Mediators and Market Segmentation

Transcription

1 Mediators and Market Segmentation Elizabeth George Pontikes University of Chicago Booth School of Business April 12, 2013 Draft, do not cite Acknowledgements: I would like to thank Ron Burt, James Evans, Ray Reagans, Amanda Sharkey, and Chris Yenkey for helpful comments and suggestions, and Noah Askin, John Burrows, and Tony Vashevko for assistance with data collection. This research is funded in part by the Polsky Center for Entrepreneurship and the Charles E. Merrill Faculty Research Fund at the University of Chicago Booth School of Business.

2 Mediators and Market Segmentation ABSTRACT This study investigates the role of mediators in defining market segments. Mediators segment a domain by coining labels, deciding which organizations to include as part of the label, and ranking organizations within the market segment. Some markets take hold, others fade away, and still others are continuously re-defined. This study investigates what influences whether a market segment will persist over time. It proposes that both compositional factors, in term of whether specialists or generalists are included in a market, and relational factors, in terms of how the market is connected to other segments in the domain, are influential. These ideas are investigated for the market definition activities of Gartner, the prominent IT analyst organization, through a quantitative longitudinal analysis of all magic quadrant reports on IT market segments released by Gartner from Findings show that the vertical structure of a market segment is critical to the processes studied. When market segments include many specialists at the low-end of the market, they are more likely to persist. However, at early stages of market development, markets with many specialists in the high-end are less likely to persist. This suggests that before a market segment is well established, the identity-enhancing benefits of specialists are offset by the credibility of prominent generalists. For the relational analysis, findings show that lenient markets, with connections to many other market segments, are less likely to persist. This supports the idea that leniency dilutes the distinctiveness and thus the value of these segments, and as hypothesized, this effect is driven by connections of organizations that rank highest in the market. Surprisingly, findings also show that leniency as measured by connections from lowranking organizations lead to higher rates of market persistence.

3 Mediators and Market Segmentation Often [the IT vendors] don t have the clout in their own right to name Normally somebody wants a third party to make that naming intervention. It could be academia that does it; sometimes it is. It could be a group of vendors who get together and start using common terms. But normally the vendors are desperately trying to use different terms because they don t want to be seen as copying or following a competitor. So what happens with us is we [Gartner] are in effect drawing a starting line, saying: there is the line. And everybody lines up behind it Analyst, Gartner Inc. (Pollock and Williams 2011) Market emergence is an increasingly important subject in organizational research. Markets segment the competitive sphere and provide cognitive structures people use to understand and evaluate organizations. Managers use market segments to identify competitors, customers to discover alternatives, investors to create comparison sets, and researchers to define their scope of study. How markets are defined has a material effect on organizations. This is especially interesting from a sociological perspective because markets are, in part, socially constructed. Market segments reflect underlying similarities among organizations and their offerings, but where boundaries are drawn is based on perceptions of market participants (DiMaggio 1987). For market segments to effectively sort organizations and their products, there needs to be an agreed-upon definition of what constitutes a market segment that is, what market labels stand for and which organizations should be included within the boundaries of a market (Hannan, Pólos and Carroll 2007). The role of a mediator is to sort through the multiplicity of offerings in a market and create sensible market segments that people can use to find organizations and products. This can take the form of rankings (for example the U.S. News ranking of universities, colleges, business schools, law schools, and the like), reports (for example reports issued by information technology analysts), or guides (for example Zagat s restaurant guide). The market segments (or more generally, categories) that are used in these 1

4 reports not only reflect how people already think about and segment the domain, but also anticipate future directions for new segments. It is important for mediators to follow existing trends in order for the segments they feature to be credible and useful. But, as the introductory quote indicates, it is also important for them to stake out new directions in a market. Naming new trends, and drawing a line around a label to define a market segment, is fundamental activity for mediators such as market analysts. Mediators feature prominently in organizational research on classification. Researchers use mediators much like the target customer does: to define the relevant segments of a domain. Using categories defined by stock market analysts, film critics, or online Web sites, studies show that defying these boundaries can have harmful consequences for organizations or individuals (Hsu 2006; Zuckerman 1999; Hsu, Hannan and Koçak 2009). This work focuses on the consequences producers face if they defy categorical boundaries, but it underplays the disagreements, changes, and general complexity in mediators creation of categories. Categories are treated as fixed systems that arise from stable properties of organizations. But, as with any classification process, mediators develop market segments by trying out new labels, retiring others, updating definitions, and refining the competitive set (Bowker and Star 1999). Research on rankings emphasizes the contested process by which mediators establish categorical boundaries (Espeland and Sauder 2007). This work highlights the element of social construction in categorical definitions, but again focuses on how the categories, once constructed by mediators, induce conformity in the population. The way mediators construct the category is treated as somewhat idiosyncratic. Given that prominent mediators are looked to as authorities on market segmentation and that there are strong pressures to conform to their classifications, it is important to understand 2

5 how the process of market segmentation unfolds from the mediator perspective. This paper suggests that there are general structural factors in terms of a market segments composition and its relationships to other markets that influence whether it will continue to be a relevant market segment reported on by mediators. A large body of research shows that establishing and maintaining distinctiveness is critical for categories to emerge and endure. Categories are created when there is widespread agreement on a schema, or definition that outlines feature values that indicate which objects should be considered part of the category (Hannan, Pólos and Carroll 2007). Coming to agreement on a schema, and defining boundaries of a category, is a social process (Lamont and Molnar 2002). The stronger the boundaries, the more distinctive a category is. Distinctive categories are more appealing and more valuable, especially for novice audiences who use categories to make sense of an unfamiliar domain (Pontikes 2012; Kovács and Hannan 2010; Negro, Hannan and Rao 2010). At the same time, it is also important to be able to place a category within the larger domain. When a category is new and unfamiliar, analogies to established types helps facilitate understanding and acceptance (Bingham and Kahl 2013; Hargadon and Sutton 1997). In the medical field, when there were a lot of organizational forms with related identities, this increased the probability that a new form would emerge to a point until the area of identity space became too crowded (Ruef 2000). Applied to markets, these studies indicate that both connection and uniqueness will be important for the emergence and endurance of market segments. This study suggests the extent to which distinctiveness and similarity contribute to the persistence of a market segment in are not idiosyncratic, but are systematically related to the vertical structure of a market segment and its maturity. Research on organizational categorization 3

6 has largely looked at markets as clusters of similar organizations. However, markets also develop a hierarchical structure and quality ordering (White 1981; Podolny 1993). High-status organizations are most prominent and their activities are seen as the future of the market. Organizations at the low-end provide momentum and prospects for growth. Because high-status organizations are seen as representative of a market segment, it is their distinctiveness or connectivity at relevant stages of market maturity that is most salient, which increases the likelihood the market segment will endure. Low-status organizations are not as highly scrutinized, and so can balance the activities of organizations at the high-end, allowing the market segment as a whole to be both distinctive and familiar. The extent to which a market is different from or similar to other markets in the domain is considered in in terms of both the composition of organizations in the market segment and its relationships to other market segments. The compositional view looks at whether organizations in the market segment are specialists or generalists, while the relational view considers how many connections a focal market segment has to other markets in the domain. These ideas are investigated in a longitudinal analysis of magic quadrant reports on information technology market segments issued by the preeminent technology analyst, Gartner. Mediators and market definition Systems of classification are agreed-upon segmentations of a domain. A functional system of classification implies a level of consensus about labeling, meaning, and boundaries of categories. As such, the creation and maintenance of classification is an inherently social process. Mediators are not necessary for classification; categorical boundaries can emerge through informal interactions among producers. For instance, taking a competitive stance in a market vis-à-vis 4

7 rivals can lead to stable markets (White 1981; Porac et al. 1995), and category distinctions are reinforced when producers self-identify with market segments (Pontikes and Hannan 2012; Negro, Hannan and Rao 2011). At the same time, mediators such as critics or analysts can play an important role in structuring classification within a domain. Mediators are seen as a neutral third party who can draw a boundary around markets, as well as rank individuals or organizations within them, providing stability and guidance to producers (Hsu, Roberts and Swaminathan 2011). An information technology (IT) analyst from Gartner, the preeminent information technology research firm and subject of the empirical analysis in this paper, describes their role as mediators in the IT domain: When something like CRM comes up or ERP or whatever, you ll find that analysts were going: Look there s a pattern. There s a trend. It s consolidating this is going to go in that direction and that s going to be called [pauses for effect] ERP. We are doing that for the users. The vendors then go: Great. That is where we are going. Boom! We re an ERP vendor. They do it because they can see that we have drawn a box around a market that they are slap right bang in the middle of and they feel that they can dominate it or have a serious part to play, (Pollock and Williams 2011). This quote emphasizes the role of mediators in drawing boundaries around markets, as well as the importance of labeling. In fact, a point of pride of Gartner analysts is their ability to coin labels for market segments, sometimes even seeing labels as competing with one another, as the analyst s continued discussion highlights: we coin[ed] acronyms like MRM, which is Marketing Resource Management in about EFM I think we came up with in about 2005 So, for example, in marketing, we used to talk about MOM, which is like Marketing Operations Management. We decided we would prefer the term Marketing Resource Management. I can t remember exactly why, but it was about the resourcing, staffing, and operational issues, and it is interesting now you will hardly ever see the term MOM. It just got slaughtered by MRM. (2011) Gartner s focus on labeling reflects theoretical research on the formation of categories, which proposes that categories emerge when audiences come to agreement on a definition associated with a label (Hannan, Pólos and Carroll 2007). The role of mediators is to promote a 5

8 label and a definition that both producers and customers can rely on. The above quotes suggest that coining new labels is an important activity for Gartner. However, although Gartner is critical in promoting labels, often they are not the primary authors of new labels. Gartner is widely credited with having coined CRM in the 1990s, but this concept is traced back to work of marketing academics in the 1980s (Pollock and Williams 2011). Even Gartner s own descriptions indicate that they are not always the primary authors of labels. The above analyst s description of the enterprise feedback management market segment illustrates this point: [we saw] there is an elite group of Feedback Management vendors here who are giving multichannel, real time, and they are doing analytics so we said it is something Feedback Management. And we noticed that there is a company up in Boston [who] started to use the term EFM Enterprise Feedback Management and we went that s the term we like. So we basically stole it and started using it and if you look around now, any Feedback Management vendor who is of any decent type will have EFM slapped all over their website because that is the term, (2011). This quote shows how analysts move through the sense-making process of noticing a pattern, clustering similar organizations, and labeling them. It also shows that Gartner does not necessarily author new labels, in that they are first to use a term. Indeed, a study that compares Gartner reports to press releases issued by software producers between finds that over 90% of terms picked up by Gartner (in all reports not just magic quadrants) are first found in producer press releases (Pontikes 2013). Still, even if Gartner does not coin a label, they are still actively engaged in naming a market segment. They articulate the label s definition and its competitive set, and draw boundaries that provide some stability to classification within the IT domain. Market segments are created and maintained by mediators through a negotiated process. Some segments take root and become standard industry classification; for Gartner these include customer relationship management (CRM), enterprise resource planning (ERP) and marketing resource management (MRM). Other segments are introduced but do not take hold 6

9 either fading away completely or being replaced with something else. For mediators that have sway over producers and consumers, the classifications they choose to promote influence the market structure of an industry. Therefore it is important to understand the factors that influence the market segments that endure in classification promoted by mediators. Compositional factors Market segments are categories within a system of classification. As such the literature on how categories emerge and endure can be fruitfully applied to questions in this study. Categories are most useful as cognitive maps if they are distinctive. Rosch (1978) proposes that basic level categories have higher cue validity and are therefore more differentiated from other categories. One way a category can be more or less differentiated is based on its membership, or compositional factors. The activities of category members influence how the category s social meaning evolves. When members of a category borrow elements from a different category, they blur the boundaries and make the focal category less differentiated (Rao, Monin and Durand 2005). In addition, organizational forms are more likely to coalesce when members have an identity that is focused on the category. A case study on the disk array market cites the fact that most disk array organizations derived their primary identities from other markets as a reason why the emerging market failed to become an organizational form (McKendrick and Carroll 2001). Further, the number of organizations that started in the disk array market contributed to the establishment of the form, while the number of organizations making lateral moves from other markets into disk arrays undercut the form s development (McKendrick, Jaffee, Carroll and Khessina 2003). In the mutual fund industry, categories with more internal variability were 7

10 more likely to be reconstituted (Lounsbury and Rao 2004). These studies suggest that when market segments are composed of similar organizations whose activities are focused on the market, it increases the segment s distinctiveness. If distinctive market segments are less likely to be replaced, this implies: Hypothesis 1: Mediators are more likely to continue to report on market segments that contain more specialists. At the same time, other literatures have emphasized the role of analogy in categorical development, especially at early stages when new categories are unknown. Research in psychology shows that people draw analogies from familiar schemas to understand new concepts (Novick and Holyoak n.d.; Gick and Holyoak 1983). In an organizational context, managers draw analogies with familiar concepts to craft new strategies (Gavetti, Levinthal and Rivkin 2005), to create innovative technologies (Hargadon and Sutton 1997), and to make sense of new product markets (Bingham and Kahl 2013). Ruef (2000) shows that in the health care field, having links to similar organizational forms helps foster the creation of new forms, because these connections have a legitimizing effect on the a potential new form. Together, these studies suggest that in early stages of market creation, generalist members those with ties to other market segments may make the new market segment easier to understand and accept. But if a market segment contained only generalist members in its early stages, how could it become distinctive enough to attract credible specialist organizations as it matured? Indeed, the in the example of the disk array market, there were generalist members even at very early stages, and the form still did not coalesce. 8

11 Considering the vertical structure of a market segment can resolve this conflict. Often research in classification focuses on horizontal differences across product markets, but ignores vertical differentiation within a market. Yet, most markets reveal a status ordering, and an organization s vertical position constrains its opportunities, the actions it can take, and potential rewards (Phillips and Zuckerman 2001; Podolny 1993). Moreover, high-status organizations are more visible and are viewed as representative of the market, and their actions hold special weight for outside observers. For example, the development of the novevelle cuisine movement in France, defections of high-status chefs from the traditional classical cuisine were most important in legitimizing the new form (Rao, Monin and Durand 2003). This suggests that in early stages of market segment formation, a combination of generalists in high-status positions and specialists in low-status positions can support the longevity of the new market. High-status generalist organizations create links to familiar markets to anchor the new segment, while lowstatus specialist organizations provide a platform on which the segment can coalesce around a distinctive identity. This implies: Hypothesis 2: In early stages of market emergence, mediators are less likely to continue to report on market segments that contain more specialists in high-status positions. Relational factors Another way a category can be more or less distinctive is based on its position with respect to other categories, or in terms of relational factors. Categories are defined not only in terms of their composition, but also in terms of the categories they are connected to. Market segments that 9

12 have a high degree of overlap with other segments in the domain have low contrast and are not as distinctive. As a result, they are less valuable for organizational members (Kovács and Hannan 2010; Negro, Hannan and Rao 2010). This is especially true when a market segment is in a central location in its network with connections to many other markets (Pontikes and Barnett 2012). Relational factors take into account how many other markets a focal market is connected to, or their centrality in the market network. Market segments that both 1) have a high number of generalists and 2) have high network centrality are lenient. This is because such markets do not highly constrain their members from being in a variety of different market segments. Lenient markets not only contain generalists, but also are similar to a large number of other markets. Relational factors (leniency) result from compositional factors (generalists) in that market segments are connected to each other through their organizational members. But there are important conceptual differences between the two. If we consider compositional factors only, market segments with a high number of generalists might overlap with only one or two other markets. This limited overlap has the potential to act as an anchor in early stages of market formation, providing familiarity and legitimacy to an emerging market segment (discussed in detail above). Considering leniency also takes into account how broadly the market overlaps with other segments; increasing the number of potential analogies does not enhance familiarity or comprehension. Research on how analogy is used to make sense of new concepts investigates situations where there are one or two analogs to familiar objects (Gick and Holyoak 1983; Bingham and Kahl 2013). As the number of analogies grows large, this can make a new market more confusing. It also indicates there is increased competition between markets. Ruef (2000) shows that low levels of identity clustering fosters new form emergence, but after a point, increasing numbers of similar forms leads to competition that decreases the likelihood that a new 10

13 organizational form will emerge. Lenient market segments are in a saturated area of the domain where there are many alternatives. Many other market segments can plausibly subsume lenient markets. This suggests: Hypothesis 3: Mediators are less likely to continue to report on high leniency market segments. Considering the vertical structure of a market segment, since high-status organizations are more recognizable, salient, and seen as most representative of the market, their connections will be most consequential. Therefore, the effect of leniency should be stronger at the high-end of the market: Hypothesis 4: Mediators are less likely to continue to report on market segments with leniency in their high-status connections, as compared to market segments with leniency in their low-status connections. Empirical Application These hypotheses are tested using market segment reports issued by Gartner, a prominent IT research and analysis organization. A number of organizations emerged in the 1980s and 1990s as intermediaries to help large companies evaluate different IT product offerings. These include Gartner (formerly The Gartner Group), Forrester Research, the Meta Group, the Giga Group, and International Data Corporation (IDC). Gartner is one of the oldest, founded in 1977 by Gideon Gartner. Gartner is generally considered the leading IT research firm (Firth and Swanson 2005). 11

14 As of 2013, Gartner works with over 12,000 organizations in 85 countries, 1 and Gartner clients spend $85,000 - $90,000 on average (Burks 2006). A 2005 academic survey of IT managers found that Gartner was the leading choice for research and analysis, with 77% reporting to be clients (Firth and Swanson 2005), and a 2001 InformationWeek survey found that 90% of companies surveyed used Gartner as an information source (Burks 2006). Gartner prepares reports on the state of the information technology industry. They explain and define market segments, identify new trends, and evaluate and compare vendors within market segments. They sell their reports to IT managers, and often the clients they are advising in one market segment are the firms they are evaluating in a different segment (for example Oracle is evaluated by Gartner and also may be a Gartner client). One of Gartner s key successes was their creating and shaping the enterprise resource planning (ERP) market segment in the early 1990s, which established them as the leading analyst with the cognitive authority as experts in identifying and fostering new IT paradigms (Pollock and Williams 2011). The rise of IT research and analyst organizations is attributed to the increasing amount of complexity and uncertainty in this domain. It is difficult for IT managers to keep up with the rapid innovation in this industry, not to mention expensive to expend the resources to adequately evaluate each solution. In addition, IT purchases are expensive and long-term. IT research firms have been successful at exploiting this uncertainty and, through their reporting, have inserted order into the market, making it more tractable and stable for both customers and vendors (Pollock and Williams 2009). Gartner s magic quadrant reports have been especially effective in ordering the IT domain. A magic quadrant report is issued for a market segment. It defines the segment, describes its future directions, and ranks vendors within the segment along two dimensions using 1 From their Web site, accessed in

15 a 2x2 quadrant. Vendors are ranked in terms of their ability to execute and completeness of vision. There are stark divisions among the four quadrants, with top vendors in the upper right hand quadrant labeled as leaders, middle-ranked vendors in the upper left-hand quadrant as challengers and those in the lower right-hand quadrant as visionaries, and the lowest ranked vendors in the lower left quadrant as niche players. An example magic quadrant is included in figure Insert figure 1 about here ---- Magic quadrant reports have become industry standards and competitors have followed, replicating the format of these reports. Magic quadrants are not only widely used, but also widely criticized in terms of their accuracy and potential bias. However, these criticisms do not appear to have curbed the growing demand for this research (Pollock and Williams 2009). It is uncertain exactly when the first magic quadrant report was issued. Gartner analysts believe they have traced the firs report back to 1986, and it is suspected that it was initially released under a different name (Pollock and Williams 2009). These reports increased in popularity in the mid 1990s. Gartner s electronic records first track magic quadrants reports in 1996, with seven released that year. In 1997, Gartner released its first report defining the magic quadrant methodology. 2 Magic quadrant reports changed the way information technology products and vendors were evaluated. Before magic quadrant reports, IT managers evaluated products based on functionality and cost. Magic quadrant reports made salient ability to execute and completeness of vision. As an analyst describes: In a stable environment you would look at functionality that was pretty much what we were looking at what we said in 97 was change. You need to look at functionality but most vendor packages are mature enough to where there is at least common functionality and we started seeing that trend that we had aging systems and, the point is that you had to look at 2 This is the first methodological definition that can be traced through Gartner s electronic records. In private communications with the author, Gartner has stated that they do not have systematic records of reports released before their electronic records, which begin in

16 buying software as being a partnership with a vendor, and that s a long-term relationship. It s not something short term. And so, the vision of the company do they understand the business of [a specific sector]? Do they know where you were going? and the ability to execute, those are still crucial Now, if I am a Chief Financial Officer I am probably going to look at functionality as being crucial. That s fine. But somebody better look out for the good of the [institution] as a whole, (Pollock and Williams 2009). Gartner periodically describes their methodology in their reports, and these descriptions are remarkably consistent over time. Ability to execute is based on the vendor s financial strength, research and development, marketing and sales capabilities, and alliances. Completeness of vision has four components: 1) does the vendor have a vision or strategic plan? Is this vision in line with industry and sector trends? Does this vision match what Gartner Group believes to be the appropriate strategies for the market sector? Does the vision show complete or enterprise targeting? (Lusher and Braude 1997). Vendors are not only ranked along these continuous dimensions; divisions between quadrants are consequential. Gartner provides guidance as to how they conceive of the four quadrants. The leader executes well today, [and is] well-positioned for tomorrow, the challenger executes well today [and] may dominate a large segment, but does not understand [the] market direction, the visionary understands where the market is going or has a vision of changing market rules, but does not execute well yet, and the niche player either focuses on a small segment and does it well, or is unfocused and does not outinnovate [sic] or outperform others, (Zaffos 2001). The corpus of Gartner s magic quadrant reports provide detail on mediator-constructed classification, for both horizontal distinctions across market segments, and for vertical distinctions ranking organizations within each market segments. This context provides a unique opportunity to investigate how boundaries develop horizontally between market segments, and how the vertical structure of each segment affects this process. Data 14

17 The hypotheses are tested using data on every magic quadrant report released from the earliest reports on record in 1996 through April There are 1,567 of these. Some reports are general descriptions of the magic quadrant process, and so were excluded from the analysis. There are 1,300 magic quadrant reports that rank vendors in a market segment. Sometimes one report will contain more than one quadrant ranking, usually segmented by geography. There are 51 reports that contain more than one magic quadrant figure. In all, there are 1,380 magic quadrants included in the analysis. Figure 2 shows the number of magic quadrants per year Insert figure 2 about here ---- Market segments were identified by the labels used in the titles of the reports. This is in line with the Gartner s focus on labeling and terminology described in detail above. To extract the relevant labels, each quadrant was linked to labels included in the title of the report and in the heading of the figure that presented the quadrant. In most cases these were the same. Text analysis was used to extract relevant labels. Using the Natural Language Toolkit (NLTK) in python, stop-words were removed as well as general terms from this corpus, such as magic quadrant, vendor, Gartner and any dates (e.g. Q201). Then a stemmer was run on all words. Every word and two, three, or four word phrase was extracted from each quadrant title. This resulted in a list of words and phrases, some of which were labels for market segments and others that were noise. To determine which labels referred to a market segment, an n x n matrix of similarity scores between each magic quadrant (over the entire time period) was constructed. Similarity was calculated using cosine similarity between the word/phrase vectors of the two quadrants: similarity A, B =!!!! (1) 15

18 Next, a network plot was created using Gephi where all quadrants were nodes and edges were based on similarity. The plot yielded clusters based on labels for market segments. Clusters were identified using the Blondel et al. (2008) algorithm implemented in the modularity statistic in Gephi. This algorithm assigned every quadrant to a cluster. A list was created for all words and phrases that occurred at least twice in each cluster. This list was then sorted through by hand to identify relevant market labels. There were 335 relevant labels. Most labels identified a product market, like application integration or metadata repository; there were 291 of these. There were also labels for geographic markets like North American (16), for verticals like manufacturing (15), and for sub-segments of the market, like high-end (13). Only the labels for product markets were included in this analysis. A list of labels for the most reported on market segments are included in table 1, with the number of reports on each segment, its first year of appearance, and its last year of appearance Insert table 1 about here ---- Inspecting table 1 shows that some labels, like CRM and ERP have become standard market segments; there are many reports issued on them and they have persisted over time. Other segments have a shorter duration, like learning management systems (LMS). Figure 3 contains a histogram of the duration (in years) for each market segment, which shows that one quarter of all labels are only reported on for 1-2 years and over half do not last longer than 5 years Insert figure 3 about here ---- This gives credence to the idea that Gartner is continually changing their classification, creating new market segments, phasing some out, and changing others. Rather than creating fixed classification that is stable over time, theirs is a dynamic structure, with a small percentage of 16

19 markets becoming stable and continuing through the time of study. This emphasizes the importance of researching what factors influence their continued reporting on market segments. For each magic quadrant, the set of organizations included, and how the organization ranked on each dimension, was extracted. The names of all organizations were extracted using optical character recognition (OCR). The location of the organizations within the quadrant on both dimensions could not be captured using standard OCR techniques. To identify the location, each quadrant was captured as a png file. A program searched the binary data of each png file to locate the black dots that place every organization. Then, a team of research assistants matched the organization s name to its location for each quadrant. A list of unique organizations was extracted, and inspected by hand to determine when the same organization was included with multiple spellings. There are 3,157 organizations in these magic quadrants, and of these, 1,110 are only included in one magic quadrant. A couple of firms are broadly included in many different market segments IBM, Oracle, SAP, Microsoft, and HP are in over 200 magic quadrants. However, this is a long tail; 1,894 organizations are included in between 2 and 20 magic quadrants over this time period. There are 188 organizations that are public or that IPO over this time period. This shows a fair amount of breadth in the organizations covered in Gartner s magic quadrant reports. Independent variables Specialists: To test hypothesis 1 and 2, the number of specialists and percentage of specialists in each magic quadrant was computed. Specialists were defined as organizations that (1) had never before appeared in any Gartner report, or (2) had only appeared in reports on the market segment in the previous year or since a report was last issued on the focal market. High-status specialists 17

20 were those included in the leaders or challengers quadrants, and low-status specialists were those included in the visionaries and niche players quadrants. Although it is somewhat ambiguous whether challengers are higher status than visionaries, challengers rank high on ability to execute and therefore have large market share and prominent customers. Thus, challengers will also be salient representatives of the market segment. Models were run using leaders only as high-status and results are similar. However, effects are most pronounced when the vertical segmentation is grouped into leaders/challengers versus visionaries/niche players. Figure 4 shows the average and standard deviation of the percent of specialists by quadrant Insert figure 4 about here ---- Market segment duration: To test hypothesis 2, the effect of the number of specialists in early versus late stages of the market is captured using an interaction between number of specialists or percent of specialists and the duration of the market segment, measured in years since the first report on that segment was issued. Leniency: leniency is measured as the degree centrality of a market segment in the given year times the percentage of generalist organizations included in the quadrant. The natural log is used since this measure has a skewed distribution:! leniency! = ln %gen!!!! w!! (2) Here, w!" is the weighted number of connections between market segment i and segment j. Connections are based on the number of organizations included in i that are also included in j (in the current year), weighted by the total number of organizations in both segments. Therefore 0 < w!" 1. N is the number of alter labels j that i has nonzero connection to. Because some market segments include a small number of generalists that are connected to many other market segments, degree centrality alone is a noisy measure of how lenient a market s boundaries are. 18

21 This is why the leniency measure multiplies centrality by %gen!, or the percentage of generalist organizations in the market segment. Leniency by status is measured similarly, except that connections between labels (w!" ) were measured based on leader-leader, challenger-challenger, visionary-visionary, and niche player niche player connections. Figure 5 shows a network plot of the all connections among market segments in This plot was created in Gephi, using the Force Atlas algorithm followed by the Fruchterman- Reingold algorithm to optimize distance between nodes. The colors indicate distinct clusters as calculated by the Blondel et al. algorithm (clustering is for illustrative purposes only and does not factor into the analysis). The size of each node represents leniency. All high-leniency market segments are central in this plot, but some of the most central nodes are less lenient than some less central nodes. For example, OLTP is higher leniency than web account management or business intelligence (BI). This reflects that the leniency measure includes the percentage of generalists in each quadrant. In supplementary analyses the results are compared to models that use only centrality. Figures 6 and 7 show network plots of only leader-leader connections and of only visionary-visionary connections, respectively, for all market segments in Comparing these plots shows very different relationships across market segments between high-status organizations as compared to relationships between low-status organizations. The visionary network shows a lot more clustering and fewer connections, whereas the leader network is more interconnected. Importantly, there is little overlap between market segments that are high leniency with respect to leader connections as compared to high leniency segments with respect to visionary connections. This suggests there may be important implications in separately investigating market relationships based on the vertical structure of the market segment. 19

22 Dependent variable The dependent variable is an ordinal (0/1) flag that indicates whether there is a report issued on the market segment in the current year. Control variables A number of controls are included in the model to account for potential alternative explanations. The number of reports that have been issued on the market segment in the previous year indicates how popular it is and how much momentum it has. The time since a report was last issued on the segment captures segments that are becoming obsolete. The duration (or age) of the market segment is also included. Supplementary models include the number of organizations included in the market segment, and the number of organizations split by quadrant level, a Herfindal index on the proportion of firms in the different quadrant levels for each segment, and the number of public organizations included in the segment. Fixed effects are included for each year, and in supplementary analyses market segment fixed effects are included. All independent and control variables are lagged by one year. Model and estimation These data provide information on whether Gartner chooses to report on a market segment in the given year. With these data, the time at which a market segment is dropped (or phased out) is not directly observed. Further, for a number of market segments, Gartner will skip one or two years before issuing a subsequent report. Therefore these data do not lend to a survival analysis. Instead, the hypotheses are tested using a logit model. This models the probability that a report 20

23 will be issued on the market segment in the given year divided by the probability that it will not be issued, as a function of the independent variables and controls: log!!!! = f(βx + ε) (3) Market segments enter the risk set the after the first year they are reported on and remain in the risk set throughout the duration of the analysis. The data are structured in yearly spells, and there are 2219 market year observations. The model is estimated in Stata 12 using logit and xtlogit. Robust standard errors are used, clustered by market segment. Results Table 2 presents descriptive statistics and table 3 presents correlations for this analysis Insert tables 2 and 3 about here ---- Table 4 contains tests of hypotheses 1 and 2. These are logit models on the likelihood that a market segment is included in a report in the current year. Model 1 contains controls only. Market segments that were reported on in the previous year are more likely to be reported on in the current year, which indicates that some markets are more popular than others. There is a negative effect on time since the market segment was last covered, which captures segments that have been phased out. The duration of the market, or the time since it was first covered, does not have a stable effect. Model 2 includes the percent of organizations in the market that are specialists. This shows no detectable effect. However, when this is split up in model 3 into the percent of lowstatus specialists (visionaries and niche players) as compared to high-status specialists (leaders and challengers), there is a positive effect for low-status specialists, significant at p < Model 4 includes the interaction of percent high-status specialists with the time since the market 21

24 was first covered (duration). The interaction has a positive effect, significant at p<0.001, and when it is included the main effect is negative and significant. This shows support for hypotheses 1 and 2. Having higher percentages of specialists in low-status positions within the market leads to a higher probability of coverage at all stages of market maturity, in support of hypothesis 1. Market segments that have the mean percentage of low-status specialists (42%) are 34% more likely to be subsequently be covered, as compared to market segments with no low-status specialists. At the high-end of the market, initially it is detrimental to have a high percentage of specialists. However, as the market matures, this effect reverses. For a market segment that is one year old, having the mean percentage of high-status specialists (23%) leads to a 20% decrease in the probability that it will continue to be covered. At year 5 the effect changes from negative to positive. For market segments that are 6 years old, having the mean number of specialists leads to a 5% increase in the probability that it will continue to be covered, compared to a market with no high-status specialists. Table 5 presents additional tests of hypotheses 1 and 2, including the number of specialists (as opposed to percent). Model 6 shows that the net number of specialists has a positive and significant effect (p < 0.05), and models 7 and 8 show the same pattern of results reported above. This provides additional support for hypotheses 1 and 2. Table 6 presents tests of hypotheses 3 and 4. Models 9 11 include leniency with controls only, and model 12 is the full model. Model 9 shows that leniency has a negative effect, significant at p < 0.05, in support of hypothesis 3. Model 10 includes leniency measured only through leader ties. This effect continues to be negative and significant (p < 0.01), and the coefficient jumps, in support of hypothesis 4. Model 11 includes leniency as measured for all status levels. Leader leniency continues to be negative and significant at p < Niche player 22

25 leniency is negative and significant in this model, although this effect is not robust across models (as shown in model 12; it also does not have a significant effect when included on its own). Model 12 is the full model. Results show continued support for hypothesis 1 and 2, when leniency is included. Leader leniency continues to have a negative and significant effect, in support of hypothesis 4. This model also shows that visionary leniency has a positive effect, significant at p< 0.01, which is robust across most models. Table 7 provides supplementary analyses. Model 13 includes centrality measures instead of leniency measures. Results show a similar pattern of results, although the coefficients loose significance. Comparing model 13 to model 12 illustrates the importance of weighting the number of connections between market segments by the percent of generalists in the market to capture leniency. Markets that contain a few well-connected generalists will score high on degree centrality, even though most of their members have focused identities. Including the percent of generalists in the leniency measure takes into account whether the breadth of a market s connections to other market s are derived from the majority of its members. This captures the leniency of the focal market s boundary. Models 14 and 15 include market segment fixed effects. Model 14 includes the percentage specialists in the market, and model 15 includes the numbers of specialists. Results show that effects of leader centrality and percent high-status specialists are robust across both models. Effects of low-status specialists retain significance when included as the number (but not percent) of specialists. There remains a positive effect of visionary centrality in model 15, at marginal significance, and challenger centrality is positive and significant in these models. This indicates that the positive effects of visionary centrality reported above are likely capturing differences in network structures across market segments, but not within a market segment over 23

26 time. On the other hand, model 14 and model 15 indicate that for a given market, as challenger centrality increases, so does its probability of persistence. This may be due to the fact that large generalist firms tend to enter market segments in the challengers quadrant, and their entry likely coincides with the market becoming more established. Appendix A contains additional supplementary analyses, including controls for the number of organizations in the market, in each quadrant, the number of public organizations, and a Herfindal index of the proportion of organizations across quadrant types. Results reported are robust to the inclusion of these controls. Discussion This paper suggests that structural factors influence the evolution of market segmentation in mediated markets. It shows that both compositional factors, in terms of whether organizational members are specialist or generalist, and relational factors, in terms of leniency, affect whether a market will continue to be covered by analysts. Further, both effects depend on the vertical structure of the market. Market segments are more likely to persist when they contain a large number of specialists at the low-end of the market. For specialists at the high-end, the effect depends on the maturity of the market. Early on, it is beneficial to have generalist market leaders. As the market matures, it becomes more beneficial to have specialist market leaders. This is consistent with the explanation that in early stages of market development, ties to familiar concepts help facilitate sense-making an understanding about a new market. It also supports the idea that high-status organizations are most representative of a market; high-status generalists provide salient links to well-understood concepts. As the market matures, these links are no 24

27 longer helpful facilitate understanding, and specialists at all levels of the market create cohesion and differentiation, which makes a market segment less likely to be displaced. Results also show that relational factors affect market persistence. Leniency, especially as measured by leader connections, is negatively related to the persistence of a market at all stages of market maturity. This supports the idea that when generalist members have a wide breadth of connections to other markets, the market segment is in a saturated area, and there are a number of alternative markets that could replace the focal market. Further, leniency indicates that boundaries are weak and the market may have lost its usefulness for the mediator. This finding also supports the idea that the helpfulness of drawing analogies is limited to a couple of references. As potential analogies grow, more connections lead to more confusion rather than clarification. Surprisingly, results also show that leniency in the visionary network has a positive and significant effect on market persistence. This indicates that market segments with a wide breadth of visionary connections are more likely to persist. Inspection of figures 6 and 7 may provide some clues for interpreting this effect. The network plot for visionary connections is more clustered, and market segments are not broadly connected throughout the industry. In addition, the visionary connections are completely different from leader connections. Market segments with high visionary leniency may indicate that organizational members are building important foundational connections. Gartner suggests that visionaries are the most innovative of the market; perhaps these connections help facilitate new ideas and new inventions. Overall, this study shows that mediated markets do not necessarily result in stable, fixed classification. Rather, mediators continually add new market segments, change existing ones, and phase others out, in order to stay on the cutting edge of new trends and to stay on pace with 25