and import quotas. However, the dollar value of these intangibles is very low when compared to the dollar amount spend in SGA and R&D. Following Peters and Taylor (2017) we constructed intangible investment by aggregating the R&D, 30% of SGA and the intangible components. When firms report SGA in the income statement, they normally report these numbers after adding the R&D expenses to SGA expenses. First, we subtracted R&D from SGA and then took 30% of SGA into the calculation. The reason we took only 30% of SGA is because it is argued in the finance and marketing literature (Eisfeldt & Papanikolaou, 2014; Hulten & Hao, 2008; Zhang, 2014) that at least part of SGA represents an investment in organizational capital through advertising, spending on distribution systems, employee training, and payments to strategy consultants. Indeed, a recent study by Ptok, Jindal, and Reinartz (2018) confirms that a small component of SGA belongs to marketing spend. Similarly, in the marketing literature, Kurt and Hulland (2013), follow Mizik and Jacobson (2007) and Luo (2009), in using S&GA expenditure minus R&D expenditure as a measure of a firm's marketing expenditure intensity. Prior literature has also validated the measure in several ways. It shows a positive correlation between firms' use of brand capital (it is also called organizational capital)

To test these hypotheses, we measured the articulation of CVP by B2B firms in a very large database, and gauged their investment in brands, their spending on advertising and promotion, and their future financial performance from the same database. In the next section we describe the dataset employed in this study. 4. Data We collected our data from two different sources: EDGAR and COMPUSTAT. To gauge articulation of CVP in B2B firms, we downloaded all the 10-K filings, excluding amended documents, from the SEC's Electronic Data Gathering, Analysis, and Retrieval (EDGAR) website (www.sec.gov) filed for the period 2004–2017. A 10-K is an annual filing that publicly traded companies in the USA are legally required to send to the Securities and Exchange Commission that gives a comprehensive summary of a company's financial performance. The form will also include information such as the company's history, organizational structure, executive compensation, equity, subsidiaries, and other facts that the firm may wish to disclose. 10-K filings have been studied in business disciplines by a large number of authors using text analysis to determine what they communicate. In the area of finance for example, Loughran and McDonald (2011) developed word lists which they then linked to 10-K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings. More recently these authors studied requests for 10-K reports immediately after filing and found that there was a very low request rate for this information by investors, suggesting that the majority of stakeholders do not use this document in stock research (Loughran & McDonald, 2017). Karapandza (2016) used text analysis of verbs in 10-K reports to show that firms that talk less about the future in these communications generate positive and abnormal returns. 3

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4.2.2. Stage 2 text analysis: generating the CVP variable from the raw text of the 10Ks We followed Bodnaruk, Loughran, and Mcdonald (2015) closely to parse the raw text files. We then constructed our CVP variable - using a custom dictionary comprising the 5 phrases mentioned in the data section. We searched for the frequency of the CVP related words in all the parsed 10-K filings. We used RIOT SCAN software for the second stage of our text analysis. We also counted the total number of words used in the annual reports. Finally we calculated the number of words that belonged to the CVP list of words as a percentage of the total number of words. We subsequently used this measure of CVP in the further analysis. For example, if a firm had 40,000 words in its annual report for the year 2016, and the annual report had 76 phrases that define CVP, then for that year that firm would have a value of 76/40, 000 or 0.19 for the CVP measure.

and the Bloom and Van Reenen (2007) managerial quality score. This score is associated with higher firm profitability, production efficiency, and productivity of information technology (IT) (Bloom, Sadun, & Van Reenen, 2010). Eisfeldt and Papanikolaou (2014) show that firms using more brand capital are more productive after accounting for physical capital and labor, spend more on IT, and employ higher skilled workers. They show that firms with more brand capital list the loss of key personnel as a risk factor more often in their 10-K filings. Practitioners also use this approach. A popular textbook on value investing recommends capitalizing SG&A to measure assets missing from the balance sheet (Greenwald, Kahn, Sonkin, & Van Biema, 2004).

4.2. A text based measure of CVP In this section we describe how we generated the text-based measure of CVP. First, we downloaded all raw text 10-K filings from the EDGAR website (www.sec.gov), filed for the period of 2004–2017. We did not include any amended filings or any 10K variants (for example, 10K/A, 10K-405, 10KSB and 10KSB40) in our analysis. Our focus was restricted to the annual reports of the firms.

5. Empirical models In order to test H1 and H2 we estimated the following OLS model:

Invit + 1 = α 0 + βCVPit + α2 Sizeit + α3 Levit + α 4 Growth it + +α5 Liquidityit + α 7 Riskit + α 9 Competitionit +

4.2.1. Stage 1 text analysis: parsing annual reports The raw text version of the 10K filings provided on the SEC Edgar is an aggregation of all information such as HTML, XBRL and ASCII coded graphics. The aggregation of all these files makes the size of the filing very large, which can make it very difficult to analyze the text. Bodnaruk, Loughran and McDonald (2015) for example, describe IBM's 10-K filing for 2012 in detail, and explain how only 7.6% of the data in the file is actually usable text for content analysis purposes. By parsing these files from the raw text files it becomes easier to conduct textual analysis on them. For example, the size of the raw text files downloaded from EDGAR varies from a few megabytes to a few gigabytes. However, after we parsed out the XBRL, ASCII encoding, exhibits and graphics the size of the files was reduced to a few kilobytes. We parsed the original text files downloaded from EDGAR using the following sequence (see Loughran & McDonald, 2011; Loughran & McDonald, 2015): First, we removed all the ASCII encoded segments such as < TYPE > tags of graphic, zip, excel and pdf from the files. The purpose of ASCII encoding is to convert binary data files to plain ASCIIprintable characters, to ensure that the data is readable across different platforms. However, this conversion from binary to plain text increases the size of the original file significantly. Next, we removed < DIV > , < TR > , < TD > , and < FONT > tags. These tags are part of a table definition. Then we removed all text that appeared between < XBRL... > ... < /XBRL > , since XBRL allows the expression of semantic meaning commonly required for business reporting. From our analysis perspective this would have been non-textual content. Then we removed SEC headers and footers. In addition, the footer “—–END PRIVACY-ENHANCED MESSAGE—–” appearing at the end of each document was deleted. Then we removed all text that appeared between < TABLE > and < /TABLE > tags. We also removed all remaining mark-up tags (i.e, < ... >). We re-encoded reserved HTML characters. For example, we used LT for “<” GT instead of “>”, “”” instead of “"” etc. There are some idiosyncratic anomalies that were parsed out: for example line feeds (\n) following hyphens were parsed out, hyphens preceded and followed by a blank space were removed, the token “and/or” (case insensitive) was replaced by “and or” etc. Further we deleted SEC headers, hyphens preceding a line feed, replaced hyphens preceding a capitalized letter with a space, deleted names and unambiguous proper nouns, deleted capitalized or all capitals for March, May, and August, deleted possessive “s”, removed the phrase “Table of Contents”, and removed page numbers. We then parsed the remaining text in each filing into words and counts were created for CVP mentions.

∑ δk Yeark + εit+τ k

(1)

In Eq. (1) the dependent variable is future (t + 1) investments. For investments we used total intangible investment, 30% SGA or advertising expenses. Our main independent variable is CVPit, the textual measure of CVP. We controlled for a range of firm characteristics that could affect investment. Sizeit is a natural logarithm of total assets, Levit is long term debt scaled by total asset, Growthit measures the growth opportunity of the firm gauged by the ratio of market value of equity to book value of equity. In this model Liquidityit is measured by operating cash flow scaled by total assets. Riskit is the rolling standard deviation of earnings per share over the last 4 years, Competitionit is a Herfindahl Index (HHI) measure of market competition. We also included year fixed effect in all our regressions, as well as robust standard errors. We did not include any industry effects because we only focused on industries that are B2B. We winsorized all continuous variables above (below) the 99th (1st) percentiles of their distributions, to mitigate the effect of potential outliers. We provide the detailed definition of all variables used in our analysis in the variable A in which we also provide a list of industries that we used in our analysis based on Fama and French (1997). To test H3 we estimate the following model:

Performanceit + 1 = α 0 + α1 CVPit + α2 Sizeit + α3 Levit + α4 MTBit + +α5 Liquidityit + α 6 Tangibleit + α 7 Riskit + α8 Profitabilityit + α9 Competitionit + α10 Intangibleit

∑ γj Indj + ∑ δk Yeark + εit+τ j

k

(2)

The dependent variable is for different measures of firm performance. These are sales, sales per customer and number of customers. Intangible investment is based on the Peters and Taylor (2017) part. Intanit+τ is the sum of change in other intangibles, 30% of selling and general administrative expense and research and development expense scaled by total assets. The other variables are defined as per Eq. (1). Tangibleit is the tangible investment measured by the ratio of property, plant and equipment scaled by total assets. 5.1. Empirical analysis In Fig. 1 we show the extent to which firms have emphasized CVP in their annual reports over the years. We plot a time series mean of CVP for all the B2B firms for the period 2004 to 2017. The Y-axis shows the 4

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Time Series mean of CVP 0.25 0.2 0.15 0.1 0.05 0

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Fig. 1. Time series mean of CVP for Business to Business Firms for the period from 2004 to 2017.

percentage of words related to CVP out of the total words in the annual report and the X-axis shows calendar years. We observe an upward trend in the value for CVP, which suggests that firms are emphasizing CVP to a greater extent, although we also observe marginal decline for CVP during the period of 2009 and 2010, perhaps due to the effects of the global financial crisis being felt at the time. In Table 1 we present the descriptive statistics of all the variables in our sample. The number of observations for each variable is different due to some missing values in the variables. Variables are either scaled by total assets or natural log. The mean (median) value of CVP is 0.20 (0.19). The 1 year ahead mean (median) sales is 0.96 (0.78), and 1 year ahead sales per customer 4.63 (4.76). The 1 year ahead natural log of number of customers is 1.59 (1.60), and the mean (median) brand related investment is 0.07 (0.04). In Table 2 we present the results for H1 and H2. For brand related investment we use 30% of SGA after subtracting research and development expenses from SGA, based on prior literature. For promotional investment we used advertising. Advertising expenses cover the cost of advertising in the media such as radio, television and periodicals and promotional expenses. Although advertising expenses are a component of SG&A expenses, SG&A also includes commissions and marketing expenses (Standard and Poor's 2013). They are therefore broader than mere advertising expenditures. We also used total intangible investment for the firm. The total intangible investment includes 30% SGA, research and development expenses and change in other intangible investment from Compustat. After controlling for other variables that

Table 2 Effect of CVP on marketing related investments.

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Risk HHI Constant Observations Year effect Adjusted R2

N

P25

Mean

Median

P75

SD

CVP 1 year ahead ADV 1 year ahead 30% of SGA 1 year ahead Sales 1 year ahead sales per customer Natural log of No of (1 year ahead) customers Liquidity Size Lev MTB Risk HHI Tangible investment Intangible investment

39,140 36,806 36,806 36,432 33,169

0.144 0.000 0.012 0.418 3.104

0.200 0.009 0.074 0.967 4.637

0.192 0.000 0.042 0.783 4.762

0.246 0.003 0.089 1.291 6.250

0.078 0.027 0.489 0.774 2.301

33,554

1.099

1.597

1.609

2.079

0.669

38,543 38,944 38,745 35,917 36,438 39,140 37,717 38,817

0.017 4.622 0.017 0.009 0.265 0.040 0.154 0.016

0.037 6.217 0.224 0.132 1.071 0.179 0.483 0.128

0.071 6.271 0.189 0.028 0.546 0.071 0.350 0.084

0.120 7.816 0.356 0.091 1.139 0.212 0.741 0.185

0.182 2.240 0.212 0.377 1.696 0.234 0.414 0.162

(2)

Intang (t + 1)

ADV (t + 1)

−0.0572 (0.596) −0.0159⁎⁎ (0.033) −0.0328 (0.687) −0.0595 (0.699) −0.347⁎⁎⁎ (0.000) −0.00796⁎⁎ (0.013) −0.0377⁎⁎ (0.033) 0.275⁎⁎⁎ (0.000) 12,760 Y 0.005

(3)

⁎⁎⁎

−0.00979 (0.000) −0.000572⁎⁎⁎ (0.000) −0.00192⁎⁎ (0.035) 0.00137⁎ (0.091) −0.000380 (0.764) −0.0000432 (0.631) 0.00190⁎⁎ (0.004) 0.0107⁎⁎⁎ (0.000) 12,760 Y 0.014

30%of SGA (t + 1) 0.117⁎⁎⁎ (0.000) −0.0168⁎⁎⁎ (0.000) 0.0874⁎ (0.051) 0.0361 (0.154) 0.0149 (0.658) −0.00229⁎⁎⁎ (0.000) 0.0132⁎⁎ (0.001) 0.115⁎⁎⁎ (0.000) 12,760 Y 0.036

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

can affect total intangible investment, CVP does not have any effect on total intangible investment but has a positive effect on brand related investment (30% SGA). This means that B2B firms that emphasize CVP invest more in brand building. We also find that CVP has a negative effect on promotional investment (advertising expenses). This suggests that B2B firms that place a higher emphasis on CVP are able to reduce their expenditure on advertising because customers, as discussed above, understand and retain the articulated CVP. In Table 3 we present the results for the role of CVP in driving future firm performance. For the performance measure we used sales scaled by total assets, sales (scaled by total assets) per customer and the natural log of number of customers. We find that after controlling for other factors, CVP has a positive effect on future sales and sales per customer, which implies that CVP has a positive effect on firm performance. However, we did not find any effect of CVP on number of customers. A possible explanation for this might be that firms that emphasize CVP probably focus more on attracting loyal customers and building long term relationships with existing customers. This also corroborates the

Table 1 Descriptive statistics of our sample. Variables

(1)

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Table 3 Effect of CVP on firm performance. (1)

(2)

(3)

Sales (t + 1)

Sales per customer (t + 1)

No of customer (t + 1)

0.691⁎⁎⁎ (0.000) 0.942⁎⁎⁎ (0.000) 0.327⁎⁎⁎ (0.000) 0.433⁎⁎⁎ (0.000) 2.296⁎⁎⁎ (0.000) −0.273⁎⁎⁎ (0.000) 0.768⁎⁎⁎ (0.000) 0.000960 (0.889) 0.465⁎⁎⁎ (0.000) −1.254⁎⁎⁎ (0.000) 11,558 Y 0.773

−0.110 (0.155) 0.0398⁎⁎⁎ (0.000) −0.0362 (0.276) −0.0166 (0.370) 0.0959⁎⁎ (0.002) −0.0553⁎⁎⁎ (0.000) −0.0895⁎⁎ (0.035) −0.00169⁎ (0.629) 0.146⁎⁎⁎ (0.000) 1.237⁎⁎⁎ (0.000) 11,592 Y 0.032

Table 4 Panel A: effect of CVP on firm performance during the GFC (2008–2010). Panel B: effect of CVP on brand investment during 2008–2010 global financial crisis. Panel A

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Tangible Intangible Risk HHI Constant Observations Industry effect Adjusted R2

0.210⁎⁎ (0.021) −0.0334⁎⁎⁎ (0.000) 0.291⁎⁎⁎ (0.000) 0.218⁎⁎⁎ (0.000) 1.149⁎⁎⁎ (0.000) −0.290⁎⁎⁎ (0.000) 0.325⁎⁎⁎ (0.000) 0.00908⁎⁎ (0.009) 0.552⁎⁎⁎ (0.000) 1.113⁎⁎⁎ (0.000) 12,701 Y 0.123

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Tangible Intangible Risk HHI Constant Observations Year effect Adjusted R2

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

(1)

(2)

(3)

Sales (t + 1)

Sales per customer (t + 1)

No of customers (t + 1)

−0.173 (0.347) −0.0192⁎ (0.056) 0.444⁎⁎⁎ (0.000) 0.204⁎⁎ (0.013) 0.969⁎⁎⁎ (0.000) −0.312⁎⁎⁎ (0.000) 0.465⁎⁎ (0.002) 0.00945 (0.229) 0.545⁎⁎⁎ (0.000) 1.074⁎⁎⁎ (0.000) 2450 Y 0.110

0.238 (0.431) 0.953⁎⁎⁎ (0.000) 0.702⁎⁎⁎ (0.000) 0.380⁎⁎⁎ (0.000) 1.912⁎⁎⁎ (0.000) −0.303⁎⁎⁎ (0.000) 0.707⁎⁎⁎ (0.001) −0.0115 (0.452) 0.412⁎⁎⁎ (0.000) −1.541⁎⁎⁎ (0.000) 2335 Y 0.765

−0.231 (0.162) 0.0382⁎⁎⁎ (0.000) −0.259⁎⁎⁎ (0.001) −0.0315 (0.420) 0.0568 (0.416) −0.0563⁎ (0.074) −0.172⁎ (0.082) 0.00666 (0.467) 0.130⁎⁎ (0.020) 1.443⁎⁎⁎ (0.000) 2340 Y 0.027

Panel B

observation discussed above that these firms would need to spend less on advertising to acquire customers, and instead emphasize customer retention that is reinforced by a clearly articulated and well-understood CVP. There are numerous factors that, to different degrees, potentially influence a firm's financial performance, brand investments, and promotional expenditure. For example, a firm's actual marketing, sales, and service activities would influence its sales performance to a far higher degree than the articulation of CVP in annual reports. Since in the existing analysis, we cannot claim causality, we have addressed this issue in two ways. First, we have used the 2008–2010 Global Financial Crisis (GFC) as an external shock for firms to understand the importance of CVP. There was a significant decline in investor (and customer) trust during this period, because of the recessionary conditions. Hence, we contend that during/after the GFC, firms had to emphasize their CVP more in order to win back customer and investor trust. We therefore reexamined the relationship between firm performance and CVP; and brand investment and CVP during the GFC. These results are presented in Table 4 below. Panel A of Table 4 shows the effect of CVP on firm performance during the 2008–2010 GFC. We do not find any significant effect of CVP on future sales, sales per customer and number of customers. This is not overly surprising - since during the crisis the performance of firms significantly deteriorated. In Panel B, we present the results for the effect of CVP on future brand investment and promotional investment. We find consistent results suggesting firms that emphasize CVP increase future brand investment and reduce promotional investment. This result is important and provides strong support for the role of CVP since we find the positive effect of CVP on brand related investment during the GFC when firms were cutting expenses and investment due to credit constraints (Campello, Graham, & Harvey, 2010). Second, there may be self-selection bias in our sample - suggesting that firms with higher CVP tend to invest more in brand capital. To address this issue, we use a propensity score matching approach to identify a sample of control firms that differ in CVP but do not differ on

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Tangible Intangible Risk HHI Constant Observations Year effect Adjusted R2

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

6

(1)

(2)

30%of SGA (t + 1)

ADV (t + 1)

0.0810⁎⁎ (0.009) −0.0121⁎⁎⁎ (0.000) 0.0894⁎⁎⁎ (0.000) 0.00827 (0.691) 0.122⁎⁎⁎ (0.000) −0.0211⁎⁎ (0.001) 0.186⁎⁎⁎ (0.000) 0.00139⁎ (0.080) 0.0275⁎⁎ (0.003) 0.0866⁎⁎⁎ (0.000) 2452 Y 0.151

−0.00706⁎⁎ (0.032) −0.000438⁎⁎ (0.008) 0.00832⁎⁎⁎ (0.001) 0.00258 (0.337) 0.00967⁎⁎⁎ (0.000) −0.00488⁎⁎⁎ (0.000) 0.0135⁎⁎⁎ (0.000) 0.0000106 (0.931) 0.00418⁎⁎ (0.013) 0.00701⁎⁎ (0.020) 2452 Y 0.046

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Table 5A T-test of mean difference of the observable characteristics for the treatment and control samples Variable

Treatment

Control

t-test of Mean Difference p-value

Size Leverage Growth opportunities Liquidity Tangible Risk HHI

6.014 0.201 0.114 0.033 0.515 1.131 0.193

6.046 0.202 0.117 0.028 0.513 1.133 0.192

0.423 0.672 0.656 0.192 0.837 0.934 0.909

Table 5C Effect of CVP on firm performance for a matched sample.

CVP(t) Size(t) Leverage(t) Growth opportunities

other observable characteristics. Specifically, we estimate the following logit model.

Liquidity Tangible

Hight Intangible

= α1 + α2 Sizeit + α3 Levit + α4 MTBit + +α5 Liquidityit + α 6

Risk

Tangibleit + α 7 Riskit + α8 Profitabilityit + α9 Competitionit + α10 Intangibleit +

∑ δk Yeark + εit+τ

HHI

(3)

k

Constant

In the equation above, Highit is a dummy variable equal to 1 if the firm has a higher value of CVP than the median of the distribution for the sample and 0 otherwise. We use all the control variables in our model. We also include a year fixed effect in the model. We formed our matched sample based on the propensity score generated by the equation above. For each firm with higher than median CVP value, we identify one control firm with the closest propensity score within a caliper of 0.001 from the sample that has lower than median CVP value. We use this approach following prior research (Rosenbaum & Rubin, 1983). In our matched sample we have 1940 firms where 970 come from the treatment sample and 970 from the control sample. To establish that our treatment firms and control firms are similar in other characteristics except for CVP, we provide a t-test of mean difference of the observable characteristics for the treatment and control sample in Table 5A. The mean values of the control variables for the treatment and control sample are similar.

Observations Year effect Adjusted R2

Size(t) Leverage(t) Growth opportunities Liquidity Tangible Risk HHI Constant Observations Year effect Adjusted R2

(2)

(3)

Sales(t + 1)

Sales per Customer(t + 1)

No of Customers(t + 1)

0.125 (0.227) −0.0285⁎⁎⁎ (0.000) 0.335⁎⁎⁎ (0.000) 0.178⁎⁎⁎ (0.000) 1.084⁎⁎⁎ (0.000) −0.330⁎⁎⁎ (0.000) 0.232⁎⁎ (0.005) 0.00886⁎ (0.054) 0.588⁎⁎⁎ (0.000) 1.127⁎⁎⁎ (0.000) 9173 Y 0.108

0.567⁎⁎⁎ (0.000) 0.945⁎⁎⁎ (0.000) 0.371⁎⁎⁎ (0.000) 0.329⁎⁎⁎ (0.000) 2.268⁎⁎⁎ (0.000) −0.306⁎⁎⁎ (0.000) 0.756⁎⁎⁎ (0.000) 0.00106 (0.899) 0.518⁎⁎⁎ (0.000) −1.241⁎⁎⁎ (0.000) 9174 Y 0.762

−0.0984 (0.247) 0.0394⁎⁎⁎ (0.000) −0.0529 (0.156) −0.0114 (0.627) 0.0790⁎⁎ (0.032) −0.0462⁎⁎ (0.004) −0.138⁎⁎ (0.005) −0.00110 (0.798) 0.126⁎⁎⁎ (0.000) 1.255⁎⁎⁎ (0.000) 9174 Y 0.028

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

In Table 5B, we present the result for the effect of CVP on brand related investment. Consistent with our expectation, we find that CVP has a positive effect on brand related investment and a negative effect on promotional expenses. This result further reinforces the overall positive effect of CVP on brand investment. In Table 5C, we present the result for the effect of CVP on firm performance – where we find that CVP has a positive effect on future sales per customer.

Table 5B Effect of CVP on brand investment for a matched sample.

CVP(t)

(1)

6. The role of CVP for different cross-sections of firms

(1)

(2)

30%of SGA (t + 1)

ADV (t + 1)

0.115⁎⁎⁎ (0.000) −0.0173⁎⁎⁎ (0.000) 0.103⁎⁎ (0.027) 0.0199 (0.463) −0.0285 (0.615) 0.00119 (0.939) −0.00264⁎⁎ (0.010) 0.0153⁎⁎⁎ (0.001) 0.116⁎⁎⁎ (0.000) 10,052 Y 0.039

−0.00985⁎⁎⁎ (0.000) −0.000567⁎⁎⁎ (0.000) 0.00159 (0.154) 0.00150 (0.124) 0.00209 (0.168) −0.00433⁎⁎⁎ (0.000) 0.000152⁎ (0.251) 0.00219⁎⁎ (0.003) 0.0119⁎⁎⁎ (0.000) 10,052 Y 0.021

In this section we report results for some additional analyses we conduct for different cross- sections of firms. First, we consider the effect of CVP on brand related investment for firms across different sizes. We divide firms into terciles based on their total assets. This is an important test since larger firms may have established their brand name in the market, so although they emphasize CVP, they do not have to increase their brand related investment. We present the results in Table 6. In the first column we present the results for small firms and in columns 2 and 3 we present the results for mid-sized and large firms. As per our expectations we see a larger coefficient of CVP articulation for small firms and a much smaller but significant effect for mid-sized and large firms. This suggests that small firms have probably not yet establish their brands to the same extent that mid-sized and larger firms have, so in order to create customer value they need to invest more in brands than firms who have already established themselves in the market. In the next set of analyses, we consider how the articulation of CVP affects future sales for firms of different sizes. We present the results in Table 7, which shows that articulation of CVP generates higher future sales for small firms than for mid-sized and large firms; indeed for large firms, articulation of CVP has a negative effect on future sales. One might speculate that as firms increase in size they reach a point where it is difficult to maintain a large base of customers, particularly where additional growth in the customer base may come from price-sensitive customers who are less concerned with an articulated CVP.

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001. 7

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Table 6 Effect of CVP on brand investment for firms of different size.

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Tangible Risk HHI Constant Observations Year effect Adjusted R2

(Small)

(Mid-Size)

(Large)

30%of SGA(t + 1)

30%of SGA(t + 1)

30%of SGA(t + 1)

0.219⁎⁎ (0.004) −0.0733⁎⁎⁎ (0.000) 0.247⁎⁎ (0.014) −0.0454 (0.304) 0.000293 (0.995) 0.0144 (0.546) −0.00214 (0.347) −0.00423 (0.683) 0.315⁎⁎⁎ (0.000) 4655 Y 0.056

0.0209⁎ (0.074) −0.00316⁎⁎ (0.049) 0.0140⁎⁎ (0.007) −0.00147 (0.919) 0.160⁎⁎⁎ (0.000) −0.0315⁎⁎⁎ (0.000) −0.00153⁎⁎ (0.001) 0.0165⁎⁎⁎ (0.000) 0.0622⁎⁎⁎ (0.000) 4232 Y 0.118

0.0245⁎⁎ (0.002) −0.00670⁎⁎⁎ (0.000) −0.00947⁎⁎ (0.007) 0.00104 (0.871) 0.0538⁎⁎⁎ (0.000) −0.0315⁎⁎⁎ (0.000) −0.000714⁎⁎⁎ (0.000) 0.00509⁎⁎ (0.030) 0.106⁎⁎⁎ (0.000) 3820 Y 0.218

Table 8 Effect of CVP on Firm Performance for firms having different level of market competition.

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Intangible Tangible Risk HHI Constant Observations Year effect Adjusted R2

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

Size(t) Leverage(t) Growth opportunities Liquidity Intangible Tangible Risk HHI Constant Observations Year effect Adjusted R2

(Medium)

(High)

Sales(t + 1)

Sales(t + 1)

Sales(t + 1)

0.595⁎⁎⁎ (0.000) −0.0474⁎⁎⁎ (0.000) 0.165⁎⁎⁎ (0.001) 0.147⁎⁎⁎ (0.000) 1.082⁎⁎⁎ (0.000) 0.829⁎⁎⁎ (0.000) 0.112⁎⁎⁎ (0.000) −0.0108⁎⁎ (0.012) 18.43⁎⁎⁎ (0.000) 0.223⁎⁎⁎ (0.000) 4142 Y 0.257

−0.871⁎⁎⁎ (0.000) −0.0417⁎⁎⁎ (0.000) 0.448⁎⁎⁎ (0.000) 0.257⁎⁎⁎ (0.000) 1.022⁎⁎⁎ (0.000) −0.101 (0.394) −0.611⁎⁎⁎ (0.000) 0.0318⁎⁎⁎ (0.000) −3.495⁎⁎⁎ (0.000) 1.984⁎⁎⁎ (0.000) 4468 Y 0.144

−0.142 (0.401) 0.0120 (0.217) 0.152⁎ (0.072) 0.208⁎⁎⁎ (0.000) 0.916⁎⁎⁎ (0.000) 0.438⁎⁎⁎ (0.001) −0.185⁎⁎⁎ (0.000) 0.00889 (0.207) 0.396⁎⁎⁎ (0.000) 1.029⁎⁎⁎ (0.000) 4091 Y 0.060

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

Table 7 Effect of CVP on firm performance for firms of different size.

CVP(t)

(Low)

(Small)

(Mid-Sized)

(Large)

Sales(t + 1)

Sales(t + 1)

Sales(t + 1)

0.526⁎⁎ (0.001) −0.101⁎⁎⁎ (0.000) 0.783⁎⁎⁎ (0.000) 0.0825⁎⁎ (0.018) 1.461⁎⁎⁎ (0.000) 1.070⁎⁎⁎ (0.000) −0.124⁎⁎⁎ (0.000) 0.00714 (0.342) 0.382⁎⁎⁎ (0.000) 1.126⁎⁎⁎ (0.000) 4653 Y 0.222

0.286⁎⁎ (0.038) 0.0288 (0.189) 0.314⁎⁎⁎ (0.000) 0.169 (0.265) 1.058⁎⁎⁎ (0.000) −0.387⁎⁎⁎ (0.000) −0.341⁎⁎⁎ (0.000) 0.0129⁎⁎ (0.044) 0.475⁎⁎⁎ (0.000) 0.860⁎⁎⁎ (0.000) 4228 Y 0.085

−0.649⁎⁎⁎ (0.000) −0.0736⁎⁎⁎ (0.000) −0.971⁎⁎⁎ (0.000) 0.276 (0.248) −0.658⁎⁎⁎ (0.000) −0.823⁎⁎⁎ (0.000) −0.502⁎⁎⁎ (0.000) 0.00591 (0.214)⁎ 0.737⁎⁎⁎ (0.000) 2.259⁎⁎⁎ (0.000) 3820 Y 0.237

Table 9 Effect of CVP on brand investment for different levels of market competition.

CVP(t) Size(t) Leverage(t) Growth opportunities Liquidity Risk HHI Constant Observations Year effect Adjusted R2

(Low)

(Medium)

(High)

30%of SGA(t + 1)

30%of SGA(t + 1)

30%of SGA(t + 1)

0.195⁎⁎ (0.001) −0.0185⁎⁎⁎ (0.000) 0.124⁎⁎ (0.047) 0.0197 (0.486) 0.115⁎⁎⁎ (0.000) −0.00415⁎⁎⁎ (0.001) 2.832⁎⁎⁎ (0.000) 0.0192 (0.314) 4156 Y 0.046

−0.0513 (0.227) −0.00760⁎⁎ (0.003) −0.0501⁎⁎ (0.014) 0.105⁎⁎ (0.026) −0.133⁎⁎ (0.005) 0.00119 (0.230) −0.625⁎⁎⁎ (0.000) 0.178⁎⁎⁎ (0.000) 4498 Y 0.147

0.0993⁎⁎ (0.033) −0.0216⁎⁎ (0.008) 0.186⁎ (0.097) −0.0298 (0.624) −0.154 (0.205) −0.00316⁎⁎ (0.019) −0.0181 (0.223) 0.157⁎⁎⁎ (0.000) 4106 Y 0.048

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

p-values in parentheses. ⁎ p < .10. ⁎⁎ p < .05. ⁎⁎⁎ p < .001.

For firms facing medium levels of competition there is a negative effect of CVP on future sales, as shown in the second column of Table 8. In the case of firms facing high levels of market competition, articulation of CVP does not have any effect on sales. Finally, in Table 9, we consider how articulation of CVP can affect brand investment for firms facing different levels of market competition. Articulation of CVP has a higher effect on brand investment for

In the next set of analyses, we show how CVP affects firm performance for different levels of market competition. We divided firms into three groups based on their HHI. We present the results in Table 6. In the first column we show the results for firms facing the lowest level of market competition, and find that articulation of CVP has a larger effect on future sales for firms facing the lowest levels of market competition. 8

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firms facing lower levels of market competition. For firms facing medium levels of competition CVP do not have any effect, and for firms facing high levels of competition, there is a small but positive and significant effect of articulation of CVP on brand investment. This is most likely because to maintain their market share firms in highly competitive markets need to invest in brand to create and maintain customer value.

Rintamäki et al. (2007). We also contribute by showing how firms smaller in size and firms facing lower competition in the market reap the benefit of a CVP. Our findings complement work by Morgan (2012) who suggests that CVP enhances competitive advantage of firms, which is important for superior performance.

7. Discussion

Our findings point to a number of managerial actions for B2B firms. The results indicate positive links between the articulation of a CVP and important marketing and strategy variables including the building of brand equity, spending on promotion and firm performance. It does seem that when B2B firms think seriously about a CVP, and articulate this thinking and communicate it to external stakeholders, including customers, that this has positive effects. By implication this also suggests that B2B marketers should not only give serious attention to a CVP as an internal strategy driver, they should find as many ways as possible of communicating this to internal stakeholders such as employees, and external stakeholders such as customers, suppliers and investors. A wide array of media can be employed to achieve this, including internal manuals and intranets, and external media such as brochures, offering operating manuals, advertising, public relations, and the website and social media. The target markets of most B2B firms tend to consist of far smaller numbers of customers than those of B2C firms, so this communication can usually be far more finely targeted and nuanced. At the heart of these managerial actions of course lies a clear definition and subsequent articulation of the CVP. We hark back to the PFE (2017) definition of a CVP, and recommend that the CVP be viewed as a strategic tool that facilitates the communication of the organization's ability to share resources and offer a superior value package to targeted customers. In simple terms, the CVP should communicate clearly to the customers of B2B firms, who are usually price driven, what it is that the supplier offers that they value and should be prepared to pay for.

9. Managerial implications

One of the findings of the work presented here is that there is an increase over time in the articulation of CVP by B2B firms in their 10K reports, which suggests that over time firms are beginning to give greater strategic attention to the development and expression of a more explicit customer value proposition to external stakeholders. In this study we show how an articulation of CVP by B2B firms in their 10-K reports can affect firm performance and brand investment, and advertising spend. B2B firms who articulate CVP to a greater extent, enjoy higher sales overall as well as higher sales per customer, although a higher articulation of CVP is related to a lowering of customer base size. Our findings that articulation of CVP positively affects firm performance echo Payne and Frow's (2005) contention that CVP is crucial to the value creation process with significant performance implications. We find that firms with higher articulation of CVP attract a long-term customer base. This finding is in accordance with the theoretical propositions of both Terho, Haas, Eggert, and Ulaga (2012) and Ulaga and Eggert (2006b) who note that “suppliers need a detailed understanding of customers' business models, processes, and objectives to understand and articulate how their goods and services will affect customers' operations and create value-in-use” (p.24). A greater articulation of CVP by B2B firms in their 10-K reports is associated with higher brand investment by these firms, who also on average spend less on advertising and promotions. In that sense our finding supports the idea of CVP presented in prior literature (Lanning and Michaels (1988), Smith and Wheeler (2002), Rintamäki, Kuusela, and Mitronen (2007). We also found effects of CVP articulation related to firm size with regard to brand investment where it has a larger consequence for smaller firms, and firm performance where again it has a larger effect for smaller firms with regard to sales. The effects of CVP articulation also vary depending on the nature of the competitive situation in markets. These positive effects are most pronounced on sales and brand investment in markets where firms face lower levels of competition.

10. Limitations and avenues for future research Like all studies of a similar nature, this one is not without limitations. First, while the database used is extremely large, it only focuses on listed B2B companies in the US, and does not include unlisted firms, or firms outside of the US. Second, by focusing on 10-K reports we did not include any other verbal or written articulations of CVP by the firms concerned; we did not access any promotional materials of these firms, or any internal documents that might express or expound views on or stances toward CVP. Third, while we studied firms across all the B2B sectors that file 10-K reports, we did not conduct any industry level analysis, or make comparisons between firms in different industries. The importance or prevalence of an articulation of a CVP might indeed be higher for some industries than in others. This type of comparison might be interesting to pursue in future research. Finally, by its nature this study focused on the articulation of the CVP by the B2B firm, and not the interpretation or processing of this CVP by the B2B customer. As PFE (2017) argue, most of the literature focuses on how firms deliver value to customers, rather than any collaborative value creation by those customers. In this sense we are following a trend noted by Kowalkowski (2011) of being one-sided in stressing value that is predetermined by the firm, and ignoring the customer perspective, contrary to service-dominant logic (Vargo & Lusch, 2004). Another limitation is that firms may explicitly state their CVP but do not explicitly label this as such, or firms may implicitly enunciate a CVP but do not provide a CVP label to this. For both the cases, in our analysis, the firm will be scored as 0. This then to some extent over- or underestimates the coefficient we use for our CVP measure. However, we put forward the following argument: The terms used to denote CVP are simple words. Given that annual reports are non-technical in nature, firms should be using simple words to get the message across. Also since firms' customers understand and prize these value propositions, firms

8. Theoretical contributions Our study makes a number of theoretical contributions. Our study is the first attempt to identify a quantitative and novel measure, though imperfect, of CVP from firms' annual reports. We are hopeful that future research will refine our gauge of CVP and extract both implicit and explicit measures of CVP from firms' annual reports which can then be examined in the context of a business. Our study is the first to empirically examine the role of CVP on firm performance using 15 years of 10-K data for 2325 B2B firms. We find CVP positively affects future sales, sales per customer and helps build a long term customer base, which in turn impact business performance and success. This is an important contribution, because if CVP is a cornerstone of marketing strategy, then it is important to empirically determine whether CVP positively affects firm performance. Our research complements studies such as Payne et al. (2017) who have provided a theoretical exposition of CVP's role in firm performance. We also show that CVP positively affects brand investment and lower advertising expenses. This finding is robust even when firms are facing macroeconomic crises such as the GFC. This again underscores the importance of how CVP is positively associated with brand building. Our research complements the theoretical relationship between CVP and brand building proposed by Lanning and Michaels (1988), Smith and Wheeler (2002), and 9

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customers or corporate customers, or indeed any other customer clearly or groupings. It would therefore be worthwhile to determine whether the articulation of CVP by B2B firms differs in extent depending on the nature of the customer served. Finally, the observation in this research that articulation of CVP seems to vary over time is worthy of further investigation. Might articulation of CVP depend to some extent on whether the economy is in recession or not, and if so, why might that be? Finally, we believe that this paper has shown that 10-K reports offer a rich trove of data not only for finance and accounting scholars, but also for marketing scholars (along with their colleagues in strategy, management and operations who are already doing so) to explore. While 10-K reports area essentially technical in nature, they are still communication messages that firms send to stakeholders and in that sense are as much marketing messages as they are formal communications to the investment community. A textual analysis of the content of a longitudinal sample of 10-K reports would inform us of whether what firms communicate in them has changed over time. Automated text analysis stools such as LIWC (e.g. Chung & Pennebaker, 2012; Cohn, Mehl & Pennebaker, 2004) would be useful in this regard.

would like to use these terms to make it explicitly clear to their customers and investors. We chose 10K filings because this is the most common and most comprehensive reporting format for large firms. Prior literature has highlighted the importance of the management and discussion section of the annual report and how it is related to firm value. Further since 10-K filings are a mandatory requirement by the Securities Exchange Commission, the information provided in 10-Ks is more likely truthful and reliable. A number of new directions for research flow from this work. As far as we are aware, this is the first attempt to consider CVPs from a very large sample, and to examine the effects of an articulated CVP quantitatively; most empirical considerations of CVP in the past have used qualitative research tools such as focus groups, depth interviews and case studies. Whereas this research relied on textual data from 10-K reports, it would be worthwhile to consider other textual data in the form of corporate communication that B2B firms produce, including websites, corporate brochures and strategy documents. These could be analyzed in a similar manner to the approach followed in this study. Alternatively, there are a number of other automated text analysis tools (see Humphreys & Wang, 2017 for an overview) that can be used to shed light on marketing phenomena. These include dictionary-based tools that have been in other academic marketing research, such as WordStat (e.g. Pitt, Opoku, Hultman, Abratt, & Spyropoulou, 2007), DICTION (e.g. Pitt et al., 2017), Leximancer (e.g. Campbell, Pitt, Parent, & Berthon, 2011) and LIWC (e.g. Packard, Moore, & McFerran, 2018). Each of these software applications has unique features that provide greater insight into the words that individuals and groups in firms use, and could be used on the same dataset used here, or other text pertaining to CVPs. Recent developments in artificial intelligence (AI) have also given marketing scholars interesting and useful tools with which to analyze text such as that in the dataset used in this study. For example, IBM's Watson suite of AI applications enables researchers to identify the emotions (e.g. Pitt, Mulvey, & Kietzmann, 2018), personality and values expressed by the creator of a corpus of text. Data from both software- and AI-based text analysis can in turn be related to other variables of interest. It will also be noted that in the current research we did not distinguish between B2B firms that serve government

11. Conclusion In this study we show that B2B firms that emphasize CVP invest more in their brands and enjoy superior future sales performance. Using text analysis we searched for the terms that are associated with CVP in all US based B2B firms' annual reports for the period of 2004–2017. We also show that B2B firms articulation of CVP has a negative effect on their customer base. This is because firms that emphasize on CVP tend to attract long term loyal customers, those who really care about a CVP. We also find firms that care about CVP spend less on promotional expenditure such as advertising expenses. In a set of additional tests we show that small to medium sized firms have better future performance if they emphasize on CVP. Similarly we find small to medium sized firms invest more in brand capital if they emphasize on CVP. Further we show firms that face low level of competition have better performance and invest more in brand capital when they emphasize on CVP.

Appendix A 1. Definition of variables

Variable name

Construction

Sales CVP Size Intangible

Sales scaled by total assets Percentage of CVP words in 10-K filings Natural log of total asset (30% selling and general administrative expense + change in intangible expense from previous fiscal year + research and development expenditure) scaled by total assets. This measure is adopted from Peters and Taylor (2017) Short term debt plus long term debt scaled by total assets. Market value of equity to book value of equity. Market value of equity is end of fiscal year stock price multiplied by total number of share outstanding.

Leverage Growth opportunities Liquidity Tangible Risk HHI SGA ADV Sales per customer No of customers

Operating cash flow scaled by total assets Gross property plant and equipment scaled by total assets 4 year moving standard deviation of earnings per share. Herfindahl index. Measure of competition 30% selling and general administrative expense (after subtracting research and development expenses from SGA) scaled by total assets Advertising expense scaled by total assets Ratio of Sales scaled by total assets and number of customers Natural log of number of customers

Appendix A 2. List of business to business industries 1 Agriculture 12 Medical equipment 13 Pharmaceutical products; 14 Chemicals 15 Rubber and plastic products 16 Textiles; 17 Construction materials 10

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18 19 20 21 24 25 26 28 29 30 37 39 41

Construction Steel works etc Fabricated products; Machinery Aircraft Shipbuilding, railroad equipment Defence Metallic and industrial metal mining Coal Petroleum and natural gas Measuring and control equipment Shipping containers Wholesale

Appendix A 3. Appendix

Industry

Number of firms

Agriculture Medical equipment Pharmaceutical products Chemicals Rubber and plastic products Textiles Construction materials Construction Steel works etc Fabricated products Machinery Aircraft Shipbuilding, railroad equipment Defence Non-metallic and industrial metal mining Coal Petroleum and natural gas Measuring and control equipment Shipping containers Wholesale Total

26 246 573 143 53 20 108 68 74 12 189 31 13 11 32 26 342 110 16 230 2323

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Sagarika Mishra is a Senior Lecturer in the Department of the Finance, Deakin Business School. She completed her PhD (in Applied Economics) at Western Michigan University in 2008. Her research interests include Corporate Finance, Applied Time Series Analysis, Macroeconomics, Monetary Economics and Forecasting and she has published in The Accounting Review and the Journal of Banking and Finance (among others). Michael T. Ewing is Alfred Deakin Professor and Executive Dean of the Faculty of Business & Law at Deakin University (Australia). He received his doctorate from the University of Pretoria (South Africa). His research interests include marketing communications and brand management. He has published in the Journal of the Academy of Marketing Science, Information Systems Research, the International Journal of Research in Marketing, the Journal of Service Research and Social Science & Medicine (among others). Leyland F. Pitt is the Dennis F. Culver EMBA Alumni Chair of Business, Beedie School of Business, Simon Fraser University, Vancouver, Canada, and Distinguished Fellow, Hanken, Helsinki, Finland. His work has been accepted for publication in Journal of Advertising Research, Journal of Advertising, Information Systems Research, Journal of the Academy of Marketing Science, Industrial Marketing Management, Sloan Management Review, California Management Review, and MIS Quarterly (which he also served as Associate Editor).

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