The copycat CMO: firms' imitative behavior as an explanation for CMO presence

The present study adds to the CMO literature the perspective of firms’ imitative behavior on why firms have CMOs in their TMT. We propose that a firm’s decision to have a CMO on its TMT is driven not only by contingency-reated considerations but also by social ones, as the decision is significantly influenced by industry peers. Empirical findings based on 505 large US firms from 2000 to 2012 indicate that firms’ imitative behavior is a significant driver of CMO presence, especially when firm uncertainty is strong and inference uncertainty is low. Post hoc analyses indicate that this imitation behavior tends to be performance neutral at best.

Chief marketing officer; Imitation; Neoinstitutional theory; Herding; Uncertainty

Many firms have established functionally oriented top management teams (TMTs) on which the Chief Marketing Officer (CMO) represents the customers’ and market’s perspectives (Nath and Mahajan [69] ). The presence of the CMO is an important indicator of the marketing function’s influence at the corporate level, as the CMO can ensure that the function’s perspectives are considered in the TMT’s strategic decision making (Brown et al. [16] ; Wang et al. [88] ). However, CMOs are still underrepresented on TMTs (Hyde et al. [45] ), raising questions concerning what drives a firm to include a CMO on its TMT.

Nath and Mahajan ([69] ) argue that a firm’s decision to appoint a CMO is driven by contingency logics, such that a firm decides to have a CMO on its TMT if its structural, strategic, and environmental context calls for an influential and skilled marketing function. The authors find empirically that a firm’s differentiation, innovation, branding strategy, the TMT’s marketing experience, and whether the CEO is an outsider drive the CMO’s presence on the TMT. Kashmiri and Mahajan ([46] ) find that family-named family firms, as a kind of structural property, are more likely than other firms to have CMOs on their TMTs.

Nath and Mahajan ([69] ) also conclude that there may be other reasons for firms’ having CMOs and call for the CMO position to be studied from other theoretical perspectives. In response, we argue that another reason for firms’ installing CMOs may be that they perceive pressure to do so because their industry peers have done so—that is, that imitation contributes to CMOs’ presence on TMTs. The decision to have a CMO is a strategic choice that is subject to considerable public scrutiny and social pressure, both of which can lead firms to mimic the accepted behaviors in their environments (Shen and Cho [83] ). In addition, because the CMOs’ impact on firm performance has been unclear for a long time, decision makers are likely to address unanswered questions by imitating others (Abrahamson and Rosenkopf [4] ; DiMaggio and Powell [23] ). Practitioner-oriented publications disagree about the need for the CMO position, with some contributions claiming that the CMO’s strength on the TMT should be high and others sharply criticizing the CMO position (Kerin [48] ; McGovern and Quelch [60] ). The academic literature has not been clear either, which Boyd et al. ([14] ) illustrate by referring to the CMO as an “enigmatic creature” (p. 1147). Only recently do Germann et al. ([31] ) find that CMO presence robustly and positively impacts firm performance. This kind of uncertainty is likely to lead to imitative behavior as a failsafe.

In addition to Nath and Mahajan’s ([69] ) contingency logic, we draw on Abrahamson’s ([1] ) “fad perspective,” which combines neoinstitutional theory and herding models to argue that a firm’s decision to have a CMO on its TMT is influenced by the prevalence of the CMO position in its industry. We incorporate uncertainty into our research model as a key influencer of imitative behavior and argue that the extent of a firm’s imitative behavior depends on the type of uncertainty—firm, market, or inference—to which the firm is exposed. We validate our theoretical model empirically by means of secondary data from 505 large U.S. firms from 2000 to 2012.

Our research contributes to the literature in several ways. First, we contribute to the emerging research stream on CMOs. While controlling for structural, strategic, and environmental contingencies, we argue theoretically and validate empirically that CMO presence is also driven by imitation behavior. In this way, we inform the broader literature on functional TMT members which has also focused on contingency explanations for functional CxOs’ presence (Menz and Scheef [62] ; Roh et al. [78] ) and has called for rationales that support imitation as an explanation for the presence of particular TMT members (Menz [61] ).

Second, we contribute to the broader literature on the marketing organization. While extant studies in this area focus on optimal-fit perspectives (see Moorman and Day’s [67] extensive summary and Frösén et al. [27] for a recent empirical study), we introduce neoinstitutional and herding perspectives as explanations for marketing phenomena in the firm. Thus, we explain that firms’ choices of certain kinds of marketing organizations can be influenced by industry fads.

Third, we contribute to the marketing literature, which often examines uncertainty as a boundary factor (e.g., Feng et al. [26] ), by showing that uncertainty can have a variety of sources and that uncertainty’s impact can differ based on its source. We also inform the broader literature on institutional theory and herding models by establishing that uncertainty may strengthen or weaken a firm’s imitative behavior, depending on the type of uncertainty. In doing so, we challenge the widely held view that uncertainty always enhances a firm’s tendency to imitate (Strang and Still [84] ).

Theoretical background and hypotheses development Literature review on CMO research

We define the CMO as the executive on the TMT who is responsible for marketing-related activities. Nath and Mahajan’s ([69] ) study constitutes the starting point of the emerging large-scale empirical research on the CMO, which is outlined in Table 1. Research on the CMO in the marketing literature can be divided into three groups. The first group of studies, which is particularly relevant to our purposes, consists of two studies and examines what drives CMO presence in TMTs. Nath and Mahajan ([69] ) and Kashmiri and Mahajan ([46] ) find that structural, strategic, and environmental contingencies drive CMO presence. The second, larger group of studies uses CMO-related constructs to explain firm outcome variables. Some of these studies examine the relationship between CMO presence and various measures of firm performance (Boyd et al. [14] ; Germann et al. [31] ; Nath and Mahajan [69] ; Nath and Mahajan [70] ), while others link CMO characteristics (e.g., education) to firm-related outcomes (Homburg et al. [42] ; Wang et al. [88] ; Wang et al. [87] ), examine how CMO compensation is related to firm performance (Bansal et al. [8] ; Kim et al. [49] ), or consider the influence of CMO presence on marketing-related decisions (Boyd and Brown [13] ; Mintz and Currim [65] ). In the small third group of CMO-related studies in the marketing literature, which examines the CMO’s situation, Nath and Mahajan ([70] ) find that several contingencies impact the CMO’s influence in the TMT, Engelen et al. ([24] ) identify social capital as one of the drivers of CMO influence, and Nath and Mahajan ([71] ) identify drivers of CMO turnover.

Focusing now on the first group, which applies most closely to our purposes, we identify three additional empirical studies on what drives the presence of functional CxOs other than the CMO in the broader management literature. All three studies take a contingency perspective. Hambrick and Cannella ([33] ) use contingency logic to explain the presence of a Chief Operating Officer (COO) on the TMT, finding that firms with CEOs who have little or no experience in operational activities or in managing their particular firms are likely to have COOs. Menz and Scheef ([62] ) find that diversification, acquisition activity, and interdependent roles in the TMT impact the presence of a Chief Strategy Officer (CSO). Finally, Roh et al. ([78] ) use a contingency logic to explain the presence of Chief Supply Chain Officers (CSCO) and use empirical evidence to find that financial leverage, internationalization, and diversification drive CSCO presence.

Research conceptualization

Like Nath and Mahajan’s ([69] ) contingency perspective on the CMO position, all extant studies on the presence of other functional TMT members take a contingency perspective (Hambrick and Cannella [33] ; Menz and Scheef [62] ; Roh et al. [78] ). We add to this discussion the perspective that CMO presence on the TMT is driven by a firm’s imitation behaviors. We base this argumentation on two observations: The first is that the TMT is the decision-making apex of the firm, and its constituents represent the firm and its functional departments both internally and externally (Menz [61] ). It follows that TMT structures and changes therein are highly visible; therefore, when firms decide on their TMTs’ structures, they are under pressure to conform to other market actors’ expectations, so they adopt behaviors and decisions that they see as being commonly accepted. The second observation on which we base our argument is that firms may still perceive considerable ambiguity surrounding the performance consequences of CMOs. While some practitioners see the CMO as a key to success (Gilliatt and Cuming [32] ; Hyde et al. [45] ), others see the position as “dead” (Turpin [86] ). Two recent surveys show that the CMO position is under considerable pressure (Hoda [40] ; Moorman [66] ), and the academic literature has long offered a mixed account of CMOs’ performance consequences (Germann et al. [31] ; Nath and Mahajan [69] ). The imitation-behavior perspective posits that one way in which firms react to ambiguity concerning a practice’s performance impact is to model themselves on their industry peers (Abrahamson [1] ). Figure 1 illustrates the conceptual model of this research.Role of imitation pressure in CMO presence

Hypotheses CMO presence and imitation behavior

We employ Abrahamson’s ([1] ) “fad perspective,” which captures the logic from neoinstitutional theory and herding models to explain how social pressure leads to a firm’s imitating its peers in adopting a practice like putting a CMO on its TMT.

Neoinstitutional theory posits that firms are embedded in and affected by their environments, whose actors pressure them to resemble other organizations in the environment in order to gain legitimacy (DiMaggio and Powell [23] ; Meyer and Rowan [63] ). Legitimacy, defined as “a generalized perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definition” (Suchman [85] , p. 574), is key to firm survival, as external actors are more likely to supply needed resources to organizations that they consider legitimate (Meyer and Rowan [63] ; Parsons [75] ; Pfeffer and Salancik [76] ). Therefore, firms take care in building and protecting their legitimacy by adopting legitimizing practices (Suchman [85] ). As prevalence is one of the key drivers of a legitimate practice (DiMaggio and Powell [23] ), it follows that firms imitate practices that are prevalent among their peers to increase their legitimacy. We argue that a firm’s structural decision to have a CMO on its TMT can be the result of legitimacy-driven imitation, as the CMO position can be seen as a legitimizing structural practice. Structural practices serve as observable proxies for less visible legitimizing firm characteristics by signaling that firms pursue their goals with appropriate means and positioning in their environments (Meyer and Rowan [63] ). The literature links the CMO position to several favorable firm characteristics, including the firm’s market orientation and marketing capabilities (Feng et al. [25] ; Frösén et al. [27] ). The CMO position has also been related to the firm’s management of external stakeholders like customers and alliance partners (Boyd et al. [14] ; Krush et al. [51] ) and to strategic orientations that depend on identifying and exploiting market opportunities, clearly positioning the firm in its environment.

As for herding models, they posit that firms react to information asymmetry by following the “herd” in adopting a practice (Abrahamson and Rosenkopf [5] ). Variants of herding models highlight several reasons for this behavior, primary among them reputational herding and competitive herding. Reputational herding refers to the fear of fatal reputational repercussions from deviating from the consensus, while competitive herding refers to the fear of losing competitive positioning (Abrahamson and Rosenkopf [3] ). While the driver of reputational herding is “safety in numbers” (Palley [74] , p. 444), based on the thinking that “it is better to fail as part of the herd than to succeed as a deviant” (Hirshleifer and Teoh [39] , p. 42), competitive herding is a response to competitors’ moves. Imitation equalizes these moves, minimizing the possibility of falling behind (Ross and Sharapov [79] ). Two prerequisites for both kinds of herding are a positive indication of a practice’s value and considerable ambiguity still surrounding it. We propose that the presence of a CMO on the TMT can be the result of herding. Although the CMO’s direct performance impact has long been subject to discussion (Boyd et al. [14] ; Germann et al. [31] ), certain firm characteristics that the CMO represents, such as increased marketing capabilities and market orientation, are likely to be value-enhancing (Feng et al. [26] ; Frösén et al. [27] ; Morgan et al. [68] ). Empirical research provides evidence of this effect for both herding models (Basdeo et al. [9] ; Delios et al. [21] ; Head et al. [37] ).

Neoinstitutional theory and herding models suggest, then, that industry peers, especially the larger peers that are most visible to other players, are particularly important in a firm’s decision to imitate (Garcia-Pont and Nohria [30] ; Henisz and Delios [38] ; Xia et al. [91] ). Industry peers are a firm’s direct competitors for resources and a “competitive frame of reference” (Burt [17] p. 345) for the firm and other market actors, such as the media, governments, and financial stakeholders. Therefore, we argue that firms closely monitor their industry peers’ behavior and are particularly receptive to trends and changes in peer behavior (Lee and Pennings [52] ).

The greater the prevalence of the CMO position in a firm’s industry, the greater the likelihood that a firm will also have a CMO on its TMT.

Both neoinstitutional theory and herding models consider uncertainty to be the central influencing factor in firms’ imitative behaviors (Bikhchandani et al. [11] ; DiMaggio and Powell [23] ). To provide a comprehensive view of uncertainty that incorporates multiple levels of analysis, we consider the three types of uncertainty proposed by Gaba and Terlaak ([28] ): market uncertainty, firm uncertainty, and inference uncertainty.

Imitation behavior and market uncertainty

Market uncertainty stems from volatility in firms’ environments from unforeseeable variations in customers’ preferences, product demand, and/or competitor behavior (Feng et al. [26] ; Han et al. [34] ). We argue through neoinstitutional theory and herding models that market uncertainty increases imitation behavior.

From the perspective of neoinstitutional theory, the benefits of legitimacy are amplified in uncertain markets, so a firm’s inclination to imitate its peers’ practices, such as the presence of CMOs on their TMTs, should also be amplified in uncertain markets. In contrast to the technical value of adopting legitimizing practices, which value becomes unreliable in uncertain markets, the independence from market conditions of the social advantages of adopting legitimizing practices increases their attractiveness in the face of market uncertainty (Abrahamson and Rosenkopf [5] ). At the same time, performance as a measure of a firm’s condition is less reliable in uncertain markets than it is in stable ones, which leads market actors to place increased importance on social considerations like legitimacy (Scott [81] ). As a result, legitimate firms become significantly better positioned in their competition for resources than less legitimate firms are, which increases the likelihood that a firm will seek to increase its legitimacy by imitating other firms in having or not having a CMO.

As Huang et al.’s ([43] ) findings of increased herding in investment behaviors during the financial crisis indicate, the risk-avoiding behavioral logic of herding models is strengthened by market uncertainty because market uncertainty weakens the positive link between the quality of information and outcome certainty and amplifies the negative consequences of behavioral deviation (Ross and Sharapov [79] ). That is, market uncertainty reduces the value of a firm’s private information while increasing both the value of the social signal of majority behavior and the risk of deviating from the norm. It follows that the signal from reputational herding in regard to having a CMO is amplified because uncertainty about the relationship between a firm’s actions and their performance outcomes increases the attractiveness of following the herd. This notion is mirrored in Han et al.’s ([34] ) argument that in markets with high demand instability, managers pursue less risky decisions. Hence, competitive herding increases because imitation is the best way to maintain the firm’s reputation and avoid large deviations in performance from those of one’s peers (Lieberman and Asaba [55] ; Ross and Sharapov [79] ). Therefore:

Market uncertainty strengthens the positive relationship between the prevalence of the CMO position in a firm’s industry and the likelihood that a firm will also have a CMO.

Imitation behavior and firm uncertainty

We argue that firm uncertainty, as reflected in performance volatility, increases imitative behavior regarding CMO presence on the TMT. The neoinstitutional literature on the concept of legitimacy suggests that firms with high levels of firm uncertainty are more likely than other firms are to seek legitimizing behavior (Zimmerman and Zeitz [94] ). As such firms’ performance records do not recommend them in their competition for resources, they come to depend on the goodwill of those from whom they require support. Such firms must balance their lack of track record with other signals of desirability to increase their legitimacy (Suchman [85] ), which increases the likelihood of imitative behavior in terms of practices like naming a CMO to the TMT.

Herding models similarly suggest that firm uncertainty amplifies imitative behavior, as uncertainty increases the value of the information that can be inferred from others’ actions. In line with this argument, Kim and Pantzalis ([50] ) find that analyst herding is more likely to occur in regard to organizations that are difficult to track and monitor. From a reputational herding perspective, past firm uncertainty increases a firm’s tendency to imitate its peers’ decisions to have CMOs on their TMTs, as being similar to its peers can help the firm counteract reputational losses from the lack of a solid track record. From a competitive herding perspective, the small incentive to deviate from the consensus decreases in the face of firm uncertainty, as such uncertainty suggests that the firm’s private information on how to improve performance consistently is unreliable. Therefore:

Firm uncertainty strengthens the positive relationship between the prevalence of the CMO position in a firm’s industry and the likelihood that a firm will have a CMO.

Imitation behavior and inference uncertainty

Inference uncertainty stems from inconsistency in the information a firm infers from its peers’ behavior (Gaba and Terlaak [28] ). When there is a high level of inference uncertainty, the information gleaned from peer adopters of a practice and peers who reject the practice is about equal, so the firm must make an imitation decision based on conflicting observations.

From a neoinstitutional theory perspective, inference uncertainty regarding CMO presence weakens a firm’s imitative behaviors because inference uncertainty undermines the behavior’s legitimacy (Meyer and Scott [64] ). Rhee et al. ([77] ) study niche-width strategy imitation and find that, as the variance of strategic changes among a firm’s reference group increase, the likelihood that the firm will imitate a strategic change decreases. Therefore, inference uncertainty regarding a firm’s peers’ decisions to have CMOs on their TMTs decreases the firm’s confidence in the value and legitimacy of having a CMO, which decreases the likelihood of imitation.

In the herding model case that Bikhchandani et al. ([12] ) outline, actors disregard all information inferred if the number of previous adopters equals that of rejecters because the accuracy of the estimate the actor can make based on heterogeneous observations decreases (Hogarth [41] ). Therefore, both reputational and competitive herding regarding CMO presence declines when inference uncertainty is high. Therefore:

Inference uncertainty weakens the positive relationship between the prevalence of the CMO position in a firm’s industry and the likelihood that a firm will have a CMO.

Methodology Sample

The starting point of our sample generation was the 2013 Forbes Global 2000, which lists the largest companies worldwide. From this list we took the largest 510 U.S. firms that were also covered in Standard and Poor’s ExecuComp database from 2000 to 2012. This limitation to large firms increases the likelihood that the firms’ TMTs contain functional executives, as research shows that the roles of functional TMT members in small- and medium-sized companies are less clearly defined than they are in large organizations (Lubatkin et al. [57] ). Our limitation to large firms also increases the likelihood that detailed information on the executives and TMTs is available.

Since we want to use the panel nature of our data to determine the effects of the proportion of industry peers with CMOs on a firm’s decision to have a CMO on its TMT, our regression analyses include only firms for which we have observations for at least two years. Our dataset, generated using Standard & Poor’s COMPUSTAT and ExecuComp databases, consists of unbalanced data panels since continuous information on each firm for each observation year is not available in these databases. Our main data source, ExecuComp, reports the firms’ proxy statements (SEC form DEF14A), which include many TMT characteristics. Our final sample consists of 505 U.S. firms and 5795 firm-year observations. (The number of observations in the models varies because of missing values.)

The extant literature usually defines a firm’s TMT according to what the firm’s proxy statements report is its TMT (Dezsö and Ross [22] ; Roh et al. [78] ). Firms’ proxy statements must report information on at least five top executives, but they can include more. About 30% of the firms in our sample report that they have six top executives, and about 15% report that they have seven. Dezsö and Ross ([22] ), who examine how female representation on the TMT impacts firm performance, build on the ExecuComp database and state that they “take the managers reported in ExecuComp to be the a firm’s top management team” (p. 1078). This approach is pursued in many upper echelons studies in marketing and management (e.g., Connelly et al. [20] ; Feng et al. [25] ).

Using this definition of the TMT, we find an average TMT size of 5.94 members in our sample. There is common wisdom in the upper echelons literature that the mean size of the TMT’s “inner circle,” the group of executives who determine a firm’s strategic direction, is between three and seven people (Dezsö and Ross [22] ), but the literature has also provided estimates of between three and nine people (Carpenter et al. [18] ), with multiple studies identifying about six people (Connelly et al. [20] ; Dezsö and Ross [22] ; Feng et al. [25] ; Roh et al. [78] ). We argue that our “inner circle” definition as the group of top management executives firms report in their proxy statements is appropriate for our research purposes, since the signal of instituting a CMO position must be highly visible if imitation is to occur.

Measures CMO presence

To identify firms that have CMOs, we screened the firms’ executive titles reported in the ExecuComp database for a number of identifying terms. We used a broad definition and a narrow definition for the position of CMO. While the narrow definition refers to an executive who is has the title “CMO” or who has the term “marketing” in his or her title, the broad definition also takes into account related terms like “customer,” “sales,” and “brand” as part of the executive’s title (Bansal et al. [8] ; Menz [61] ). For a given firm and year, the measure takes the value of 1 if the screening yielded a positive result, and 0 otherwise. Web Appendix A lists the search terms used in both definitions. We use primarily the broad definition in our analysis, but we run robustness checks with the narrow definition.

CMO prevalence

We computed this independent variable by weighting the presence of a CMO position in a firm in terms of the firm’s market share for each year of observation. We then took the sum of the individual firm observations that correspond to the same 2-digit SIC code to arrive at the industry-level measure. The weighting reflects that firms observe larger firms (relative to other firms in the industry) and firms that are more widely covered in the media (Haunschild and Miner [36] ) more frequently than they do other firms. This measure can be interpreted as the market share of firms in the industry that have CMOs. We also present a robustness check with an unweighted proportion measure, which is calculated by dividing the number of firms that have CMOs and that are in the same 2-digit SIC code as the focal firm by the number of firms listed in the same 2-digit SIC code in a given year. We did not take the focal firm into consideration when we built these measures.

To confirm that 2-digit SIC codes are more appropriate in our research setting to define industry groups than the narrower 4-digit SIC codes, we conducted a small validation survey among business consultants with industry expertise. We presented fifteen consultants with profiles of three companies and a list of 100 other company names taken randomly from our sample (also with short descriptions but no SIC code information). For each of the three profiled firms, the consultants marked which of the 100 firms the profiled firm should monitor. The informants rated their ability to answer this question as consistently high (average of 4.1 on 5-point-Likert scale on the item “I felt competent in selecting competitors for (company name)”). The results show that 98% of the questionnaires identified at least one competitor that operates in the same 4-digit SIC code, and 69% of the questionnaires identified at least one firm as a competitor that was from the same 2-digit SIC code but a different 4-digit SIC code. This result suggests that firms observe others from the same 4-digit SIC code as well as those from the same 2-digit SIC code, indicating that the 2-digit SIC code level is appropriate for defining industry groups. This notion is echoed in the literature, as 2-digit SIC codes are employed in imitation studies (Yang and Hyland [92] ), and other studies indicate that 2-digit SIC codes build homogenous industry clusters that are sufficiently granular to yield explanatory power and to be transferable to other industry-classification schemes (Bhojraj et al. [10] ; Clarke [19] ). 2-digit SIC codes are also sufficiently inclusive to form industry groups that have an appropriate number of firm observations; imitation is more likely to occur, especially from the herding perspective, when a reasonable number of firms pursue a behavior that another firm can imitate (Abrahamson [2] ).

We use primarily the broad CMO definition for the prevalence measure that captures the imitation-pressure variable since we believe that a firm that observes its peers and thinks about imitation does not necessarily focus on details in titles but acts on the general tendencies it perceives in its peers’ behavior. This reasoning is in line with what we learned from interviews with practitioners, who state that exact titles of TMT members are often a matter of company policy.

Market uncertainty

We calculated market uncertainty using the volatility of the industry’s sales growth (based on 2-digit SIC codes) by regressing sales over a five-year period ending in the focal year and using the standard error of the regression divided by the mean value of industry sales for the five-year period (Seo et al. [82] ).

Firm uncertainty

Following Gaba and Terlaak’s ([28] ) approach to measuring firm uncertainty, we computed firm uncertainty as the rolling standard deviation in firm performance over the five-year period ending in the focal year, measuring firm performance as return on equity (ROE).

Inference uncertainty

To measure inference uncertainty, we applied the measure that Gaba and Terlaak ([28] ) propose. In addition to the level of inconsistency in peers’ decisions to create or dispose of the CMO position, the measure incorporates the absolute amount of information reflected in these decisions. Inference uncertainty is calculated as the absolute difference between the number of firms that created a CMO position and the number that dissolved one, divided by the number of firms that have done either, such that:Inference uncertainty=−CreatedCMOpositionst‐1‐DissolvedCMOpositionst‐1CreatedCMOpositionst‐1+DissolvedCMOpositionst‐1where the numerator captures the level of the inconsistency (the greater the absolute difference, the smaller the inconsistency) and the denominator reflects the amount of information presented by changes concerning the CMO’s position in the TMT. To facilitate interpretation, the measure is multiplied by (−1) so higher values reflect greater uncertainty.

Control variables

We controlled for a number of Nath and Mahajan’s ([69] ) structural, strategic, and environmental factors that could influence a firm’s decision to have a CMO position.1 [1] As structural variables we used firm size, measured as the natural logarithm of the firm’s number of employees (Nath and Mahajan [69] ; Ndofor et al. [72] ), and the CMO’s additional functional responsibilities, measured as a binary variable coded as 1 when a CMO has additional responsibilities, and zero otherwise. Like Nath and Mahajan ([69] ), we also consider the TMT’s marketing and general management experience, measured as the proportion of TMT members with experience in each area. We applied the search terms used to identify CMOs in order to identify TMT members who have marketing experience and code executives as having general management experience if they were the head of a division or region or held titles with no specific functional responsibilities (Nath and Mahajan [69] ). At the CEO level, we controlled for CEO tenure (as years since appointment) and for whether the CEO was hired as an outsider (as a binary variable). CEO tenure is a proxy for CEO turnover, which is usually accompanied by TMT changes that could include the creation or disposal of the CMO position (Nath and Mahajan [69] ). We captured TMT structure using TMT size (the number of executives listed in the ExecuComp database for the firm in a given year) and COO presence (as a binary variable).

As strategic variables, we took into account firm innovation (measured by the ratio of R&D to sales), differentiation strategy (measured by the ratio of advertising to sales), and diversification (a dummy variable that takes the value of 1 if the firm is diversified using Palepu’s [[73] ] measure of total diversification, and zero otherwise). As for the environmental variables, market concentration is calculated as the proportion of sales of the eight firms with the largest market shares at the 2-digit SIC level, while industry growth, measured as the average growth in industry sales over the past five years, is used as an environmental control. Finally, we controlled for prior performance, captured by the percentage change in ROE.

Analyses

We use pooled logistic regression with the generalized estimation equations (GEE) approach to test our hypotheses, which is appropriate when analyzing a binary dependent variable like CMO presence (Long [56] ). GEE estimations are particularly appropriate to our research setting, as we observe the same firms over a period of time, and the technique allows us to control for serial correlation while specifying the distribution of our dependent variable (Liang and Zeger [54] ; Zeger and Liang [93] ). Because of these favorable properties, this estimation approach is often used in research models that test for the presence of particular TMT members (e.g., Hambrick and Cannella [33] ; Nath and Mahajan [69] ) and in the study of imitation behaviors (e.g., Rhee et al. [77] ). We winsorized all values at the 1% and 99% levels and standardized all values to reduce multicollinearity (Aiken et al. [6] ). We estimated the following equation, where i is the firm and t is the year of observation:CMOpresenceit=β0+β1ProportionCMOIndustryit−1+∑j=18βj+1StructureControlsjit+∑k=13βk+9StrategyControlskit−1+∑m=12βm+12EnvironmentControlsmit+∑n=13βn+14UncertaintyTypesnit−1+∑o=13βo+17ProportionCMOIndustryit−1UncertaintyTypesoit−1+εit

Following the literature on dynamic panel models (Arellano and Bond [7] ; Wooldridge [90] ), we also employed a consistent generalized method of moments (GMM) estimator as a robustness check. In this model, we included the lag of our dependent variable, CMO presence, as an additional explanatory variable in order to accommodate the notion that current CMO presence is driven by past CMO presence.

Findings Findings on hypotheses testing

Table 2 shows the descriptive statistics and correlation coefficients. There is a broad-definition CMO in 20% of all firm-year observations in our sample, which is consistent with Bansal et al. ([8] ), who also pursue an “inner circle” view based on ExecuComp data. As no correlation coefficient exceeds |0.4|, and none of the computed variance inflation factors (VIFs) exceed the commonly defined cut-off of 10—the highest VIF has the value 1.32—we conclude that multicollinearity is not likely to be an issue in our model.

Table 3 reports the regression results of our analyses. We start by outlining the findings based on the pooled logistic regression using GEE with the (market share) weighted imitation measure and the broad CMO definition. Model 1 introduces the controls. As in Nath and Mahajan ([69] ), differentiation (β = 0.24, p < 0.001) and innovation (β = 0.19, p < 0.001) positively impact CMO presence, while the TMT’s general management experience (β = −0.53, p < 0.001) has a negative impact. Diversification (β = −0.37, p < 0.01) and COO presence (β = −0.37, p < 0.001) have a significant negative impact on CMO presence in our study. Nath and Mahajan ([69] ) also find negative regression coefficients in these cases, but without significance. Market concentration positively (β = 0.36, p < 0.001) impacts CMO presence, and firm size (β = −0.40, p < 0.001) negatively impacts it in our study, while Nath and Mahajan ([69] ) find no significant relationships for these variables. We also find that TMT size, a variable that is not included in Nath and Mahajan ([69] ), is positively related to CMO presence (β = 0.06, p < 0.05). A contradiction can be found for the TMT’s marketing experience, as we find significant negative impacts on CMO presence in all our models (e.g., in model 1: β = −0.60, p < 0.001), while Nath and Mahajan ([69] ) find two non-significant, negative regression coefficients and one significant positive impact in their models.2 [2],3 [3]

Model 2 introduces the imitation variable, CMO prevalence, whose weak but significant relationship to CMO presence (β = 0.06, p < 0.1) lends some support to H1. Model 3 introduces the three uncertainty variables, and model 4 introduces the three interaction terms. Our imitation variable is significantly positively related to CMO presence in Model 3 (β = 0.09, p < 0.05), lending further support to H1. To ease interpretation, we estimated the marginal effects of CMO prevalence in the industry on CMO presence, holding the value of all other model variables at their means (Table 4). If the prevalence of the CMO position is 0% (10%, 20%, 50%), the probability that the focal firm has a CMO is 15% (16%, 16%, 19%). Assuming an industry setting with four competitors of equal size that initially have no CMOs, if two install a CMO in year t-1, the likelihood that the focal firm will have a CMO in year t increases by 27%.

Since the interaction term in Model 4 between market uncertainty and imitation is not significantly related to CMO presence (β = −0.04, n.s.), H2 is rejected. However, H3 is supported because the interaction term between imitation and firm uncertainty is significantly positively related to CMO presence (β = 0.14, p < 0.001). Table 4 indicates the marginal effects for both high and low levels of firm uncertainty: When firm uncertainty is high and the prevalence of the CMO position in the industry is 0%, the probability that the focal firm has a CMO is only 12%. With increasing CMO prevalence (10%, 20%, 50%), the probability that the focal firm has a CMO increases (13%, 15%, 20%). Changes are much less marked when firm uncertainty is low, as Table 4 indicates.

H4 is also supported since the interaction term between imitation and inference uncertainty is significantly negatively related to CMO presence (β = −0.04, p < 0.05). Table 4 indicates that imitation is particularly strong when inference uncertainty is low. When CMO prevalence is 0%, the likelihood that the focal firm has a CMO is 15%, but this likelihood increases to 25% when half of industry peers have a CMO. When inference uncertainty is strong, an increase in CMO prevalence in the industry from 0% to 50% leads to only a small increase (from 15% to 17%) in the likelihood that the focal firm has a CMO.

In Model 5, which shows the full model with our main independent and moderating variables based on the narrow CMO definition, findings remain largely the same, albeit with lower significance levels. This result indicates that movements in peer behavior, such as installing a marketing-related position (rather than only those titled “CMO”), are sufficient to create imitation pressure and that firms do not always imitate the exact position title but may use some discretion in naming the position. Core findings remain stable in Model 6, which shows the findings when the regression is estimated based on the imitation measure without weighting for market share and based on the broad CMO definition.

Finally, Model 7 shows the dynamic model with CMO presence in t-1 as an independent variable. The direct imitation effect disappears, so H1 is not supported in this model, while H3 and H4 receive support, as they do in the other models. These findings suggest that inertia in terms of CMO presence explains more of CMO presence than imitation does and underscore the strong importance of firm and inference uncertainty as moderators.

Additional analyses

Since firms could also imitate the most successful firms, regardless of their industry, our first additional analysis built alternative proportion measures to test this suggestion. One measure is the proportion of firms that have CMOs among the 100 most successful firms in our sample based on sales, while a second measure is the proportion of firms that have CMOs among the top 100 firms based on ROE. ROE, “the true bottom-line measure of firm performance” (Ross et al. [80] , p. 59), is widely used in the marketing literature (e.g., Luo et al. [58] ). Neither measure in t-1 is significantly related to CMO presence in t, suggesting that firms do not base their decisions on whether to have a CMO on what successful firms across industries do.

Our second additional analysis estimates additional regression models based on our sample by applying to the Chief Financial Officer (CFO) and Chief Technology Officer (CTO) the same measurement logics that we used here in studying the CMO position. We adapted the independent variables when necessary (e.g., by replacing the variable “TMT’s marketing experience” with “TMT’s finance experience”). This analysis seeks to illuminate whether our arguments regarding the CMO position apply to other “novel” CxO positions (i.e., the CTO) that are often surrounded by more controversy and ambiguity than are established positions like that of the CFO. Our findings indicate that, while imitation pressure (CxO prevalence, weighted by market share) is a significant driver of CTO presence (ß = 0.13, p < 0.01), it is not a driver of CFO presence. (See Web Appendix C for the findings of the regression models.)

The third additional analysis investigated the relationship between performance and imitative behavior by seeking to determine whether firms that have CMOs in industries with strong CMO prevalence (“high CMO prevalence industries”) and firms that do not have CMOs in industries with low CMO prevalence (“low CMO prevalence industries”) outperform the other firms in our sample. In line with Brouthers and Nakos ([15] ) and Li et al. ([53] ), we built a deviation dummy score, where 1 indicates that the focal firm acts in line with its industry peers, and zero otherwise. Since the literature does not indicate what is a high or low CMO-prevalence industry, we pursue alternative definitions using two measures of prevalence (number of peers with CMOs, combined market share of peers with CMOs) and various cut-off points (e.g., top 30%, bottom 10%, more or less than average).4 [4] When we relate the resulting fit measures to the firms’ ROEs, we find either no significance or a significant negative performance impact (β = −0.13, p < 0.05 and β = −0.11, p < 0.05).

Theoretical and managerial implications

This study investigates whether a firm’s decision to have a CMO on its TMT is driven by imitation of its industry peers. Based on neoinstitutional theory, herding models, and three types of uncertainty to which firms’ decision makers are subject, we derived a theoretical model and validated it empirically. Our findings indicate that a firm’s imitative behavior can play a role in its decision to have a CMO on its TMT, especially when firm uncertainty is high and inference uncertainty is low. These findings have implications for at least four literature streams.

First, our study has implications for the growing body of literature on the CMO position, particularly for studies that investigate the antecedents of CMO presence (“group 1” in the literature overview in Table 1). Our control variables confirm the findings of the two extant studies in this area (Kashmiri and Mahajan [46] ; Nath and Mahajan [69] ) that structural, strategic, and environmental factors drive CMO presence. However, while controlling for these factors, our study adds peers’ imitation behavior in interaction with uncertainty as an explanation for firms’ decisions to have or not have CMOs. In this way, we link to the broader marketing literature that investigates copycat marketing activities like copycat private labels or copycat luxury brands (see, e.g., Kelting et al. [47] ; Gao et al. [29] ). We also show that imitation behavior is at work not only in terms of marketing activities in the marketplace, as these recent studies show but also when firms set up their internal marketing organizations (e.g., in the form of the CMO position). Our findings also contribute to the practical debate on the value of the CMO position, as they offer a social view of the phenomenon: CMO prevalence may not be increasing or decreasing only because firms recognize or refute the economic value of the CMO but also because they are driven by their peers’ behavior. The imitation-increasing effect of idiosyncratic uncertainty underscores this notion, as the weaker the position in which the firm finds itself, the more likely it is to follow its peers’ lead, even disregarding its own views on whether the CMO adds value to the TMT. Combined with the additional analysis that shows that firms do not imitate successful firms across industries, our findings also indicate that in the case of the CMO, imitation pressures emanate from the firm’s immediate industry environment; that is, firms imitate their industry peers whose situations are similar (e.g., in terms of markets, products, legal situation) to those of the focal firm.

Second, we contribute to the broader literature on the marketing organization. While extant studies in this area focus on optimal-fit perspectives (Moorman and Day [67] ), we introduce the neoinstitutional and herding perspectives that, as Hult’s ([44] ) overview shows, are largely ignored in studies on the marketing organization. We show that marketing research can draw on these two perspectives to explain phenomena related to the marketing organization (here: the presence of the CMO) and to illuminate why a firm might systematically choose marketing-related organizational constructs that are not optimal to its situation.

In addition, we argue theoretically and validate empirically that three types of uncertainty exert divergent influences on a firm’s decision to include a CMO in its TMT. Existing research on organizational issues in marketing often investigates uncertainty as a boundary condition (e.g., Luo et al. [59] ), but it focuses on unidimensional conceptualizations of uncertainty without differentiating among its types. Focusing on only one type of uncertainty or generalized uncertainty could lead to an incomplete picture of uncertainty’s role. While market uncertainty plays no role, firm uncertainty strengthens the impact on CMO presence of the prevalence of CMOs in the firm’s industry, and inference uncertainty weakens it. The finding that market uncertainty does not moderate the relationship between the prevalence of the CMO position in an industry and the presence of a CMO in a firm in that industry runs counter to our theoretical explanations, perhaps because firms pay little attention to their industry peers in determining how to confront volatile surroundings. For example, Strang and Still ([84] ) find that, with increasing uncertainty surrounding investment projects, bankers place less faith in the their peers’ behavior in guiding their own behavior than they do in experts’ opinions.

In addition to these contributions to the marketing literature, our findings contribute to the broader management literature. As our literature analysis indicates, most of the extant studies on functional TMT members focus on structural, strategic, and environmental factors to explain the presence of a particular CxO (Menz and Scheef [62] ; Roh et al. [78] ). While our controls confirm a set of those drivers for CMO presence, we add imitation behavior to the list of explanations, substantiated by the neoinstitutional (legitimacy) and herding perspectives. Thus, we show that a firm’s decision to have a particular functional CxO is a multi-faceted one that no single theoretical perspective can explain. As our post-hoc analysis indicates, imitation behavior driven by legitimacy and herding is applicable to less prevalent CxO positions, such as those of the CMO and the CTO, that are still surrounded by considerable ambiguity, and not to more established positions, such as that of the CFO. Therefore, when investigating the drivers of CxO presence, studies must take into consideration not only the CxO’s potential value to the TMT’s decision-making (e.g., perspectives, knowledge) but also such factors as the frequency of the positions presence on TMTs and uncertainty about its contributions.

We also inform the broader literature on institutional theory and herding models as it relates to sources of uncertainty, an area that has been largely neglected (Yang and Hyland [92] ). We establish that, depending on the type of uncertainty, uncertainty may strengthen or weaken a firm’s imitative behavior. In doing so, we challenge the widely held view that uncertainty always enhances a firm’s tendency to imitate (Strang and Still [84] ). In addition, our post-hoc analysis’ finding that imitation is not necessarily a competitive advantage sheds light on the relationship between imitation and performance. Westphal et al. ([89] ) find that only early adopters profit economically from novel management techniques, while imitators benefit only somewhat, if at all, since, when under pressure, they tend to copy adopters without making the necessary adaptations to their specific situation. While our dataset does not allow us to differentiate between early adopters and imitators, our finding that the fit between a firm’s decision making and the prevalent decision outcome in its industry does not yield above-average returns indicates that a dynamic similar to that of Westphal et al. ([89] ) may apply to the case of the CMO.

Limitations and avenues for future research

This study opens several avenues for future research. First, while we argue that legitimacy- and herding-related mechanisms translate the prevalence of the CMO position in an industry into whether a particular firm in that industry adds a CMO to its TMT, we do not measure the corresponding variables (social pressures related to legitimacy, reputation, and competitive position) as mediators in our regression models. Using secondary data, like the data we use in this study, to measure variables that are related to various types of perceived social pressures may be impossible. Future studies could build experiments that confront top managers with a variety of scenarios in which CMO positions are installed or dismissed in an industry in order to provide information about how the types of social pressures impact a firm’s decision concerning whether to have a CMO. As the literature review in Table 1 indicates, extant studies have almost exclusively used secondary data sources, so future studies could also investigate the potential of combining secondary and primary data on CMO-related topics. While CMOs in large firms are often difficult to survey, surveys about prominent CMOs in large firms (e.g., surveys on their modes of communication) fielded to industry experts could be combined with available secondary data on the firm.

Another avenue for future research involves whether group-oriented behavior (as imitation of industry peers can be) may change with altering conditions (e.g., the decision maker develops knowledge about the topic) (Harmeling et al. [35] ). Future research might adopt insights from this literature to our topic in order to determine whether experience gained with the CMO position or the firm’s growth into a dominant industry player impacts the role of imitation in the decision concerning whether to have a CMO on the TMT.

J. Andrew Petersen served as Area Editor for this article.

Electronic supplementary material

The online version of this article (doi:10.1007/s11747-017-0533-x) contains supplementary material, which is available to authorized users.

References Citations

1 Abrahamson E, Managerial fads and fashions: The Diffusion and refection of innovations, Academy of Management Review, 1991, 16, 3, 586, 612, 10.5465/amr.1991.4279484

• 2 Abrahamson E, Management fashion, Academy of Management Review, 1996, 21, 1, 254, 285, 10.5465/amr.1996.9602161572
• 3 Abrahamson E, Rosenkopf L, When do bandwagon diffusions roll? How far do they go? And when do they roll backwards?. A computer simulation, Academy of Management Proceedings, 1990, 1990, 1, 155, 159, 10.5465/ambpp.1990.4978478
• 4 Abrahamson E, Rosenkopf L, Institutional and competitive bandwagons: using mathematical modeling as a tool to explore innovation Diffusion, Academy of Management Review, 1993, 18, 3, 487, 517, 10.5465/amr.1993.9309035148
• 5 Abrahamson E, Rosenkopf L, Social network effects on the extent of innovation diffusion: a computer simulation, Organization Science, 1997, 8, 3, 289, 309, 10.1287/orsc.8.3.289
• 6 Aiken LS, West SG, Reno RR, Multiple regression: testing and interpreting interactions, 1991, Newbury Park, Sage Publications
• 7 Arellano M, Bond S, Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 1991, 58, 194, 277, 10.2307/2297968
• 8 Bansal, N., Joseph, K., Ma, M., & Wintoki, M. B. (2016). Do CMO incentives matter? An empirical investigation of CMO compensation and its impact on firm performance., Management Science.
• 9 Basdeo DK, Smith KG, Grimm CM, Rindova VP, Derfus PJ, The impact of market actions on firm reputation, Strategic Management Journal, 2006, 27, 12, 1205, 1219, 10.1002/smj.556
• 10 Bhojraj S, Lee CMC, Oler DK, What's my line? A comparison of industry classification schemes for capital market research, Journal of Accounting Research, 2003, 41, 5, 745, 774, 10.1046/j.1475-679X.2003.00122.x
• 11 Bikhchandani S, Hirshleifer D, Welch I, A theory of fads, fashion, custom, and cultural change as informational cascades, Journal of Political Economy, 1992, 100, 5, 992, 1026, 10.1086/261849
• 12 Bikhchandani S, Hirshleifer D, Welch I, Learning from the behavior of others: conformity, fads and informational cascades, Journal of Economic Perspectives, 1998, 12, 3, 151, 170, 10.1257/jep.12.3.151
• 13 Boyd D, Brown B, Marketing control rights and their distribution within technology licensing agreements: a real options perspective, Journal of the Academy of Marketing Science, 2012, 40, 5, 659, 672, 10.1007/s11747-011-0262-5
• 14 Boyd, D., Chandy, R. K., & Cunha, M. (2010). When do chief marketing officers affect firm value?: a customer power explanation., Journal of Marketing Research, 47(6), 1162-1176.
• 15 Brouthers K, Nakos G, SME entry mode choice and performance: a transaction cost perspective, Entrepreneurship Theory & Practice, 2004, 28, 3, 229, 247, 10.1111/j.1540-6520.2004.00041.x
• 16 Brown SW, Webster FE, Steenkamp J-BE, Wilkie WL, Sheth JN, Sisodia RS, Marketing renaissance: opportunities and imperatives for improving marketing thought, practice, and infrastructure, Journal of Marketing, 2005, 69, 4, 1, 25, 10.1509/jmkg.2005.69.4.1
• 17 Burt R, The contingent value of social capital, Administrative Science Quarterly, 1997, 42, 2, 339, 365, 10.2307/2393923
• 18 Carpenter MA, Geletkanycz MA, Sanders W, Upper echelons revisited: antecedents, elements, and consequences of top management team composition, Journal of Management, 2004, 30, 749, 778, 10.1016/j.jm.2004.06.001
• 19 Clarke RN, SICs as delineators of economic markets, The Journal of Business, 1989, 62, 1, 17, 31, 10.1086/296449
• 20 Connelly BL, Haynes KT, Tihanyi L, Gamache DL, Devers CE, Minding the gap: antecedents and consequences of top management-to-worker pay dispersion, Journal of Management, 2016, 42, 4, 862, 885, 10.1177/0149206313503015
• 21 Delios A, Gaur AS, Makino S, The timing of international expansion: information, rivalry and imitation among Japanese firms, 1980-2002, Journal of Management Studies, 2008, 45, 1, 169, 195
• 22 Dezsö C, Ross D, Does female representation in top management improve firm performance?: a panel data investigation, Strategic Management Journal, 2012, 33, 9, 1072, 1089, 10.1002/smj.1955
• 23 DiMaggio PJ, Powell WW, The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields, American Sociological Review, 1983, 48, 147, 160, 10.2307/2095101
• 24 Engelen A, Lackhoff F, Schmidt S, How can chief marketing officers strengthen their influence? A social capital perspective across six country groups, Journal of International Marketing, 2013, 21, 4, 88, 109, 10.1509/jim.13.0017
• 25 Feng H, Morgan NA, Rego LL, Marketing department power and firm performance, Journal of Marketing, 2015, 79, 5, 1, 20, 10.1509/jm.13.0522
• 26 Feng H, Morgan NA, Rego LL, Firm capabilities and growth: the moderating role of market conditions, Journal of the Academy of Marketing Science, 2017, 45, 1, 76, 92, 10.1007/s11747-016-0472-y
• 27 Frösén J, Luoma J, Jaakkola M, Tikkanen H, Aspara J, What counts versus what can be counted: the complex interplay of market orientation and marketing performance measurement, Journal of Marketing, 2016, 80, 3, 60, 78, 10.1509/jm.15.0153
• 28 Gaba V, Terlaak A, Decomposing uncertainty and its effects on imitation in firm exit decisions, Organization Science, 2013, 24, 6, 1847, 1869, 10.1287/orsc.2013.0823
• 29 Gao, S. Y., Lim, W. S., & Tang, C. S. (2016). Entry of copycats of luxury brands., Marketing Science. doi:10.1287/mksc.2016.1008
• 30 Garcia-Pont C, Nohria N, Local versus global mimetism: the dynamics of alliance formation in the automobile industry, Strategic Management Journal, 2002, 23, 4, 307, 321, 10.1002/smj.225
• 31 Germann F, Ebbes P, Grewal R, The chief marketing officer matters!, Journal of Marketing, 2015, 79, 3, 1, 22, 10.1509/jm.14.0244
• 32 Gilliatt N, Cuming P, The chief marketing officer: a maverick whose time has come, Business Horizons, 1986, 29, 1, 41, 10.1016/0007-6813(86)90085-6
• 33 Hambrick DC, Cannella AA, C.E.O. Who have COOS: contingency analysis of an explored structural form, Strategic Management Journal, 2004, 25, 10, 959, 979, 10.1002/smj.407
• 34 Han, K., Mittal, V., & Zhang, Y. (2016). Relative strategic emphasis and firm idiosyncratic risk: the moderating role of relative performance and demand instability., Journal of Marketing. doi:10.1509/jm.15.0509
• 35 Harmeling, C. M., Palmatier, R. W., Fang, E., & Wang, D. (2017). Group marketing: theory, mechanisms, and dynamics., Journal of Marketing. doi:10.1509/jm.15.0495
• 36 Haunschild PR, Miner AS, Modes of Interorganizational imitation: the effects of outcome salience and uncertainty, Administrative Science Quarterly, 1997, 42, 3, 472, 500, 10.2307/2393735
• 37 Head K, Mayer T, Ries J, Revisiting oligopolistic reaction: are decisions on foreign direct investment strategic complements?, Journal of Economics & Management Strategy, 2002, 11, 3, 452, 471, 10.1162/105864002320272567
• 38 Henisz WJ, Delios A, Uncertainty, imitation, and plant location: Japanese multinational corporations, 1990-1996, Administrative Science Quarterly, 2001, 46, 443, 10.2307/3094871
• 39 Hirshleifer, D., & Teoh, S. H. (2003). Herd behaviour and cascading in capital markets: a review and synthesis., European Financial Management, 9(1), 25-66.
• 40 Hoda, S. (2015). Why the best chief marketing officer might not be a marketer: introducing the 360-degree CMO. Huffington post. Retrieved 16 Mar 2016, from, http://www.huffingtonpost.com/syed-hoda/why-the-best-chief-market_b_8052104.html.
• 41 Hogarth RM, Judgement and choice: the psychology of decision, 1987, 2, New York, Wiley
• 42 Homburg C, Hahn A, Bornemann T, Sandner P, The role of chief marketing officers for venture capital funding: Endowing new ventures with marketing legitimacy, Journal of Marketing Research, 2014, 51, 5, 625, 644, 10.1509/jmr.11.0350
• 43 Huang T-C, Lin B-H, Yang T-H, Herd behavior and idiosyncratic volatility, Journal of Business Research, 2015, 68, 4, 763, 770, 10.1016/j.jbusres.2014.11.025
• 44 Hult G, Toward a theory of the boundary-spanning marketing organization and insights from 31 organization theories, Journal of the Academy of Marketing Science, 2011, 39, 4, 509, 536, 10.1007/s11747-011-0253-6
• 45 Hyde, P., Landry, E., & Tipping, A. (2004). Making the perfect marketer., Strategy+Business, 37, 37-43.
• 46 Kashmiri S, Mahajan V, What’s in a name?: an analysis of the strategic behavior of family firms, International Journal of Research in Marketing, 2010, 27, 3, 271, 280, 10.1016/j.ijresmar.2010.04.001
• 47 Kelting, K., Duhachek, A., & Whitler, K. (2017). Can copycat private labels improve the consumer’s shopping experience? A fluency explanation., Journal of the Academy of Marketing Science, 1-17. doi:10.1007/s11747-017-0520-2
• 48 Kerin R, Strategic marketing and the CMO in: Marketing renaissance: opportunities and imperatives for improving marketing thought, practice, and infrastructure, Journal of Marketing, 2005, 69, 4, 12, 14
• 49 Kim, M., Boyd, D. E., Kim, N., & Yi, C. H. (2016). CMO equity incentive and shareholder value: Moderating role of CMO managerial discretion., International Journal of Research in Marketing, 33(4), 725-738.
• 50 Kim C, Pantzalis C, Global/industrial diversification and analyst herding, Financial Analysts Journal, 2003, 59, 2, 69, 10.2469/faj.v59.n2.2515
• 51 Krush MT, Sohi RS, Saini A, Dispersion of marketing capabilities: impact on marketing’s influence and business unit outcomes, Journal of the Academy of Marketing Science, 2015, 43, 1, 32, 51, 10.1007/s11747-014-0420-7
• 52 Lee K, Pennings JM, Mimicry and the market: adoption of a new organizational form, Academy of Management Journal, 2002, 45, 1, 144, 162
• 53 Li Y, Ji J, Cai Z, The timing of market entry and firm performance: a perspective of institutional theory, Industrial Marketing Management, 2014, 43, 5, 754, 759, 10.1016/j.indmarman.2014.04.007
• 54 Liang K-Y, Zeger SL, Longitudinal data analysis using generalized linear models, Biometrika, 1986, 73, 1, 13, 22, 10.1093/biomet/73.1.13
• 55 Lieberman MB, Asaba S, Why do firms imitate each other?, Academy of Management Review, 2006, 31, 2, 366, 385, 10.5465/amr.2006.20208686
• 56 Long JS, Regression models for categorical and limited dependent variables. Advanced quantitative techniques in the social sciences, 1997, Thousand oaks, Sage publications
• 57 Lubatkin MH, Simsek Z, Ling Y, Veiga JF, Ambidexterity and performance in small-to medium-sized firms: the pivotal role of top management team behavioral integration, Journal of Management, 2006, 32, 5, 646, 672, 10.1177/0149206306290712
• 58 Luo X, Rindfleisch A, Tse DK, Working with rivals: the impact of competitor alliances on financial performance, Journal of Marketing Research (JMR), 2007, 44, 1, 73, 83, 10.1509/jmkr.44.1.73
• 59 Luo X, Wieseke J, Homburg C, Inventivizing CEOs to build customer- and employee-firm relations for higher customer satisfaction and firm value, Journal of the Academy of Marketing Science, 2012, 40, 6, 745, 758, 10.1007/s11747-011-0290-1
• 60 McGovern G, Quelch J, The fall and rise of the CMO, Strategy+Business, 2004, 37, 1, 8
• 61 Menz M, Functional top management team members: a review, synthesis, and research agenda, Journal of Management, 2012, 38, 1, 45, 80, 10.1177/0149206311421830
• 62 Menz M, Scheef C, Chief strategy officers: contingency analysis of their presence in top management teams, Strategic Management Journal, 2014, 35, 3, 461, 471, 10.1002/smj.2104
• 63 Meyer JW, Rowan B, Institutionalized organizations: formal structure as myth and ceremony, American Journal of Sociology, 1977, 83, 2, 340, 363, 10.1086/226550
• 64 Meyer JW, Scott WR, Organizational environments: ritual and rationality, 1983, Beverly Hills, SAGE
• 65 Mintz O, Currim IS, What drives managerial use of marketing and financial metrics and does metric use affect performance of marketing-mix activities?, Journal of Marketing, 2013, 77, 2, 17, 40, 10.1509/jm.11.0463
• 66 Moorman, C. (2015). The CMO Survey. Retrieved 16 Feb 2016, from, http://cmosurvey.org/results/survey-results-february-2015/.
• 67 Moorman, C., & Day, G. S. (2016). Organizing for marketing excellence., Journal of Marketing, 80(6), 6-35.
• 68 Morgan NA, Slotegraaf RJ, Vorhies DW, Linking marketing capabilities with profit growth, International Journal of Research in Marketing, 2009, 26, 4, 284, 293, 10.1016/j.ijresmar.2009.06.005
• 69 Nath P, Mahajan V, Chief marketing officers: a study of their presence in firms’ top management teams, Journal of Marketing, 2008, 72, 1, 65, 81, 10.1509/jmkg.72.1.65
• 70 Nath P, Mahajan V, Marketing in the C-suite: a study of chief marketing officer power in firms’ top management teams, Journal of Marketing, 2011, 75, 1, 60, 77, 10.1509/jmkg.75.1.60
• 71 Nath, P., & Mahajan, V. (2017). Shedding light on the CMO revolving door: a study of the antecedents of chief marketing officer turnover., Journal of the Academy of Marketing Science, 45(1), 93-118.
• 72 Ndofor HA, Sirmon DG, He X, Utilizing the firm’s resources: how TMT heterogeneity and resulting faultlines affect TMT tasks, Strategic Management Journal, 2015, 36, 1656, 1674, 10.1002/smj.2304
• 73 Palepu K, Diversification strategy, profit performance and the entropy measure, Strategic Management Journal, 1985, 6, 3, 239, 255, 10.1002/smj.4250060305
• 74 Palley TI, Safety in numbers: a model of managerial herd behavior, Journal of Economic Behavior & Organization, 1995, 28, 3, 443, 10.1016/0167-2681(95)00046-1
• 75 Parsons T, Structure and process in modern societies, 1960, Glencoe, Free Press
• 76 Pfeffer J, Salancik GR, The external control of organizations: a resource dependence perspective, 1978, New York, Harper & Row
• 77 Rhee M, Kim Y-C, Han J, Confidence in imitation: niche-width strategy in the UK automobile industry, Management Science, 2006, 52, 4, 501, 513, 10.1287/mnsc.1050.0494
• 78 Roh J, Krause R, Swink M, The appointment of chief supply chain officers to top management teams: a contingency model of firm-level antecedents and consequences, Journal of Operations Management, 2016, 44, 48, 61, 10.1016/j.jom.2016.05.001
• 79 Ross J-M, Sharapov D, When the leader follows: avoiding dethronement through imitation, Academy of Management Journal, 2015, 58, 3, 658, 679, 10.5465/amj.2013.1105
• 80 Ross S, Westerfield R, Jordan B, Essentials of corporate finance, 2001, Boston, McGraw-Hill
• 81 Scott WR, The adolescence of institutional theory, Administrative Science Quarterly, 1987, 32, 493, 511, 10.2307/2392880
• 82 Seo J, Gamache DL, Devers CE, Carpenter MA, The role of CEO relative standing in acquisition behavior and CEO pay, Strategic Management Journal, 2015, 36, 1877, 1894, 10.1002/smj.2316
• 83 Shen W, Cho TS, Exploring involuntary executive turnover through a managerial discretion framework, Academy of Management Review, 2005, 30, 4, 843, 854, 10.5465/amr.2005.18378881
• 84 Strang D, Still M, Does ambiguity promote imitation, or hinder it?: an empirical study of benchmarking teams, European Management Review, 2006, 3, 2, 101, 112, 10.1057/palgrave.emr.1500056
• 85 Suchman MC, Managing legitimacy: Strategic and institutional approaches, Academy of Management Review, 1995, 20, 3, 571, 610, 10.5465/amr.1995.9508080331
• 86 Turpin, D. (2012). The CMO is Dead. Retrieved 23 Aug 2016, from, http://www.forbes.com/sites/onmarketing/2012/10/03/the-cmo-is-dead/#796a76822505.
• 87 Wang, R., Gupta, A., & Grewal, R. (2016). Mobility of top marketing and sales executives in business-to-business markets: a social network perspective., Journal of Marketing Research.
• 88 Wang R, Saboo AR, Grewal R, A managerial capital perspective on chief marketing officer succession, International Journal of Research in Marketing, 2015, 32, 2, 164, 178, 10.1016/j.ijresmar.2014.11.001
• 89 Westphal JD, Gulati R, Shortell SM, Customization or conformity? An institutional and network perspective on the content and consequences of TQM adoption, Administrative Science Quarterly, 1997, 42, 2, 366, 394, 10.2307/2393924
• 90 Wooldridge JM, Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity, Journal of Applied Econometrics, 2005, 20, 1, 39, 54, 10.1002/jae.770
• 91 Xia J, Tan J, Tan D, Mimetic entry and bandwagon effect: the rise and decline of international equity joint venture in China, Strategic Management Journal, 2008, 29, 2, 195, 217, 10.1002/smj.648
• 92 Yang M, Hyland MA, Who do firms imitate? A multilevel approach to examining sources of imitation in the choice of mergers and acquisitions, Journal of Management, 2006, 32, 3, 381, 399, 10.1177/0149206305280790
• 93 Zeger SL, Liang K-Y, Longitudinal data analysis for discrete and continuous outcomes, Biometrics, 1986, 42, 1, 121, 130, 10.2307/2531248
• 94 Zimmerman MA, Zeitz GJ, Beyond survival: achieving new venture growth by building legitimacy, Academy of Management Review, 2002, 27, 3, 414, 431, 10.5465/amr.2002.7389921
1 See Web Appendix B for a table that juxtaposes Nath and Mahajan’s (2008) measurement instruments with ours and shows the controls and differences in the impacts of these controls on CMO presence in the regression models. 2 Nath and Mahajan’s (2017) study on what explains CMO turnover finds a curvilinear relationship between the TMT’s marketing experience and CMO turnover, which indicates that the impact of the TMT’s marketing experience is not linear but more complex. This complex relationship could reconcile the partial differences between our study’s findings concerning this variable and those in Nath and Mahajan (2008). 3 See Web Appendix B for a detailed juxtaposition between the control effects in Nath and Mahajan (2008) and those in our study. 4 We use three definitions of a high (low) CMO-prevalence industry: (1a) The industry is above (below) average in terms of the number of firms with CMOs in the industry compared to all industries in our sample; (1b) the industry is above (below) average in terms of the combined market share of the firms that have CMOs in the industry compared to all industries in our sample; (2a) at least 30% (not more than 10%) of firms in the industry have a CMO; (2b) the combined market share of firms that have CMOs in the industry is at least 30% (not more than 10%); (3a) at least 50% (not more than 5%) of firms in the industry have a CMO, and (3b) the combined market share of firms that have CMOs in the industry is at least 50% (not more than 5%).

PHOTO (COLOR)

PHOTO (COLOR)

PHOTO (COLOR)

PHOTO (COLOR): (PDF 83 KB)

PHOTO (COLOR): (PDF 129 KB)

PHOTO (COLOR): (PDF 208 KB)

By Cecilia Wiedeck and Andreas Engelen