Dynamic Effects of Service Transition Strategies on B2B

“Dynamic Effects of Service Transition Strategies on B2B Firm Value: Tradeoffs in Sales,

Profits, and Cash Flow” © 2016 Mehdi Nezami, Stefan Worm, and Robert W. Palmatier;

Report Summary © 2016 Marketing Science Institute

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Marketing Science Institute Working Paper Series 2016

Report No. 16-108

Dynamic Effects of Service Transition Strategies on B2B

Firm Value: Tradeoffs in Sales, Profits, and Cash Flow

Mehdi Nezami, Stefan Worm, and Robert W. Palmatier

Report Summary

In the face of declining business and growing pressures from low-cost competitors, many

business-to-business manufacturers are transitioning to services. Yet despite substantial

investments, firms fail to understand the performance effects of adding more service offerings.

In this study, Mehdi Nezami, Stefan Worm, and Robert Palmatier identify three financial-based

mediators linking service ratio (the share of a firm’s revenue generated from selling services) to

firm value. With a longitudinal data set (1998–2013) of 525 manufacturers, they test a

comprehensive framework that explores the effects of these mechanismssales growth,

profitability, and cash flow volatilityon firms’ overall performance at several stages of the

service transition.

They find that although providing services monotonously boosts sales growth, it has a U-shaped

curvilinear relationship with profitability and linearly reduces cash flow volatility. The

performance effects of moving into services also depend on industry- and firm-level factors; for

example, the positive effect of services on sales growth is greater in mature industries. Increasing

the scope of the service business by diversifying across different markets unfavorably moderates

the effect of the transition to services on profitability.

Managerial implications

In the early stages of service transition, managers need to expect a decrease in firm value.

Although tailored offerings enhance customer satisfaction, facilitating cross-selling and repeat

purchase, the substantial costs associated with such strategies reduce profitability. In later stages,

the mediating roles of sales growth and cash flow volatility gain strength. In the payoff stage, all

three mechanisms contribute positively to firm value

Their study also suggests that service ratio is a valuable metric that financial analysts can use to

assess a firm’s potential sales growth, profitability, and cash flow volatility as well as overall

effects on firm valuations.

Mehdi Nezami is a doctoral candidate in marketing at HEC Paris / Michael G. Foster School of

Business, University of Washington. Stefan Worm is Assistant Professor, BI Norwegian Business

School. Robert W. Palmatier is Professor of Marketing and John C. Narver Chair in Business

Administration, Michael G. Foster School of Business, University of Washington.


Dynamic Effects of Service Transition Strategies on B2B Firm Value: Tradeoffs in Sales, Profits, and Cash Flow

Many business-to-business (B2B) firms, from Oracle to Lockheed Martin, have added

services to solidify their customer relationships and enhance firm value. According to the U.S.

Census Bureau (2013), B2B services (e.g., engineering, computer systems design) account for

10% of U.S. gross domestic product (GDP) and grew by approximately 65% in the past decade.

Yet, despite their substantial investments in services, many companies still fail to grasp the

performance implications of adding services (Suarez, Cusumano, and Kahl 2013), suggesting

that “both researchers and practitioners need to better understand how service and marketing

efforts affect financial statements and market valuation” (Anderson 2006, p. 587). The

conflicting results that derive from prior research into the effectiveness of B2B service strategies

might arise because previous studies focus on single performance metrics or ignore differential

effects across the stages of service transition (e.g., Eggert, Thiesbrummel, and Deutscher 2015;

Homburg, Fassnacht, and Guenther 2003). In turn, we seek to improve understanding of the

dynamic effects of B2B firms’ service transition strategies on firm value, by decomposing the

effects of three financial-based mediating mechanisms while also accounting for differences

across transition stages.

Specifically, we identify three financial-based mediators linking service ratio, or the share

of a firm’s revenue generated from selling services, to firm value. First, adding services enhances

sales growth, in that firms provide customized offerings that fulfill customers’ unmet needs and

thereby gain a new source of revenue. The close collaboration and joint problem solving

undertaken during these service deployment initiatives should engender higher levels of

customer satisfaction (Fang, Palmatier, and Steenkamp 2008), which encourages cross-selling

and repeat purchases (Anderson, Fornell, and Lehmann 1994). Second, moving into services has

a nonlinear impact on profitability, according to the transition stage. In particular, operational

inefficiencies (Rust and Chung 2014) and investments in service-related resources and

capabilities (Eggert et al. 2014) impose substantial costs on firms and reduce their profitability

initially, but delivering higher value through service provision later enables firms to create

competitive advantages and enhance their profitability (Ulaga and Reinartz 2011). Third,

services reduce cash flow volatility by increasing customers’ switching costs and locking them in


for a longer period. The more stable customer base that results is less vulnerable to competitive

intensity and environmental shocks, yielding a comparatively predictable, smooth cash flow

(Anderson and Sullivan 1993; Srivastava, Shervani, and Fahey 1999). Overall, the net effect of

service transition strategies on firm value thus depends on the aggregated mediation due to sales

growth, profitability, and cash flow volatility, contingent on transition stages, as well as on firm-

and industry-level factors.

With a panel data set of 525, publicly traded, U.S. B2B manufacturers from 1998 and 2013,

we examine these performance effects. The firms in our sample belong to a wide range of

manufacturing industries and account for 25% of U.S. GDP. In studying how sales growth,

profitability, and cash flow volatility connect manufacturers’ service ratio to their firm value, as

moderated by context factors (Figure 1), we take particular care to overcome econometric

challenges in our estimation. We thus use system generalized method of moments (GMM)

dynamic panel data methods (Arellano and Bover 1995; Blundell and Bond 1998), augmented

with an external instrumental variable, to account for potential endogeneity in firms’ transition to

services.

This research contributes to services in industrial markets in three ways. First, Fang,

Palmatier, and Steenkamp (2008) establish a link between services and firm value, but without

exploring the mediating mechanisms whereby this effect occurs. We provide a richer theoretical

explanation, by disaggregating and testing the effects of three different mechanisms that connect

service transition strategies to firm value. Each of these mechanisms also has a different

functional form. Moving into services expands sales growth following a convex, monotonously

increasing function, but it has a U-shaped, curvilinear relationship with profitability, and it

reduces cash flow volatility linearly. These different functional forms explicate the net effect of

shifting to services, such that in the early stages (service ratio < 20%), a one percentage-point

increase in service ratio, on average, enhances sales growth by 9%, but it reduces profitability

and cash flow volatility by 22% and 1%, respectively. After service sales reach a critical level

(approximately 23% of sales), the improved sales growth and decreased cash flow volatility

overcome the still negative profitability outcomes. When service sales reach approximately 45%,

even the effect of the profit mechanism on firm value becomes positive. Thus, in later stages

(service ratio > 45%), a one percentage-point increase in the service ratio, on average, enhances


sales growth and profitability by about 3% and 26%, respectively, and it reduces cash flow

volatility by 1%, such that all three mechanisms contribute positively to firm value.

Second, the net effect of service transition strategies on firm value reflects the sum across

multiple mechanisms; with this study, we isolate the factors that enhance or suppress each

mechanism. Our results show that industry- and firm-level factors have differential effects. For

example, industry maturity, in the form of product commoditization and slowing market growth,

positively moderates the effect of shifting to services on sales growth. Specifically, a one

percentage-point increase in the service ratio, on average, improves the sales growth of firms

operating in mature industries by nearly 3% more than that for those operating in growth

markets. Expanding the scope of the service business, or the extent to which a firm's service

business is diversified, instead aggravates the initial negative effect of the service transition on

profitability and suppresses its later positive influences. The profit loss caused by a one

percentage-point increase in the service ratio thus averages 1% less for firms with a narrower

service scope, as a firm just begins to transition to services. Later on though, a one percentage-

point increase in the service ratio, on average, enhances the profitability of these firms 15% more

than for firms with diversified businesses.

Third, the complex linkages among service ratio and firm value, as mediated by sales

growth, profitability, and cash flow volatility, with their different functional forms, make it

difficult to understand their relative effects across different stages of a firm’s transition to a

service-based business. Therefore, we offer clear managerial insights into the overall effects on

firm value at different levels of the service ratio, by decomposing the indirect effect transmitted

through each mechanism in a series of additional analyses. The trade-offs reveal three service

transition stages. In the exploration stage, characterized by substantial investments in new

resources and capabilities, the negative indirect effect through profitability overshadows the

effects of both other mechanisms and reduces firm value. Profitability drives an average of 70%

of the effect of the service ratio on firm value. In the learning stage, firms begin to build the

relevant capabilities to manage their service business, which gradually improves the impact of

shifting to services on profitability. Sales growth accounts for 33% of the net effect on firm value

in this stage, and the corresponding indirect effects of profitability and cash flow volatility are

41% and 26%, respectively. Finally, in the payoff stage, increasing the service ratio enhances

firm value by improving sales growth and profitability and reducing cash flow volatility. In this


stage, all three mediators make positive contributions to firm value and are more balanced, with

indirect effects of the linkage of service ratio to firm value of 48%, 36%, and 16%.

Understanding Service Transition Strategies

Effect of Service Transition Strategies on Firm Performance

Many B2B manufacturers add services in response to declining business and competition

from offshore, low-cost product competitors (Palmatier, Stern, and El-Ansari 2014). Lockheed

Martin, for example, drove approximately 24% of its total revenues in 2010 from services, up

from approximately 14% in 2000. Prior research refers to the shift from products to services as

“service transition strategies” (Fang, Palmatier, and Steenkamp 2008, p. 2), a well-documented

strategic redirection that reflects firms’ intention to lock in customers and generate additional

sources of revenue from their large installed customer bases. Services also enable firms to

differentiate their offerings and combat margin pressures, even as profits from equipment sales

decline in increasingly competitive markets (Wise and Baumgartner 1999).

The primary reason why firms add services reflects the expected consequences. As Tuli,

Kohli, and Bharadwaj (2007) argue, customers perceive customized service offerings as

relational processes, because they entail close interactions with suppliers. Increased customer–

seller interactions make intangible relationships more valuable to customers while also

engendering more trust in the company, a key antecedent of customer loyalty (Homburg,

Fassnacht, and Guenther 2003). Due to their intangibility and the simultaneity with which they

are produced and consumed, services also are difficult and costly to evaluate, which limits

customers’ motivation to try other service offerings, locks them in, and deters their exit (Blut et

al. 2014; Nayyar 1993). Moreover, the increasing commoditization of goods drives

manufacturing firms to investigate services as a promising means of differentiation, because they

already may have unique access to the specific resources and capabilities needed to combine

services with their products in industrial markets (Ulaga and Reinartz 2011). Firms that hold

these assets are better positioned to create an inimitable competitive advantage.

Yet moving into services also may have some negative effects, which typically become

manifest in the early stages of the transition. First, developing the processes, culture, leadership,

and structures needed to shift to services may require costly organizational changes and create

internal conflicts (Neu and Brown 2005). Second, customization is crucial for successful service


offerings, but it may result in lower operational efficiency (Rust and Huang 2014). Third,

investing in the necessary service-specific resources and capabilities imposes substantial costs on

firms (Eggert et al. 2014). Establishing these competencies even may require a firm to sacrifice

the resources it devotes to its non-service business, which may degrade its core performance.

These benefits and costs of service transition strategies likely link to overall firm value

through three financial-based mechanisms: sales growth, profitability, and cash flow volatility

(Table 1). However, extant research typically focuses on one financial-based mechanism at a

time, which prevents a clear view of the relative or net effects across these mechanisms.

—Insert Table 1 about here—

Sales growth. Sales growth provides a crucial indicator of financial health, and annual

reports frequently include statements about sales targets. Financial analysts also use sales growth

as a valuation metric; firms with greater sales growth earn higher valuations (Brailsford and

Yeoh 2004). Prior studies generally indicate a positive link between moving into services and

sales growth. For example, Antioco et al. (2008) argue that firms can increase their revenue by

providing customized service offerings that fulfill customers’ unmet needs and boost their

satisfaction. Eggert et al. (2014) find that adding services helps firms expand their sales by

creating sustainable competitive advantages and differentiating their offerings. Thus, sales

growth should represent a positive link between the shift to services and firm value.

Profitability. Businesses act in the interests of their profit-seeking stockholders, so profit

maximization, which increases investors’ income, is a primary goal of business. Extant literature

provides mixed findings about the effect of a service transition on profitability: Homburg,

Fassnacht, and Guenther (2003), Eggert et al. (2014), and Aas and Pedersen (2011), respectively,

report significantly positive, negative, and no association between services and profitability.

These conflicting findings might arise because the link between services and profitability

actually depends on the stage of the transition. Investments in newly required resources and

capabilities reduce profitability early on, but the competitive advantage obtained from leveraging

these assets enables firms to increase their profitability later. Therefore, we predict that moving

to services has a U-shaped, curvilinear effect on profitability.

Cash flow volatility. A firm’s cash flow volatility reflects the degree of variation and

uncertainty in its cash flow. Fluctuations in cash flows are driven, for example, by the

unpredictability of demand or by industry rivalry. Firms with more volatile cash flows likely


suffer periods of cash shortfalls that influence their investment policy, by increasing both the

need for and the costs of raising external capital (Minton and Schrand 1999). Shareholders also

perceive them as riskier (Allayannis and Weston 2006). Previous research generally emphasizes

that B2B services lock customers in and ensure smoother revenue streams, but no direct

empirical evidence links such offerings to the volatility of firms’ cash flows.

Multiple Mediators and Dynamics in Service Transition Strategies

Our review of extant literature highlights two fundamental drawbacks in prior empirical

studies of the effects of service transition strategies on firm value. First, most studies focus on a

single financial outcome to evaluate the effectiveness of this shift. Yet, transitioning to services

may influence multiple dimensions of corporate financial performance simultaneously. To

understand the net effect of these service transition strategies, we need empirical research that

can shed light on all potential financial outcomes in a single, analytical framework (Eggert et al.

2014). Second, the strength and direction of the effect of service transition strategies on different

financial outcomes may depend on the stage of transition and vary as a firm builds necessary

capabilities and implements the required organizational changes. In other words, the effect of

adding services is dynamic and unfolds as the firm progresses in its implementation of this

service strategy. Ignoring this dynamism likely is the source of the contrasting findings in prior

research. For example, Eggert, Thiesbrummel, and Deutscher (2015) argue that adding services

demands substantial investments, such that it has negative impacts on profitability, but Homburg,

Fassnacht, and Guenther (2003) suggest that an emphasis on services enables firms to establish

high-quality customer relationships that enhance their profitability. Accounting for the stage of

service transition thus appears critical for determining the overall effect of service offerings on

firm performance.

Conceptual Model and Hypotheses

In our conceptual model, we capture the simultaneous effects of adding services on different

financial outcomes by decomposing the net effect of the service transition on firm value (proxied

by Tobin’s q), as an indicator of firms’ expected long-term performance, into three mediating

mechanisms (sales growth, profitability, and cash flow volatility). In addition, we account for the

dynamic nature of this transition with the service ratio, or the portion of the firm’s total revenue

that results from selling services, as a measure of the firm’s progress in implementing its shift to


services (Fang, Palmatier, and Steenkamp 2008). We also recognize that the firm’s environment

and firm-specific strategic implementation could fundamentally influence the performance

impact of providing services. By examining the moderating roles of variables that operate

uniquely across each of these mechanisms, we provide a robust test of our model’s nomological

validity. In addition, we draw on the resource-based view (RBV) (Barney 1991; Kozlenkova,

Samaha, and Palmatier 2014), which pertains to how the fit between a firm’s valuable and

inimitable resources, its strategy, and its industry setting determines its performance. That is,

with the RBV, we can investigate how providing services influences the stock and utilization of a

firm’s resources and capabilities and thereby affects its performance as it progresses along its

service transition.

Linking Service Transition Strategies to Sales Growth

Effect of service ratio on sales growth. Fulfilling customers’ unmet needs by providing

customized services helps firms expand their market and create a new source of revenue. Close

collaboration and joint problem solving during the delivery of these offerings engender higher

levels of trust and create a deeper understanding of customers’ requirements. The co-developed

offerings better meet customers’ idiosyncratic requirements and enhance their satisfaction

(Antioco et al. 2008). These satisfied, loyal customers in turn generate benefits for firms beyond

their current transaction, because satisfied customers likely repurchase or express increased

receptivity to cross-buying (Gruca and Rego 2005).

Delivering services also allows manufacturers to establish a competitive advantage, because

their tailored product offerings, augmented with services, enhance their value proposition. Not

all competitors can access the specific resources and capabilities required to combine products

with services (Ulaga and Reinartz 2011), so adding services increases the inimitability and

distinction of the focal manufacturer’s offerings. In addition, the delivery of some services (e.g.,

maintenance, support) often relies on long-term contracts. The contractual commitment inherent

to these transactions enables firms to remove some portion of the market from the competitive

arena (Bharadwaj, Varadarajan, and Fahy 1993). In summary, the enhanced value proposition

and the inimitable competitive advantage obtained from providing services drive market share

and increase the sales growth rate.

H1a: The service ratio positively affects sales growth.


Moderating effect of industry maturity. An increase in industry maturity, or the extent to

which market growth slows and products become commoditized, makes shifting to services even

more appealing. Growth through product sales is more difficult to both earn and retain in mature

industries, especially because supply in these industries often exceeds demand. In addition,

technology commoditization in mature industries limits manufacturers’ opportunities to

differentiate themselves merely through (tangible) products, such that customers can easily

switch to other suppliers (Aaker and Day 1986). But transitioning toward services can help firms

mitigate these negative effects, because the additional revenue generated from selling services

offsets the slow growth in their core manufacturing sectors (Sawhney, Balasubramanian, and

Krishnan 2003). Moreover, the intangibility and heterogeneity of services makes them less

susceptible to commoditization, and the special assets needed to develop and deliver these

offerings make them inimitable. For example, excellent sales force capabilities are hard for

competitors to imitate. The differentiation achieved by adding services thus enables firms to

reduce the substitutability of their offerings and increase customers’ switching costs.

H1b: The positive effect of the service ratio on sales growth is greater in mature

industries.

Linking Service Transition Strategies to Profitability

Effect of service ratio on profitability. Shifting to services has a negative effect on

profitability in early stages (low levels of service ratio). Cross-functional coordination is a

prerequisite for the successful implementation of service transition strategies (Neu and Brown

2005), but in the early stages, disagreements over organizational goals and means may lead to

organizational conflicts and hamper interdepartmental collaboration. To resolve such conflicts,

firms likely incur significant coordinating costs. In addition, the resources and capabilities for

industrial markets are geared toward manufacturing (Eggert et al. 2014). Services, however,

inherently require different skills and competencies, such that the firm must make substantial

investments in new resources and capabilities (Nijssen et al. 2006). These investments could

even cannibalize those in production-related assets or organizational routines. Finally, whereas

manufacturers typically focus on increasing efficiency, through product and process

standardization, services are often customized to boost customer satisfaction (Rust and Huang

2014). This need for customization then hinders economies of scale, by preventing mass


production and lowering process efficiency. In the light of the necessary investments, the

decrease in efficiency may result in reduced profitability.

These negative effects likely persist until firms make the necessary organizational changes

and achieve the required competencies and capabilities. After this critical point, manufacturers

can learn how to manage their operations efficiently and economize on the costs of providing

services. Furthermore, adding services should enhance the firm’s competitive advantage and

alleviate the negative impacts of fierce competition, usually manifested in price pressures and

declining profitability. Similarly, delivering higher value by offering tailored services increases

customers’ satisfaction, which heightens switching costs and lowers price sensitivity (Anderson,

Fornell, and Lehmann 1994). Thus, providing services may minimize investments in customer

retention and enable firms to charge higher prices, both of which should enhance profit margins.

In summary, we predict a U-shaped curvilinear effect on profitability, such that the increased

costs to implement organizational changes and establish new resources and capabilities reduce

profitability initially, but when the competitive advantages and customer satisfaction obtained

from delivering services outweigh these disadvantages, firms can enhance their profitability.

H2a: The service ratio has a U-shaped, curvilinear effect on profitability; decreasing in

early stages, then becoming increasingly positive in later stages.

Moderating effect of service business scope. The service business scope, or the extent to

which a firm's service business is diversified across various industries (Nayyar 1992), is

pertinent to the effect of moving into services on profitability. Diversifying service businesses

magnifies the negative impact of adding services in the early stages, because sustainable

competitive advantages that rely on service-led growth strategies entail the development of

customized, specialized offerings to address customers’ idiosyncratic needs. Developing such

offerings demands a substantial accumulation of skills and competencies, specific to each

industry. Firms with a broader service business scope thus will incur more investment costs to

develop service-related resources and capabilities. The specificity of these assets also limits

opportunities to leverage them in other industries, which reduces the firm’s efficiency and

profitability (Montgomery and Wernerfelt 1988). Similarly, a more diversified service business

attenuates the positive effect of adding services on profitability in later stages. The heterogeneity

of the technical challenges that firms face when they adopt more diversified service businesses


means they have trouble exploiting learning or modularity benefits (Weigelt and Sarkar 2009).

Moreover, dispersing limited resources across a diverse set of markets limits their ability to build

strong relationships with customers, as is necessary for developing tailored, customized

offerings.

H2b: Expanding the scope of the service business magnifies the initial negative impact of

the service ratio on profitability and reduces its positive effect in later stages.

Linking Service Transition Strategies to Cash Flow Volatility

Effect of service ratio on cash flow volatility. Service offerings shield firms from

fluctuations in their cash flow. First, knowledge derived from coproduction and joint problem

solving during service delivery helps them predict market trends or shifting customer

preferences. Firms that deploy this knowledge are better positioned to match customers’ needs,

such that customers remain loyal to them (Anderson, Fornell, and Lehmann 1994). Second,

services deliver added value to customers, such as by increasing their operational efficiency or

lowering their risks. Yet their intangibility and simultaneity means these services are difficult

and costly to evaluate. This combination of higher perceived value and the difficulty of trying

other offerings magnifies customers’ switching costs. To economize, customers thus remain

loyal to their current service provider and avoid exit (Nayyar 1993). Third, service offerings

encourage repeated transactions or even long-term contracts, so the resulting revenues, such as

those earned from maintenance and repair services, represent a persistent cash flow that might

last long after the product has been sold or discontinued (Potts 1988). This stable customer base

in turn is less vulnerable to competitive intensity and environmental shocks, offering a smoother

stream of future revenue (Anderson and Sullivan 1993; Srivastava, Shervani, and Fahey 1999).

H3a: The service ratio negatively affects cash flow volatility.

Moderating effect of industry turbulence. A turbulent industry is marked by an unstable

economic climate, changing customer needs, and ongoing technological changes. Determining

demand in such volatile markets requires access to accurate, timely information about customers’

needs and preferences and competitors’ offerings. Knowledge obtained from close interactions

with customers during service provision then represents a more valuable resource in turbulent

markets (Fang, Palmatier, and Steenkamp 2008). From a customer perspective, technological


uncertainty in turbulent markets also induces higher levels of risk, associated with the

compatibility of technological standards and the availability of upgrades. To cope with this

uncertainty, customers favor suppliers that guarantee outcomes and assume some level of risk by

providing services (Ulaga and Reinartz 2011). This risk transfer then creates greater economic

incentives for customers to remain loyal, engage in future transactions, and adopt suppliers’

offerings more quickly, leading to more repurchases and a steadier stream of revenue in these

turbulent markets. Finally, in spreading its resources between manufacturing and services, the

firm’s risk–return profile alters, because its diversified business portfolio limits exposure to the

risk caused by volatile markets (Chang and Thomas 1989), such that it can compensate for losses

in one line of business with growth in a different line.

H3b: The negative effect of the service ratio on cash flow volatility is greater in turbulent

industries.

Effects of Sales Growth, Profitability, and Cash Flow Volatility on Firm Value

Prior literature in finance and accounting explores the relevance of sales growth,

profitability, and cash flow volatility as drivers of firm value. For example, Davis (2002) finds

that revenue announcements are closely associated with three-day market returns, because

generating more sales over time is fundamental for long-term viability. Stagnant firms may

produce profit in the short term, but they cannot attract new investors. Similarly, Varaiya, Kerin,

and Weeks (1987) and Cho and Pucik (2005) find positive relationships between firm

profitability and firm value. More profitable businesses reward investors with larger returns on

their investments, so they attract further funds from investors enticed by this promise. Firms also

can use their profits, as internal sources of financing to expand their businesses. Finally,

corporate risk management theory suggests that stockholders assign a premium to firms that

maintain smooth, stable cash flows, as volatility in cash flow increases firms’ dependence on

costly external financing to get them through their likely cash shortfalls (Froot, Scharfstein, and

Stein 1993), and limits their ability to invest in capital expenditures (Minton and Schrand 1999).

H4: Sales growth has a positive effect on firm value.

H5: Profitability has a positive effect on firm value.

H6: Cash flow volatility has a negative effect on firm value.


Methodology

Sample

To test our hypotheses, we compiled a panel data set of publicly listed B2B manufacturers

in the United States from multiple sources. The sample consists of all B2B firms in

manufacturing industries for which we found matching data in the COMPUSTAT Fundamental

(Quarterly and Annual) databases and COMPUSTAT Business Segments database. Specifically,

we obtained accounting data from the Fundamentals databases, and we drew on the

COMPUSTAT Business Segments database to construct the service ratio as our objective

measure of the service transition stage (Fang, Palmatier, and Steenkamp 2008). Merging these

data sources yielded a panel of 4,640 firm-year observations of 525 B2B manufacturers over a

16-year period (1998–2013; average panel length = 11.8 years). The sample included firms with

primary standard industrial classification (SIC) codes of 22, 24, 26-30, and 32–39, covering a

wide range of manufacturing industries (e.g., chemicals and allied products, primary metal

industry, industrial and commercial machinery, computer equipment).

Operationalization

Table 2 summarizes the construct definitions and operationalization. We used Tobin's q as a

capital market–based measure of firm value (e.g., Germann, Ebbes, and Grewal 2015). Tobin’s q

is forward looking, adjusts for expected market risk, captures long-term performance, and can be

used across industries. We compute sales growth as the logged ratio of sales at time t to sales at

time t – 1 (Tuli, Bharadwaj, and Kohli 2010). We operationalize profitability as the operating

margin (or return on sales), calculated as the operating income divided by sales. Unlike net

margins, operating margins are not influenced by other financial factors (e.g., taxation) that do

not correspond to firms' operating activities (Suarez, Cusumano, and Kahl 2013). For cash flow

volatility, we use the coefficient of variation of quarterly operating cash flow per share over a

two-year period (Allayannis and Weston 2006; Minton and Schrand 1999). To operationalize

service ratio, we use the COMPUSTAT Business Segments database, which provides

disaggregate sales revenue figures for firms’ operating business segments. Following Fang,

Palmatier, and Steenkamp (2008), we classify business segments into service and non-service, on

the basis of their 4-digit SIC codes. For example, a business segment consists of a service when

the description of the segment is “computer programming services” with an SIC of 7371 or


https://www.osha.gov/pls/imis/sic_manual.display?id=148&tab=description

“information retrieval services” with an SIC code of 7375. In contrast, a business segment

consists of a product when the description of the segment is “surgical and medical instruments

and apparatus” with an SIC of 3841 or “construction machinery and equipment” with an SIC

code of 3531. Finally, we compute a firm’s service ratio in a given year as the sum of its

revenues from service business segments, divided by its total revenue.

To measure industry maturity, we use Suarez, Cusumano, and Kahl’s (2013) approach,

which looks at the evolution of industry density (i.e., number of firms operating in an industry).

As long as an industry is in the growth stage, its density increases while it keeps attracting new

entrants. However, the onset of maturity occurs in tandem with a shakeout in the number of

remaining competitors, as firms start exiting the market (Agarwal, Sarkar, and Echambadi 2002).

We identify the onset of maturity as the peak of industry density. Denoting the density of

industry i in year t by densityit, we compute industry maturity as (-1/densityit) × 100 for the years

before the onset of maturity and as (1/densityit) × 100 for the years after its onset. Thus, our

measure is negative and increasing before the onset of maturity but positive and increasing

thereafter. To operationalize a firm’s scope of service business, we use an entropy measure of

service business diversification (Jacquemin and Berry 1979; Palepu 1985). For each firm in a

given year, we first divide the revenue of each of its service segments by its total service

revenue. Then, we multiply each ratio by the natural logarithm of its inverse. To compute the

entropy measure, we sum up these weighted ratios. The resulting entropy measure of

diversification takes into account both the number of service segments in which a firm operates

and the relative importance of each segment for the firm’s total service revenue. Industry

turbulence reflects the coefficient of variation of the total quarterly market volume (in sales

revenues) at the 4-digit SIC level over a two-year period (Fang, Palmatier, and Steenkamp 2008).

To rule out rival explanations, we also control for factors that might affect our dependent

variables. Specifically, as controls in each model, we include: (1) past performance, captured by

the lagged dependent variable; (2) firm size, operationalized as logged sales; (3) financial

leverage, proxied by the ratio of long-term debt to total assets (Aivaziana, Ge, and Qiu 2005); (4)

R&D intensity, or the ratio of R&D expenditures to total assets (Cui and Mak 2002); (5)

liquidity, using the current ratio as a proxy (Tuli and Bharadwaj 2009); (6) capital expenditure,

normalized by sales (Allayannis and Weston 2006); (7) dividends payout ratio, computed as the

ratio of cash dividends to a firm’s market capitalization (Tuli and Bharadwaj 2009); (8) market






size, measured by the log of total sales by firms with the same 4-digit SIC code; (9) industry

profitability, or the average operating margin of firms in the same industry; (10) competitive

intensity, computed as 1 minus the Herfindahl index (Black and Strahan 2002); and (11) year

dummies. In Table 3, we provide descriptive statistics and correlations for all the variables.

Model and Estimation Approach

We estimated the following equations to disentangle the mechanisms mediating the impact

of transitioning toward services on firm value:

(1) SGit = α10 + α11 SGi(t-1) + α12 SRit + α13 SRit2 + α14 SRit × Ind_MATit + α15 SRit

2 ×

Ind_MATit + α16 Zit + η1i + ԑ1it;

(2) PROFit = α20 + α21 PROFi(t-1) + α22 SRit + α23 SRit2 + α24 SRit × SCOPEit + α25 SRit

2 ×

SCOPEit + α26 Zit + η2i +ԑ2it;

(3) CFVit = α30 + α31 CFVi(t-1) + α32 SRit + α33 SRit2 + α34 SRit × IND_TURBit + α35 SRit

2 ×

IND_TURBit + α36 Zit + η3i + ԑ3it; and

(4) FVit = α40 + α41 FVi(t-1) + α42 SRit + α43 SRit2 + α44 SGit + α45 PROFit + α46 CFVit + α47 Zit

+ η4i + ԑ4it,

where SG is sales growth; PROF denotes profitability; CFV represents cash flow volatility; FV is

firm value; SR and SR2 are the linear and squared terms of the service ratio, respectively;

Ind_MAT represents industry maturity; SCOPE is service business scope; and IND_TURB is

industry turbulence. The vector Z in each model represents the control variables.

We measure cash flow volatility and industry turbulence for each firm-year observation over

eight quarters (i.e., two successive years). If we relied on single years as a time unit in our panel

estimation, the measures would suffer from severe serial correlation, so to avoid this problem,

we used independent sample periods. By including two years as the time unit for our panel, we

ensure there is no overlap in data for consecutive time periods (Allayannis and Weston 2006).

For example, if t covers 2009 and 2010, then t + 1 covers the years 2011 and 2012, and so forth.

For cash flow volatility and industry turbulence measured over eight quarters, we adopt the


average values over the same eight quarters for all other variables (Tuli, Bharadwaj, and Kohli

2010). This approach ensures an optimal temporal alignment of the measures within an

estimation period.

Two potential sources of endogeneity arise in our models. First, in specifying the linear

dynamic panel data models, each equation’s error term likely includes time-invariant unobserved

variables ηi. These variables hardly change over time, such that they correlate with the lag of the

dependent variable. By first-differencing each equation, we can remove ηi, but then the

differenced lagged dependent variable in the transformed equation will correlate with the

differenced error. Failing to account for this endogeneity would lead to biased estimates. Second,

the service ratio could be endogenously determined, if time-varying unobserved variables that

affect a firm’s financial performance (e.g., sales force capability, value-creation know-how, top

management incentives) also relate to its shift toward services.

To address these potential sources of endogeneity, we employed a Blundell and Bond

(1998) dynamic panel estimation, or a system generalized method of moments (GMM), which

relies on the panel nature of the data and uses lags and lagged differences of the endogenous

variables, along with the exogenous variables, as instruments in the level and transformed

models. Arellano and Bond (1991) suggest that, under the assumption that errors are not serially

correlated, lagged values are suitable instruments for transformed endogenous variables. In

addition, Arellano and Bover (1995) argue that if errors are serially uncorrelated, then it also is

possible to transform the lags to make them exogenous with the fixed effects and use them as

instruments for the levels. Blundell and Bond’s (1998) system estimator (system GMM)

specifies the system of stacked regressions and exploits the new moment conditions for the data

in level, while retaining Arellano and Bond’s (1991) original conditions for the transformed

equation.

In addition to panel-internal instruments, system GMM can integrate external instruments to

improve estimation robustness (Suarez, Cusumano, and Kahl 2013). We rely on Berry,

Levinsohn, and Pakes’s (1995) identification and instrumentation strategy, in which suitable

instruments for an endogenous variable get extracted from data available for other observations

that belong to the same category (see Germann, Ebbes, and Grewal 2015 for a recent example).

Analogously, we use the mean service ratio among peer firms with the same primary 4-digit

SIC code as an external instrument for the service ratio. A suitable instrument must satisfy both


an instrument relevance condition (i.e., it predicts the focal firm’s service ratio) and the

exclusion restriction (i.e., it does not correlate with the error term). We argue that industry

characteristics and market conditions are key determinants of firms’ strategic choices, such that

firms operating in the same market likely respond to similar market conditions. An industry’s

overall move toward services thus offers an appropriate predictor of the focal firm’s shift. For the

exclusion restriction, Germann, Ebbes, and Grewal (2015) argue that unobserved firm-level

factors (e.g., customer intimacy) are embedded in a firm’s organizational processes and therefore

are difficult for peer firms to observe. Even if these factors were easily observable, it is unlikely

that all competitors react to them collectively. Therefore, our instrument should be uncorrelated

with unobserved firm factors in the error term. Finally, the inclusion of year dummies and

industry-level controls in our models makes our instrument exogenous to the error term, because

it accounts for industry-level factors or shocks that may trigger service shifts by a firm and its

peers. These considerations suggest that our external instrument is suitable and valid.

Results

Table 4 contains the estimation results for Equations 1–4. Across these models, we fail to

reject the null hypotheses for Arellano and Bond’s (1991) test of autocorrelation and Hansen’s

(1982) test of overidentification, which suggest an appropriate model specification and selection

of instruments.

In Model 1, we replicate Fang, Palmatier, and Steenkamp’s (2008) finding of a U-shaped,

curvilinear effect of service transition strategies on firm value. The significant negative linear

term (β = -2.36, p < .05) and significant positive quadratic term (β = 5.11, p < .01) for the service

ratio indicate that it initially reduces firm value. However, beyond a service ratio of 23%, the

effect of growing service revenues becomes increasingly positive. Then, to test H1–H3, we ran

Models 2–7 in a stepwise fashion: first without and then with the interaction terms. In Model 2,

we find evidence of a positive effect of the service ratio on sales growth in H1a. The linear term

of the service ratio is insignificant (β = -.72, n.s.), but its quadratic term is positive and

significant (β = 1.74, p < .05). The functional form then is convex and strictly monotonically

increasing. In Model 3, we add industry maturity as a moderator and find that the quadratic term

of the service ratio remains significant (β = 1.14, p < .05). In addition, the interaction of the

linear term of the service ratio with the moderator is positive and significant (β = .05, p < .05), in


line with our prediction in H1b that the effect of service ratio on sales growth is more pronounced

in mature industries.

With Model 4 we test the U-shaped effect of the service ratio on profitability. The linear

term is negative and significant (β = -1.9, p < .01), but its quadratic term is positive and

significant (β = 2.03, p < .01), in support of the U-shaped relationship we predicted in H2a. In

early stages, moving into services decreases profitability, but this effect becomes increasingly

positive beyond a service ratio of 46%, where the curve reaches its minimum. In Model 5, we

add the interaction terms for service business scope and find stable results for the linear and

quadratic terms of the service ratio (β = -.78 p < .05; β = 1.13, p < .05). The interaction of the

quadratic service ratio term with service business scope is negative and significant (β = -11.46, p

< .05), in support of H2b: Service business scope negatively moderates the effect of the service

ratio on profitability.

In Model 6, we examine the effect of the service ratio on cash flow volatility. The

significant negative linear term of service ratio (β = -4.57, p < .05) and its insignificant quadratic

term (β = 5.01, n.s.) imply that transitioning to services linearly reduces cash flow volatility,

confirming our prediction in H3a. However, when we added the interaction terms for industry

turbulence in Model 7, we did not find support for H3b.

Finally, Model 8 contains all three mediators. Sales growth (β = .88, p < .05) and

profitability (β = .52, p < .05) significantly enhance firm value, and cash flow volatility

significantly reduces it (β = -.08, p < .05), in line with our predictions in H4, H5, and H6.

Moreover, after controlling for service ratio’s direct effect on firm value in Model 9, the effects

of sales growth (β = .5, p < .05), profitability (β = .46, p < .01), and cash flow volatility (β = -.13,

p < .01) remain significant. The coefficients of the linear (β = -.54, n.s.) and quadratic (β = 2.72,

n.s.) terms of the direct effect of service ratio are insignificant. Sobel (1982) tests, comparing the

direct effects of the service ratio on firm value between the models with and without the three

mediators are significant (p < .05 for all three mediators), confirming the role that each

mechanism has in mediating the relationship between service ratio and firm value. Taken

together, our findings suggest that these three mechanisms fully mediate the effect of the service

ratio on firm value.

To depict our interaction effects, we plot the curvilinear relationships between service ratio

and financial-based mediators at high (one standard deviation above the mean) versus low (one


standard deviation below the mean) levels of the significant moderators. As Figure 2, Panel A,

shows, the positive effect of the service ratio on sales growth is more pronounced in mature

industries. This moderating role of industry maturity is particularly strong: In mature industries,

a 1% increase in the service ratio, on average, boosts sales growth by an additional 3% compared

with the effect in growth markets. In Figure 2, Panel B, compared with firms that diversify their

service businesses, the profitability of manufacturers with narrower scopes drops by an average

of 1% less when they increase their service ratio by 1% in the early stages. Moreover, this same

increase in the service ratio during later stages enhances the profitability of these firms, on

average, by an additional 15% over those with more diversified service businesses.

Robustness and Sensitivity

We conducted several sensitivity analyses to ensure that our results were robust to

alternative measures and model specifications. First, we used alternative operationalizations of

profitability, as return on assets (Joh 2003), and of cash flow volatility, measured as the standard

deviation of quarterly cash flows per share over two years (Allayannis and Weston 2006). The

results, as we detail in Appendix A, are similar to those for the main estimation, enhancing

confidence in the robustness of these findings. Second, Roodman (2006) notes that choosing a

different set of panel-internal instruments may change the results. We therefore applied a

reduced set of instruments limited to more recent lags. The results in Appendix B show that our

findings are robust to this selection of alternative panel-internal instruments.

Decomposing the Indirect Effect of Service Ratio on Firm Value Across Transition Stages

The complex mediating effects of sales growth, profitability, and cash flow volatility in the

relationship between service ratio and firm value led us to conduct supplementary analyses to

derive actionable recommendations for managers. Therefore, we calculated the indirect effect of

each mechanism at each stage of the service transition, to understand their relative roles in

determining the net effect of the service ratio on firm value as a firm progresses through these

different stages (Hayes and Preacher 2010). Figure 3 reveals the change in firm value associated

with each mechanism due to a 1% change in the service ratio in each stage. We identify three


service transition stages, according to the trade-offs of sales growth, profitability, and cash flow

volatility, along with their relative roles in driving the impact of the service ratio on firm value.

In the exploration stage (service ratio < 20%), firms struggle to acquire service-related

resources and capabilities and must resolve organizational conflicts arising from disagreements

over organizational changes. These investments and organizational transformation processes

impose substantial costs on firms. The loss of profitability is thus the primary determinant that

links the service ratio to firm value in this stage (i.e., larger negative effect); it overwhelms the

other mechanisms. A one percentage point increase in the service ratio, on average, decreases

Tobin’s q through the profitability mechanism by 4.5%. At this time, firms have not yet

established the required competencies, so they cannot exploit the advantages of adding services

to their offerings. Moreover, the benefits of moving into services have the least effect in this

stage, such that a 1% increase in the service ratio, on average, enhances the Tobin’s q through

increased sales growth and reduced cash flow volatility by just .5% and 1.4%, respectively.

Delivering 70% of the effect of the service ratio on firm value, the loss in profitability thus is the

dominant mediating mechanism in the exploration stage.

In the learning stage (20% < service ratio < 45%), firms gradually acquire capabilities,

stock up on know-how, learn how to enhance the operational efficiency of their service

businesses, and realize economies of scale on initial service-related investments. On the one

hand, leveraging these competencies enables the firms to mitigate the negative indirect effect

through firm profitability; the share of the net effect of the service ratio on firm value, driven by

the profitability mechanism, thus drops to 41% on average. On the other hand, firms start

expanding their service sales and encourage customers to cross-buy and repurchase. Therefore,

sales growth and cash flow volatility drive about 33% and 26%, respectively, of the net effect of

the service ratio on firm value. Firms can offset the negative effect of shifting to services.

Specifically, in the learning stage, the indirect effects of a one percentage-point increase in the

service ratio transmitted through sales growth, profitability, and cash flow volatility result in

2.5%, 3.1%, and 2% changes, respectively, in Tobin’s q.

Finally, in the payoff stage (service ratio > 45%), firms rely on services to create a

sustainable competitive advantage and differentiate their offerings, and services also account for

a large portion of their overall sales. The decreased substitutability of their offerings means firms

can compete better, obtain and retain more sales, and enhance their profitability. Sales growth


accounts for 48% of the overall effect of the service ratio on firm value in this stage; increasing

the service ratio by one percentage point enhances firm value through this mechanism by 2%.

Profitability instead accounts for 36% of the overall effect, and a 1% increase in the service ratio

enhances firm value by 1.5% through this mechanism. Finally, cash flow volatility delivers, on

average, 16% of the net effect of the service ratio on firm value, and a one percentage-point

increase in the service ratio increases firm value by .7% by reducing this volatility.

Discussion In the face of increased product commoditization and growing global competition, many

B2B firms transition to services to obtain competitive advantages and combat margin pressures.

A survey of more than 300 manufacturing executives (Oxford Economics 2013) revealed that

70% of manufacturing firms use services to differentiate their offerings, and more than half

(56%) intend to establish services as a profit center. Yet many companies still fail to understand

the performance ramifications of adding more service offerings to their portfolios. To make more

informed decisions, managers need a better understanding of the links across B2B services and

financial outcomes (Anderson 2006; Suarez, Cusumano, and Kahl 2013), but prior research into

service–performance relations suffers two significant limitations. First, little existing research

examines the simultaneous financial performance outcomes in a single framework, even though

the transition into services affects multiple, financial-based mediating mechanisms in diverging

ways, such that the net effect on firm value reflects the sum of the effects across these

mechanisms. Second, few studies account for the stage of service transition. Adding services has

a dynamic effect on performance, reflecting the stage of the service transition, such that it

unfolds as the firm progresses to a service-based business. Ignoring the simultaneous effects of

service transition strategies on different financial mechanisms and the dynamic nature of

transitioning toward services likely led to the mixed findings in past research (Eggert,

Thiesbrummel, and Deutscher 2015; Homburg, Fassnacht, and Guenther 2003).

Theoretical and Managerial Implications

By proposing and empirically testing a comprehensive, integrated framework of the effects

of B2B services on firm performance, we explore simultaneous effects across different

mechanisms and the dynamic nature of service transition strategies for firms’ overall


performance. In this pursuit, we identify and disaggregate the roles of sales growth, profitability,

and cash flow volatility as mediating mechanisms. In Figure 4, we provide a visual, theoretical

overview of the different functional forms of these mechanisms when service ratios increases

from 5% to 70% for a hypothetical firm that represents an average in our B2B sample.

First, the relationship of service ratio and sales growth is convex and monotonously

increasing. A growing emphasis on services enhances sales growth, because these tailored

offerings meet customers’ individual needs and facilitate novel customer insights. Providing

tailored offerings, which reflect close collaborations with customers during service delivery,

enhances customer satisfaction, which in turn creates new potential sources of revenue by

facilitating cross-selling and repeat purchase. Thus, firms can offer services “as a distinct value

proposition and revenue generator in itself” (Oxford Economics 2013, p. 9). For example, for

one percentage point increase in its service ratio at its early stages of transition, Lockheed

Martin, on average, experienced 7% increase in its sales growth.

Second, the growing service ratio has a U-shaped, curvilinear effect on profitability. The

substantial costs associated with acquiring service-related competencies and implementing the

necessary organizational changes result in reduced profitability in early stages of the service

transition. Manufacturers consider this profit loss a “necessary evil” (Suarez, Cusumano, and

Kahl 2013, p. 427); as Scott McNealy, the former CEO of Sun Microsystems, argues, “services

will be the graveyard for old tech companies that can’t compete” (Morgenson 2004, p. C1). Yet

after a critical point, firms learn how to manage their service operations efficiently, and they

leverage their newly acquired capabilities to create a competitive advantage and mitigate the

negative effect of rivalry on profit margins. Thus, providing services in later stages of the

transition enables firms to differentiate their offerings and boost their profitability. For instance,

for each percentage point increase in service ratio in the early stages, profitability of MRV

Commutations Inc., a global supplier of packet and optical solutions, on average, dropped by

20%. Yet in later stages, one percentage point increase in its service ratio, on average, led to 25%

increase in its profitability

Third, adding services reduces cash flow volatility, according to a linear relationship. In

this sense, “By focusing on the outcomes of their products and services, manufacturers can

servitize their business, and thereby create whole new systems of value for customers that help

lock in long-term relationships and lock out the competition” (Forbes 2014). Although services


enhance customers’ perceptions of value, their intangibility and simultaneity also make them

relatively difficult and costly to evaluate. Staying in a relationship with their current service

providers lets customers reduce these evaluation costs. A more stable customer base also is less

vulnerable to competitive erosion, resulting in more predictable financial performance. Previous

research predicts that B2B services lock customers in and ensure smoother revenue streams, but

to the best of our knowledge, this article is the first empirical test of the link between services

and firms’ cash flow volatility. For instance, one percentage point increase in service ratio, on

average, reduced cash flow volatility of Aavid Thermal Technologies, a manufacturer of thermal

management devices, by 5%.

Our moderation analyses also indicate that the positive effect of adding services on sales

growth gets magnified in mature industries, which are characterized by product commoditization

and slow market growth. Slowed growth in established markets means that firms “are

desperately trying to differentiate through … their technical field service organization and

capabilities” (Roland Berger 2010, p. 2). Increasing the scope of the service business (i.e.,

number of service markets in which a firm is active) unfavorably moderates the impact of the

service transition strategies on profitability though, because it magnifies the costs associated with

developing service-related resources and capabilities in early stages. Later, it also impedes firms’

ability to reap economies of scale by leveraging the skills or deep customer relationships they

have acquired. Managers should consider these contingencies when moving into services.

Our empirical study also suggests that sales growth, profitability, and cash flow volatility

fully mediate the effect of the service ratio on firm value. By decomposing the effect of the

service ratio on firm value through these three mechanisms across the three transition stages, we

provide managers with novel and clear guidance about what to expect of their financial

performance as they undertake this shift to services. In the exploration stage, profitability is a

dominant mediating mechanism that drives an average of 70% of the effect of the service ratio

on firm value. With the significant profit losses in this stage, managers need to expect a decrease

in firm value. In the learning stage, the mediating roles of sales growth and cash flow volatility

gain strength, delivering 33% and 26% of the overall effect of the service ratio on firm value.

Thus, firms can offset the negative effect through profitability and mitigate the change in firm

value. If they can make it to the payoff stage, managers can expect all three mechanisms to

contribute positively to firm value. Specifically, sales growth, profitability, and cash flow drive


48%, 36%, and 16% of net effect of the service ratio on firm value. Therefore, managers can

anticipate a boost in firm value when they emphasize more services.

By clarifying the underlying financial drivers of service transition strategies, our findings

also provide important implications for the investment community. Analysts and investors assign

premiums to firms that achieve greater sales growth (Davis 2002), superior profitability (Cho and

Pucik 2005; Varaiya, Kerin, and Weeks 1987), or lower cash flow volatility (Huang 2009). We

find empirical evidence that supports the link between the service ratio and these financial-based

mediators. Therefore, the service ratio is a valuable metric that financial analysts can use to

assess a firm’s potential sales growth, profitability, and cash flow volatility, as well as the overall

effects on firm valuations, contingent on the transition stage and environmental factors.

Limitations and Research Directions

Some limitations of this study provide opportunities for research. First, we used two years as

a time unit, to avoid overlap in the data used to reflect consecutive time periods. However, this

method reduces the number of observations for the estimation. Still, by using independent

sample periods, we confirm that our measures of cash flow volatility and industry turbulence do

not suffer from serial correlation. In addition, our estimation approach relies on lags of

endogenous variables to address endogeneity, which limits our sample to observations for which

we have adequate (i.e., at least two) lags. Then again, it also enables us to estimate our

parameters efficiently by employing the information contained in the moment conditions.

Second, data constraints prevented us from examining some theoretical mechanisms (e.g.,

customer satisfaction) that might link service transition strategies with financial outcomes.

Although our findings are consistent with the predictions of these theoretical arguments, further

research might also collect data through self-reported, perceptual measures, for example.

Obtaining such data for a large sample of B2B firms covering multiple industries and multiple

years would be extremely challenging though.

Third, we focused on the financial outcomes of service transition strategies; the tactics that

firms should use to address the challenges of implementing these strategies remain largely

unexplored. For example, managers need a better understanding of what organizational structure

is most suitable for supporting their service transitions strategies and facilitating collaboration.


Similarly, services are relationship intensive, so research should identify ways to mitigate the

potentially negative effects of cultural differences in service expansions to international markets.

Research that sheds light on these topics would be valuable.


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Dynamic Effects of Service Transition Strategies on B2B