Successful selling strategies rely on both salesperson individual and team drivers to deliver customer value (Arli et al., 2018). An individual salesperson’s unique skills, aptitudes, and motivation, as imagined in the notion of a super salesperson, famously idealized in Arthur Miller’s (Miller, 1980) classic play Death of a Salesman, represent salesperson individual drivers of performance (Verbeke et al., 2011). But when salespeople work together in a sales team, their intrafirm networks also exert positive performance effects (e.g., Bolander et al., 2015; Claro et al., 2020), such that relevant salesperson team drivers of performance include intrafirm knowledge brokerage efforts, improved selling processes, and knowledge sharing at the firm level (Hartmann et al., 2018). Both classes of drivers can have positive performance impacts, but some research raises questions about the potential negative performance effects of selling skills (Blessing & Natter, 2019; Singh et al., 2018), aptitude (Korschun et al., 2014), and intrafirm relationships (Guidice & Mero, 2012). Such conflicting findings suggest that the overall effect of salesperson drivers (individual and team) on performance outcomes might vary over time and be contingent on country development or culture, which in turn would require adaptive selling strategies (Hughes et al., 2013). In particular, we posit that two notable changes to sales environments in the past decade have had direct impacts on sales performance: growing complexity in marketplaces and global selling efforts.

The marketplace has become increasingly complex for both salespeople and firms for three main reasons. First, consumers have access to more and higher quality information at low search costs (Labrecque et al., 2013; Li et al., 2014), so salespeople may lose their usefulness (Hochstein et al., 2019). Second, the emergence of new technologies and proliferation of digital channels create redundancy for the salesperson’s role (Zoltners et al., 2022). Third, as competition increases, there is intense pressure on salespeople to increase their performance, but at a lower cost (Paesbrugghe et al., 2017, 2018). Despite these challenges, salespeople continue to have important value-adding roles, especially in purchases that involve high customer involvement (Hochstein et al., 2019), highly complex buying process (Zoltners et al., 2022), and consultative or solution-selling approaches (Salonen et al., 2021). Still, the value they add depends on the extent to which salespeople can adapt their selling strategies to meet these demands (Hoar, 2017).

The global selling environment also has notable influences on salespeople, in two main ways. First, sales in international markets have increased dramatically, and many firms maintain substantial workforces outside their home country or earn most of their sales revenues in foreign countries (Marshall et al., 2020). Second, rapid development by various countries alters their existing selling environments in dynamic ways, creating even more complexity for already challenging tasks linked to sales management and strategic selling choices (Dugan et al., 2020). In combination, these trends require managers to anticipate and account for the influence of country-level contingencies on performance outcomes, as well as help salespeople adapt their selling strategies accordingly. Prior research predominantly focused on individual countries without addressing country-level differences with few exceptions (Baldauf & Lee, 2011). Moreover, a predominant focus on developed regions, such as the United States and Western Europe (Hohenberg & Homburg, 2019), produces frameworks that cannot depict marketing phenomena in other real-life settings, which involve multiple countries and development levels.

To address the complex questions involving adaptive selling strategies as a result of changing selling environments and growing international markets, we conduct two meta-analyses, with the aim of establishing the extent to which salesperson individual or team drivers should be adapted for better effectiveness (Study 1) and the specific ways such drivers are correlated with performance (Study 2). In Study 1, we assess selling strategies’ effectiveness by gathering 307 salesperson driver elasticity measures in 48 eligible studies published between 2009 and 2021. The studies included in this elasticity-based meta-analysis span seven countries and one region, with a combined N of 24,242 sampled salespeople. In Study 2, we adopt a correlation-based meta-analysis to gain specific insights on salesperson drivers by evaluating the correlation between selling strategies and performance and how the strength of such correlation is contingent upon country development and cultural characteristics. This correlation-based meta-analysis integrates 2,532 salesperson driver effects documented in 328 independent studies published between 2009 and 2021, mostly in single-country settings, and conducted in 32 countries on six continents. The countries represent 83% of the world’s gross domestic product (GDP) (World Bank, 2022), and the combined N is 126,766 sampled salespeople.

The contributions we derive from these expansive studies can inform both marketing and sales literature. First, compared with previous decades (Albers et al., 2010’s elasticity = .340), and due to changes in the marketplace and selling environment, Study 1 findings show that the effectiveness of personal selling has decreased in the past decade (this study = .152) in comparison to previous decades (1971–2009) by 56%; moreover, the predicted elasticities dropped by 57% from .255 in 2007 to .120 in 2018. Recent research (Hochstein et al., 2019; Zoltners et al., 2022) and market reports (Bages-Amat et al., 2020) have suggested this trend; we confirm it and also argue that as customers’ sense of being informed has increased, they have become more autonomous (Skrovan, 2017), relying less on sales support (Hochstein et al., 2019). The proliferation of digital channels diminishes the need for face-to-face interactions (Mantrala & Albers, 2012), and increased competition leads firms to push their salespeople harder. But we also unveil a lasting positive performance effect of salesperson drivers, which continue to add value (Viio & Grönroos, 2014). Beyond making an important contribution to marketing theory, this finding offers managers empirical insights on effective sales management.

Second, we propose and empirically validate a comprehensive salesperson performance framework that comprises both individual and team drivers. Previous sales meta-analyses exclude team drivers (e.g., Albers et al., 2010; Verbeke et al., 2011). As our meta-analytic evidence from Study 1 shows though, individual characteristics and team efforts both can have positive effects on performance outcomes. Team strategies introduced relatively recently in sales literature are used widely in managerial practice. At the same time, we acknowledge that the positive elasticity of individual drivers (predicted elasticity = .189) is 86% greater than that of team drivers (predicted elasticity = .101), drawing on marginally significant results (p = .052). The salesperson individual drivers remain the most critical factors for success (Verbeke et al., 2011), because they allow the salesperson to acquire specific customer knowledge (Slater & Narver, 2000) and effectively use that knowledge (Sujan et al., 1994). Customer relationships established by individual salespeople thus cannot be replaced easily (Mayer & Greenberg, 2006). However, the internal resource mobilization and knowledge access that result from teams and the influence of social capital achieved through intrafirm relational structures still enable salespeople to benefit from team drivers; our study identifies lower, yet still positive, effects of such drivers on performance (Mayer & Greenberg, 2006). Team drivers create challenges for managing internal networks, due to the dark side of intrafirm relationships (opportunistic, short-term, non-reciprocated behaviors; Dugan et al., 2019) and risk of deleterious team conflict (Auh et al., 2014). These are rich insights for sales managers and salespeople to allocate their resources more effectively. Study 2 findings also show greater correlation effects between performance and the individual drivers (i.e., selling skill and aptitude), than between performance and the specific team drivers (i.e., intrafirm relationship and coordination activity). Overall, our findings from both studies contribute to marketing and sales literature.

Third, we contribute to marketing and international sales literature by showing how specific countries condition the effectiveness of salespeople’s efforts (Study 1) and how the correlation between salesperson drivers and performance varies across specific country characteristics (Study 2). Study 1 reveals that such efforts are less effective in the United States than in other countries, probably due to the countries’ varying levels of development (Sheth, 2011) and short-term–oriented cultures (Hohenberg & Homburg, 2016). This elasticity analysis helps advance previous sales research by shedding light on conflicting previous findings (Guidice & Mero, 2012). In Study 2, with more countries in the sample, we take a finer-grained perspective on both country-market contingencies (market heterogeneity, unbranded competition, resource availability, infrastructure, sociopolitical governance; Sheth, 2011) and cultural values (power distance, masculinity–femininity, uncertainty avoidance, long-term orientation; Hofstede et al., 2010) to investigate how the direction and strength of the correlation between selling strategies and performance varies across countries. Thus, we can establish country-level factors’ specific influences on the strength of the correlations between salesperson individual or team drivers and performance outcomes.

Fourth, we offer a methodological contribution, by empirically showing that, despite their different aims, procedures, and potential trade-offs, elasticity and correlation-based meta-analyses actually can both provide meaningful insights on salesperson drivers. Elasticity-based meta-analysis is the proper way to test the effect of salesperson-specific selling strategies on performance (Albers et al., 2010), but elasticity data suffer limitations in terms of country and country-year sample sizes. Moreover, we could not find elasticities for all the individual performance drivers identified in the conceptual framework either (i.e., aptitude). Correlation meta-analyses benefit from a much larger sample because correlations are the most common metric reported in prior research and are less restrictive than elasticity data with regard to scale measures. The inclusion of correlation-based effect sizes thus broadens the scope of the meta-analysis and decreases sampling and non-sampling errors (Peterson & Brown, 2005). Furthermore, correlation measures allow comparisons between metrics that use different scale measures (Eisend, 2006), such as those of selling strategies and performance outcomes. Previous studies in the same domain (e.g., electronic word of mouth) have used both effect sizes (e.g., Babić Rosario et al., 2016: correlation; You et al., 2015: elasticity), however, the two effect sizes have never been used in the same research article (Grewal et al., 2018).

Change in the selling environment

Evolution of the sales context and salesperson performance drivers

Extant sales research into selling efforts denotes two performance drivers: salesperson individual drivers (Verbeke et al., 2011) and team drivers (Hartmann et al., 2018), as indicated in Table 1. Individual drivers involve enduring or learned personal characteristics that salespeople leverage to manage their external relationships with customers (Mullins et al., 2014); they should improve sales performance outcomes. They include the salesperson’s skill (learned proficiency; Hughes et al., 2013), motivation (amount of effort expended on job-related activity; Lam et al., 2019), and aptitude (native ability and enduring personal traits; Van der Borgh & Schepers, 2018), which also determine whether salespeople can satisfy their own psychological needs, as proposed by self-determination theory (Deci & Ryan, 2004), in ways that inform their attitudes, behaviors, and performance (Hohenberg & Homburg, 2016). Therefore, individual drivers exert positive performance effects because salespeople gain customer knowledge (Menguc et al., 2013), cocreate solutions with customers (Salonen et al., 2021), address customers’ problems creatively (Agnihotri et al., 2014), and deal well with customers’ objections (Blessing & Natter, 2019).

Table 1 Representative empirical sales research
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Yet even a super-salesperson may not be able to deal with complex selling environments (Hartmann et al., 2018; Plouffe & Barclay, 2007). The success of selling efforts depends on the extent to which salespeople are able to access firm resources and gain internal support to develop customer solutions (Hochstein et al., 2019). Reflecting social exchange and network theory perspective (Blau, 1964), team drivers encompassing intrafirm relationships and coordinated activities in intrafirm social networks, also drive sales performance. For example, salespeople’s internal coordination efforts promote teamwork with peer salespeople or peers in other functions (Claro & Ramos, 2018; Gonzalez & Claro, 2019). They can leverage resourceful internal relationships (Ahearne, Lam, et al., 2013; Auh et al., 2014) and share learned proficiencies, such as for gathering information or influencing others (Gonzalez et al., 2014; Steward et al., 2010). As previous research shows, effective selling strategies often require intrafirm coordination (Steward et al., 2010), resource mobilization (Li et al., 2017), and access to varied knowledge (Sleep et al., 2015) to deliver superior value to customers.

Although most practitioners and researchers acknowledge the importance of both salesperson individual and team drivers (e.g., Fuller, 2015), for many years, the focus was on individual drivers, and only in the past decade have salespeople team drivers and the relevance of intrafirm coordination across relationships and networks received more attention (Bolander et al., 2015; Plouffe et al., 2016). This is reflected in past meta-analyses of the determinants of sales performance published more than ten years ago, which only considered individual drivers (Albers et al., 2010; Verbeke et al., 2011). Yet despite growing knowledge of team drivers, even recent meta-analyses tend to ignore their impacts on salesperson effectiveness (Ohiomah et al., 2020). Moreover, extant research tends to focus on either individual or team performance drivers, rarely considering both in the same analysis.

Finally, even if salespeople recognize and have access to both types of performance drivers, it is increasingly challenging for them to be effective (Hochstein et al., 2019). They face more complex selling environments, characterized by ruthless competition and demanding customers (Arli et al., 2018; Paesbrugghe et al., 2017). Previous research identifies diminishing performance elasticity trend in the decades before 2009 (Albers et al., 2010), sparking calls for adaptive selling (Hughes et al., 2013). Firms and salespeople thus have to revisit their selling strategies to manage the increasing challenges of the complex selling environment (Ryan, 2019).

Internationalization of the selling environment

The complexity of the selling environment is enhanced by two notable trends in international sales contexts. First, firms send products and salespeople to different countries, in search of profitability; world exports increased by 46% in the 2010s (World Trade Organization, 2019). Even Chinese firms, with their large and historically protectionist home market, have been encouraged by the central government to “go global” (The Diplomat, 2014). In an increasingly globalized world (DHL Global Connectedness Index, 2020), sales territories are no longer defined by national borders, so different, varied, and complex selling environments are the norm (Sales Management Association, 2017). Although some firms still embrace a single, global selling plan, which offers the benefits of uniformity, simplicity, and control (Zoltners et al., 2015), certain countries demand unique adapted selling strategies. For example, for labor productivity, market regulation, and international trade, Australia and Japan appear homogeneous (World Economic Forum, 2019), yet their dissimilarities (e.g., sociopolitical governance levels) require adapted selling strategies (Baalbaki & Malhotra, 1995; Mandler et al., 2021). A global standardized selling plan often is insufficient, because “each country has its own market dynamics, business culture, laws, and availability of data for measuring performance” (Zoltners et al., 2015: 1).

Second, increasing world trade (e.g., by 26% in the 2010s; World Trade Organization, 2019) and national GDP levels are producing profound shifts in the economic, social, competitive, resource availability, infrastructure, regulatory, and political development of countries around the world, with concomitant impacts on customers and business life (World Bank, 2022). For example, Singapore once was categorized as underdeveloped, but it has become the world’s most competitive (as of 2019) and one of the fastest growing economies, through its embrace of free-market capitalism, education, and health care policies (World Economic Forum, 2019). Thriving, emerging economies have become the growth engines of the world (Sinha & Sheth, 2018), offering appealing potential sources of profit and revenue growth for international firms (Kumar et al., 2021). Such country development also promotes the internationalization of firms’ sales organizations. Since its economic opening in 1978, China has grown into the world’s second-largest economy and reduced its poverty levels, such that it is currently an upper middle-income country with average annual GDP growth of 10% (World Bank, 2022). Chinese firms in turn are shifting from resource-intensive, low-end manufacturing to higher-end product and service provision, and China continues to invest heavily in science and technology in its effort to become a high-tech international superpower and develop its own markets abroad (Forbes, 2019). Such an international, technology-oriented strategy, including direct investments in developing countries, illustrates how country development can drive sales internationalization.

Yet in contrast with Levitt’s (1993) influential view on the globalization of markets, global customers have not produced homogeneous markets; instead, cross-national differences still require firms to adapt their strategies to new markets (Mandler et al., 2021). Furthermore, changes to the international selling environment mean that firms must continue adapting their selling strategy to reflect ongoing shifts in their home countries and abroad. International marketing research offers contradictory findings regarding whether firms ultimately benefit from adapting their international strategy though. Lages et al. (2008) find a negative effect of product adaptation on international expansion, whereas Dow (2006) proposes that some optimum level of adaptation exists, at which a firm can achieve the greatest sales performance. As we noted in Table 1, cross-country sales research addressing standardization versus adaptation is limited; most studies focus solely on cross-cultural static differences (e.g., Piercy et al., 2004) rather than dynamic country-level development characteristics (Sheth, 2011).

Study 1: Salesperson individual and team drivers of performance

Drawing on extant sales research, we propose a conceptual framework and specific hypotheses to predict the extent to which salesperson individual and team drivers lead to performance, as well as to understand how the effectiveness of such salesperson drivers has evolved over time and how country-market characteristics can condition such effectiveness. We present this parsimonious framework in Fig. 1.

Fig. 1
figure 1

Salesperson dynamic and global performance drivers framework

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Although we rely on existing sales research that shows that salesperson individual and team drivers have positive performance impacts (Table 1), we propose that growing complexity and competition makes it more challenging for salespeople to add value, because these trends imply that customers are more informed, more digital, and more demanding. First, customers have more access to expansive, high quality, inexpensive information (Labrecque et al., 2013; Li et al., 2014), which makes them more autonomous and well-informed and less reliant on brokerage (Verbeke et al., 2011) or overall support (Hoar, 2017; Skrovan, 2017) from salespeople. In some cases, salespeople even appear redundant, adding costs and needless complexity to the customer decision-making process (Hochstein et al., 2019). In other settings though, customers still need sales support (Hochstein et al., 2019), such as for high involvement purchase decisions, in which salespeople can help them overcome information or choice overload and guide them through the decision process (Ryan, 2019). In other cases, a customer may want expert advice to ensure the accuracy of the information gathered and reinforce the choice they made (Leach et al., 2020). Customers thus continue to perceive some value in the salespeople, despite the announced “death of the salesperson” (Hoar, 2017).

Second, the proliferation of digital marketing channels supports more transactions taking place on digital platforms (Arli et al., 2018; Hoar, 2015; Hochstein et al., 2019), trends that were further intensified by the COVID-19 pandemic (Goonan & Hergesell, 2021). Because they can benefit from digitalized marketing and sales systems, customers may find salespeople less helpful (Sharma & Syam, 2018) and avoid face-to-face interactions (Mantrala & Albers, 2012). Here again though, salespeople might add value by learning about customers’ explicit and latent needs through digital channels, adapting the firm’s offerings to meet those needs, and clarifying the value added by an offered solution (Hoar, 2015). A common view suggests that digital connections are not sufficient to surpass salespeople’s ability to leverage customer knowledge and build customer relationships (Zoltners et al., 2022). Instead, salespeople can still use their domain expertise to educate customers with customized and detailed information, find the right solution for their problems, help them avoid mistakes, and establish long-lasting loyalty bonds (Ryan, 2019). Furthermore, a salesperson adds a human touch to impersonal digital interactions, which may be especially valued by customers buying complex, expensive products (Ryan, 2019).

Third, growing competition (Paesbrugghe et al., 2017) makes customers more demanding. In hyper-competitive selling contexts (Chawla et al., 2020), customers encounter better offers and then demand even more (Hoar, 2017), such as complex, customized products (Marcos-Cuevas, 2018) that require more effort from salespeople (Paesbrugghe et al., 2017). But salespeople’s productivity and effectiveness decline as their firms demand that they perform better and faster, put in more effort to cocreate novel solutions (Peesker et al., 2022), and communicate and deliver differentiated solutions for specific customers (Salonen et al., 2021). At the same time, salespeople face increasing operation costs, lengthier sales cycles (Kerr & Marcos-Cuevas, 2022), and fierce competition (Paesbrugghe et al., 2017). In response, salespeople have found ways to become more strategic (Paesbrugghe et al., 2017) and offer complex, service-based solutions to increasingly demanding customers (Paesbrugghe et al., 2018). In this value-adding role, throughout the customer journey, salespeople deliver consultative solution selling (Salonen et al., 2021) and customized offers to customers (Viio & Grönroos, 2014). We thus hypothesize:

H1

Salesperson performance positive elasticity is diminishing in magnitude over time.

Even if performance depends on salesperson individual and team drivers, and the team drivers have been gaining importance (according to publication trends, such that “salesperson teams” references in Google Scholar increased by 134% in the 2010s), individual drivers still may be more effective than team drivers for two main reasons. First, the individual drivers increase the likelihood that salespeople have the capacities to acquire specific customer knowledge (Slater & Narver, 2000), share that knowledge back to the firm (Kuester & Rauch, 2016), and implement efforts to use that knowledge effectively (Sujan et al., 1994), such as by developing high quality relationships with customers (Mullins et al., 2014), cocreating solutions with them (Payne et al., 2017), addressing customers’ problems creatively (Coelho & Augusto, 2010), and dealing properly with their objections (Alavi et al., 2018). Such customer relationships, achieved due to the existence of salesperson individual drivers, cannot be replaced easily and are starting points to improve performance. Thus, stronger performance effects result from customer loyalty to the individual salesperson than loyalty toward the firm (Palmatier et al., 2007). In their quest to address customers’ demands, salespeople might identify and contact key internal partners, through relationships and network management (Dugan et al., 2019). But even these internal collaborative teams and network ties have less power to create and deliver customer value compared with individual performance drivers (Mayer & Greenberg, 2006).

Second, managing internal relationships with other firm members is difficult (Bolander et al., 2015; Claro et al., 2020), because they may be subject to opportunistic, non-reciprocal, or short-term behaviors, reflecting the dark side of networks (Dugan et al., 2019). Networking becomes counterproductive for both the salesperson who seeks to “get ahead” and other salespeople who may see their access to internal resources denied by others’ opportunistic behavior (O'Boyle Jr. et al., 2012). Such challenges imply that salespeople must learn how to build and maintain productive intrafirm relationships and coordinate activities to leverage their network structure along their socialization process (Claro et al., 2020) and their relationship with their sales manager (Ahearne, Lam, et al., 2013). Salesperson team efforts may also face negative headquarter stereotyping (Wieseke et al., 2012) or insufficient team member identification (Ahearne, Haumann, et al., 2013). Thus, we predict:

H2

Salesperson performance elasticity is greater for salesperson individual drivers than for salesperson team drivers.

Specific country-market characteristics can condition the effectiveness of selling strategies, in the form of country development levels (Sheth, 2011) and country cultural values (Hofstede et al., 2010). For this study, we use the United States as a reference, because it is the world’s largest economy (World Bank, 2022) and the site for most sales research. Country development factors can represent opportunities or threats for specific marketing efforts and marketing mix effectiveness (Bahadir et al., 2015). In line with prior international sales literature, we predict that salesperson performance is weaker in developed countries such as the United States (Sheth, 2011), because country development factors determine opportunities to develop and launch innovative solutions, products, and services or sell adapted branded goods targeted to different customer segments whose needs are not fulfilled by unbranded goods (e.g., low-income segments; Arunachalam et al., 2019; Sinha & Sheth, 2018). In more developed countries, firms have fewer of such opportunities, because consumers are more homogeneous (Bahadir et al., 2015) and have ready access to affordable, branded offerings (Sheth, 2011). Country development factors also determine the ease of access to knowledge and other resources, the quality of the infrastructure (Sheth, 2011), the extent of confidence in business growth and institutions, and thus the level of customer demand (Arunachalam et al., 2019). In developed countries, one may expect and demand abundant resources, good quality infrastructure, and strong sociopolitical governance, resulting in better offerings and more demanding customers (Bahadir et al., 2015). Salespeople need to exert more efforts to achieve strong performance.

In terms of cultural factors, short-term–oriented cultures such as the United States focus on the short-term effects of their actions and the present accomplishments they produce (Hofstede et al., 2010). A sense of being connected with others, favorable network positioning, and basic needs of relatedness are less prioritized as sources of success (Deci & Ryan, 2004); instead, autonomy and the capacity to act independently in the present appear key (Hohenberg & Homburg, 2016). Thus, salespeople and customers are less willing to develop personal, face-to-face relationships, the beneficial effects of which are expected to be weaker (Samaha et al., 2014), because they also are less responsive to relational and social norms such as reciprocity and mutual interdependence (Hofstede et al., 2010). Furthermore, both parties are less receptive to information about ongoing relationships (Samaha et al., 2014). Thus in the United States, it can be harder to close a deal (i.e., takes longer, requires more interactions, and is more costly) than in Brazil or European countries that are more long-term oriented (InsideSales.com, 2017; Pipedrive, 2017). Not only does a short-term orientation make it more difficult for salespeople to get to know customers’ needs or manage their internal knowledge to address those needs, but it also diminishes their focus on expanding personal abilities, because individual competences are not considered antecedents of future success (Deci & Ryan, 2004; Hohenberg & Homburg, 2016). Salespeople look for short-term, material rewards and might invest more effort in response to pay-for-performance plans (Rouziès et al., 2017), rather than in response to existing norms (Hofstede et al., 2010). Because salespeople in these cultures do not prioritize developing their individual drivers, it may result in less effective selling strategies.

H3

Salesperson performance elasticity is weaker in the United States than in other countries.

Method

Data collection and coding

To test the conceptual framework in Fig. 1, we adopt a meta-analytic approach using elasticity measures to properly investigate effectiveness (Albers et al., 2010). We searched for published and unpublished empirical research on salesperson performance during 2009–2021. This meta-analysis adds to previous research because it includes team drivers and research published in recent years (Albers et al., 2010). To identify relevant studies, we searched various scientific databases, including ABI/INFORM, Business Source Complete, Elsevier Science Direct, Google Scholar, PsychlNFO, and ProQuest. We also searched the Social Sciences Citation Index, using articles that included key constructs, and conducted a manual shelf search of journals (see Web Appendix A for the full list of journals included in our sample). We sent e-mails to prominent researchers in this domain, asking for their published and unpublished works. Through this process, we generated an initial list of published and unpublished empirical studies, each of which we evaluated according to whether it offered quantitative empirical (non-experimental) evidence pertaining to salesperson drivers and performance outcomes. We then selected studies that met four criteria. First, we only included studies that reported elasticities based on objective, ratio-scaled measures of performance outcomes (e.g., sales growth, sales profit) and objective, ratio-scaled measures of individual (e.g., number of customer calls, training hours, number of managed accounts) or team (e.g., sales manager’s weekly interaction, networking intensity, network density) drivers (coding examples in Web Appendix B). In line with Albers et al. (2010), we assume that authors of the studies checked for reliability because their objective data may suffer from unreliability arising from potentially faulty or bias-prone data collection procedures. Second, we considered only elasticities obtained through statistical and econometric analyses of the drivers and performance outcomes, thereby excluding studies that used experimental or judgmental data, such as purchase intentions or preferences. Third, only studies that report estimates of current-period elasticity, either directly or derivable from author-reported lagged effects, entered the analysis. Fourth, the elasticities had to be unambiguously reported in main effect regression models, and allowed us to transform them (log or linear regression specification; Web Appendix C) from the estimated coefficients or other reported descriptive statistics. We gathered 307 salesperson driver elasticity measures in 48 eligible studies conducted in 7 countries and 1 regionFootnote 1 between 2009 and 2021 (sample details in Web Appendix D and E). The combined N is 24,242 sampled salespeople.

Model estimation and analysis

We evaluated how the elasticity of each driver on performance varies with time, driver importance, and country contingency moderator. The meta-analysis data have a nested or hierarchical structure, with effects nested within studies. Following the procedure proposed by Bijmolt and Pieters (2001), we perform hierarchical linear modeling (HLM) to account for within-study correlations of the effect sizes on study-level moderators; we can determine if between-study heterogeneity can be explained by each moderator. The estimated model is:

  1. (1).

    (Level 1) Yij = β0j + βj × Xij + εij, and

  2. (2).

    (Level 2) βj = γ0 + uJ,

where Yij is the ith salesperson performance driver elasticity from study j, β0j is the intercept for the jth study, βj is the parameter estimate of each moderator Xij and controls for the jth study, εij is the random error associated with the effect measured in study j, γ0 is the overall intercept, and uJ is the study-level residual error term. The Level 1 equation describes the impact of the hypothesized contingency effects, business settings, sales performance measure, model characteristics, and study characteristics, which vary at the study level. The Level 2 equation describes the effect of unobserved study characteristics on the intercept and slopes in the Level 1 equation. Table 2 presents the variables entered in the model and expected effects.

Table 2 Summary of variables and expected effects
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Results

Frequency distribution of salesperson performance elasticities

The frequency distributions are displayed in Fig. 2. The overall mean elasticity is .15 (SD = .26), reflecting the individual (M = .18, SD = .29) and team (M = .12, SD = .21) drivers. Although the overall mean elasticity is positive, it is below the .34 elasticity value indicated by a previous sales meta-analysis using studies conducted during 1971–2009 (Albers et al., 2010). This finding indicates that salesperson effectiveness over the last 13 years has decreased by 56% compared with before 2009. This decrease may be associated with the proliferation of relational selling and partnering relationships in the past decade (Palmatier et al., 2006), which produce intensified competition, increased product complexity, and better informed and more demanding customers (Albers et al., 2010). Compared with their predecessors from previous decades, salespeople need to increase their effort (performance drivers) to achieve the same performance.

Fig. 2
figure 2

Frequency distribution of salesperson performance drivers (Study 1: Elasticity sample)

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Hypotheses testing

Table 3 contains the results of the HLM regression to test the study hypotheses. We used two statistics to verify model fit: the Akaike information criterion (AIC), Bayesian information criterion (BIC), and deviance (−2 log-likelihood ratio), as in previous elasticity meta-analyses (You et al., 2015). The null model (intercept-only) produces a higher AIC value (null: 10; full: 4), deviance (null: 4; full: −42), and lower BIC value (null: 21; full: 89), so the full model (all variables) achieves better fit. As hypothesized (H1), salesperson drivers’ elasticities dramatically decreased by 57% over the time frame of the data (β = −.039, p < .05), falling from .255 in 2007 to .112 in 2018. This result reflects the challenges faced by salespeople who must find ways to offer value to customers who have become more informed (Hochstein et al., 2019), prefer digital platforms (Arli et al., 2018; Hoar, 2015), and have more alternative options due to increased competition (Paesbrugghe et al., 2017). The latter results in greater pressure on salespeople to adopt solution-selling and consultative approaches as a way of gaining competitive advantage (Salonen et al., 2021). Furthermore, we find marginally significant results for H2’s individual/team driver effect (β = .088, p = .052) indicating that the individual drivers performance effects (predicted elasticity = .189) are 86% greater than team drivers (predicted elasticity = .101). Individual drivers (e.g., selling skills; Hughes et al., 2013) help salespeople establish and maintain successful customer relationships (Hughes et al., 2013), gain direct customer knowledge, and cocreate solutions with customers (Gonzalez & Claro, 2019). Finally, the performance benefits of salesperson drivers are significantly lower (.106) in the United States than in other countries (.187), which confirms H3 (β = −.081, p < .05). This result matches prior research with similar results related to personal selling performance (Albers et al., 2010) or advertising–sales results (Farley & Lehmann, 1994). Greater selling efforts drive greater performance in other countries, compared with the United States.

Table 3 Estimation results of salesperson performance elasticity effects
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We also consider some control variables and find that salesperson drivers’ elasticities for products in late stages of their lifecycles are higher (.183) than those in early stages (−.072), suggesting the challenges salespeople face in selling new products (Ahearne et al., 2010). Among the data, model, and study characteristic controls, if the study did not use yearly data for the dependent variable, used other than cross section data, used performance measure at the salesperson level, did not control for endogeneity, did not use semi-log functional form, was not a published study, and 2/3 of authors were in marketing, the elasticity would be higher. We conducted several checks to ensure the robustness of the elasticity meta-analysis results (Web Appendix F).

Discussion

The elasticity-based meta-analysis in Study 1 provides parsimonious theoretical insights into issues related to the dynamic and global drivers of salesperson effectiveness. The overall performance effect of salesperson drivers is positive and has diminished in the past decade. We find a greater performance effect of salesperson individual drivers compared to team drivers, though a marginally significant coefficient. We also note that the effectiveness of salesperson selling strategies depends on country-specific characteristics. The Study 1 results strongly support our hypotheses, as the logic underlying our conceptual framework is based on elasticities, which are appropriate effect sizes to use in a meta-analysis focused on assessing salespeople’s effectiveness (Albers et al., 2010). In Study 2, we further investigate the conceptual framework by assessing the strength of the correlation of specific salesperson drivers and performance, as well as country development and cultural contingencies.

Study 2: Specific salesperson drivers across country-level contingencies effects

In Study 2, we use a correlation-based meta-analysis following the well-established tradition for meta-analyses in sales (Churchill et al., 1985; Verbeke et al., 2011) and related fields, such as relationship marketing (Samaha et al., 2014). The correlation-based data reflects the extent of similarity or strength of the relationships between selling strategies and performance outcomes and thus preclude any causal inferences. However, correlation-based effects result in larger samples than an elasticity meta-analysis, because interval scaled measures are considered, and correlations are the most common metric reported (>95%). Also, correlation measures are appropriate for making comparisons between constructs such as selling strategies and performance outcomes that largely use scale measures (Babić Rosario et al., 2016; Eisend, 2006). The different aims and outcomes of the elasticity and correlation meta-analyses offer a deeper understanding of salesperson drivers and country contingencies.

Salesperson individual versus team performance drivers

Salesperson individual drivers (selling skills, motivation, and attitude) and performance outcomes are distinct but related constructs, as salesperson individual drivers refer to enduring or learned personal characteristics that salespeople leverage to manage their external relationships with customers (Verbeke et al., 2011), whereas performance outcomes refer to salespeople’s complex and varied behavior assessed with regard to its contribution to the aims of the firm (Bolander et al., 2021). The constructs entail acknowledging, valuing, and addressing customers’ needs (Blessing & Natter, 2019) and developing customer relationships (Hughes et al., 2013). We predict a positive association between the salesperson’s a) selling skills (e.g., the ability to listen to the customer, and communicate properly; Dietvorst et al., 2009; Hall et al., 2015), attitudes (e.g., emotional intelligence; Kidwell et al., 2011), and motivation (e.g., brand effort; Hughes & Ahearne, 2010), and b) performance outcomes (e.g., salesperson’s outcomes, customer conversion, and customer relationships; Bolander et al., 2021).

Salesperson teams drivers (intrafirm relationship and coordination activity) are also expected to be associated with performance outcomes, as salesperson teams refer to the efforts made by the salesperson to access firm resources and gain internal support to develop customer solutions (Hochstein et al., 2019) and deliver superior value to customers (Dugan et al., 2019). As such, we expect a positive association between the salesperson’s a) intrafirm relationships (e.g., leveraging of resourceful internal relationships and sharing of learned proficiencies, such as managing team conflict; Auh et al., 2014), and coordination activities (e.g., gathering information and other resources, or influencing others, such as managing internal networks; Gonzalez et al., 2014), and b) performance outcomes.

Although intrafirm relationships and team coordination activities are important sources of resources and knowledge, the correlation between salesperson individual drivers and performance outcome are expected to be greater. Because individual drivers entail abilities and characteristics that are fundamental to managing customer relationships and addressing customer needs (Mullins et al., 2014; Payne et al., 2017). Internal relationships and network coordination can help salespeople address customers’ needs, by mobilizing internal resources and gaining influence over others through internally coordinated information exchanges (Auh et al., 2014) and access to expertise (Steward et al., 2010), however they can be substituted by individual drivers and play a less central role than individual drivers in customer value creation. We thus posit:

H4

The positive correlations between selling skills, aptitude, and motivation and performance outcomes are greater than the positive correlations of intrafirm relationships and coordination activity and performance outcomes.

Country-level contingencies

We argue that specific country development characteristics (market heterogeneity, unbranded competition, resource availability, infrastructure, sociopolitical governance; Sheth, 2011) condition the strength of the correlation between salesperson selling strategies and performance outcomes. We draw on Sheth’s (Sheth, 2011) country development framework and its underlying factors, which captures significant differences across more versus less developed countries (Arunachalam et al., 2019). We predict two country contingency effects.

First, in contexts characterized by market heterogeneity and unbranded competition salesperson drivers should be more strongly correlated with performance, as in such contexts the salesperson experiences more options and opportunities for recognizing and addressing customers’ needs (Blessing & Natter, 2019) and delivering superior value to customers (Dugan et al., 2019). Such activities and aims are at the basis of both salesperson drivers and performance outcomes. Greater market heterogeneity, which refers to more heterogeneity in volume and consumption patterns among and across customers in country markets (Sheth, 2011), offers more opportunities for salespeople to identify and fulfill diverse customer segments’ needs. Thus, by gaining information about each customer segment and its unique product and service demands, affordability standards, and accessibility levels (Sinha & Sheth, 2018), they can find ways to cocreate solutions with them, enhance their awareness, and share information about available offerings. High unbranded competition, as occurs in country markets where customers’ needs are fulfilled by local producers who sell unbranded products (Sheth, 2011), also offers opportunities for salespeople. They might direct their efforts toward product and process innovations that can convert non-users into first-time branded product users, by presenting offerings effectively and encouraging customers to adopt solutions to the problems they experience with unbranded, low-quality goods (Sheth, 2011). Intrafirm relationships and coordination activity may help salespeople mobilize internal resources to develop appropriate solutions (Gonzalez et al., 2014). The lack of branded competition then gives salespeople more room to come up with and launch new products, using their skills to shape customers’ demands (Arunachalam et al., 2019).

Second, in contexts characterized by high resource availability and quality infrastructure, as well as superior sociopolitical governance, salesperson drivers should be more weakly correlated with performance, because in these contexts the salesperson has less options and faces more constraints to deliver customer value (Arli et al., 2018), a key concept underlying both salesperson drivers and performance. Resource availability and quality infrastructure (e.g., communication technology, banking functions, transportation capacity; Sheth, 2011) are associated with more efficient, consistent, and profitable production, exchanges, and consumption (Bahadir et al., 2015). Better offerings and more autonomous salespeople and customers (Foss et al., 2015) make it more difficult to attract customers’ attention (O'Cass & Weerawardena, 2010). Salespeople also have a good safety net, so they may feel less pressure to pursue sales conversions doggedly (Pipedrive, 2017). Moreover, countries with superior sociopolitical governance, characterized by free markets, few protective rules, privately owned firms, and low institutional risk (Sheth, 2011), are attractive business environments that promote more competitive, better quality offerings. Customers also tend to be more demanding (Jones et al., 2005), so salespeople must devote more attention to them (Albers et al., 2010), and firms likely need to invest in more marketing- and market-focused learning capabilities to compensate for the lower expected correlation of marketing efforts with performance (O'Cass & Weerawardena, 2010). We therefore posit:

H5

The positive correlation between salesperson drivers and performance outcomes is stronger in countries with high (a) market heterogeneity and (b) unbranded competition and weaker in countries with high (c) resource availability, (d) infrastructure, and (e) sociopolitical governance.

Despite the criticism for being more static than other country-development factors (Bahadir et al., 2015), cultural factors may be relevant to international sales and the extent to which salespeople need to adjust their selling strategies (e.g., Fang et al., 2004; Hohenberg & Homburg, 2016, 2019). Therefore, we predict that the country’s masculinity, long-term orientation, power distance, and uncertainty avoidance can also help explain the predicted variability in selling strategies-performance correlations. First, in contexts characterized by higher masculinity, selling strategies should be more weakly correlated with performance, as the salesperson faces more restrictions to develop customer relationships and deliver value (Hughes et al., 2013), key aspects for both selling strategies and performance outcomes. Members of masculine cultures are driven by individual performance and achievement motives (Magnusson et al., 2014), a strong focus on material possessions (Rouziès et al., 2017), and competitiveness (Hofstede et al., 2010), so confrontation between parties is common (Samaha et al., 2014). Neither salespeople nor customers would be open or responsive to activities associated with nurturing relationships (Kale & Barnes, 1992), reciprocating relational benefits (Hofstede et al., 2010), or managing positions in networks (Magnusson et al., 2014; Samaha et al., 2014).

Second, in countries that score high on long-term orientation, power distance, and uncertainty avoidance, selling strategies should be more strongly correlated with performance, because the salesperson has more chances to identify customers’ needs and mobilize resources to address those needs, as well as to develop customer relationships (Blessing & Natter, 2019). In long-term–oriented countries, salespeople and customers are more prone and responsive to building and developing strong, long-term (internal and external) relationships or network management (Hohenberg & Homburg, 2016). Connectedness with others is key, as is the expansion of individual competences and personal abilities (Deci & Ryan, 2004; Hohenberg & Homburg, 2016). People in high power distance countries also comply with hierarchical structures and accept the inequality that accompanies status (Hohenberg & Homburg, 2016). They look for behaviors that make them appear powerful (Hofstede et al., 2010), and expertise is acknowledged as a form of status, reflecting superior knowledge and competence (Samaha et al., 2014). Acceptance of hierarchies also is associated with good connections with others, because improving status requires strong relationships with superiors or peers, which results in more access to resources through network positioning.

Finally, members of high uncertainty avoidance cultures feel threatened by uncertain, ambiguous, and unknown situations and embrace predictability and stability (Murphy & Li, 2012; Samaha et al., 2014). Salespeople look to enhance their competence by improving their abilities and proficiency in specific tasks or challenges (Hohenberg & Homburg, 2016), and customers are motivated to reduce risk by finding sellers with expertise that can provide more and better quality information and assurances that reduce their risk and generate more predictable outcomes (Hansen et al., 2011). Both salespeople and customers also are more open and responsive to activities associated with building and nurturing relationships and managing positions in networks, to reduce uncertainty and risk (Samaha et al., 2014). Longer-term, stable relationships and networks are key, as customers and salespeople look for familiarity and stability and want to avoid change (Hohenberg & Homburg, 2016). They avoid acting independently to address new challenges, which could leave them accountable for potential failures (Hofstede et al., 2010), and instead rely on social norms that emerge from existing relationships and networks (Hansen et al., 2011). We thus posit:

H6

The positive correlation between salesperson drivers and performance outcomes is weaker in countries with high (a) masculinity and stronger in countries with high (b) long-term orientation, (c) power distance, and (d) uncertainty avoidance.

Method

Data collection and coding

To further investigate the relationship between salesperson drivers and performance pertaining to the conceptual framework depicted in Fig. 1, we adopt a correlation meta-analytic approach (e.g., Fern & Monroe, 1996; Verbeke et al., 2011). Departing from the initial list of published and unpublished studies collected in Study 1, we selected studies with a correlation matrix or e-mailed the authors to request it when missing. We then expanded our search of relevant studies in the various scientific databases mentioned in Study 1 (see Web Appendix A). Two independent coders used the definitions in Table 4 to code the data and resolved any coding differences through discussion (overall agreement >97%). In Study 2, we used objective and subjective measures and referred carefully to the original scales and items reported in each study, to avoid combining dissimilar elements or separating conceptually similar variables inappropriately, even if the studies used different labels to refer to the same constructs. We gathered a total of 2,532 correlation effects in 328 studies reported in 301 manuscripts (see details in Web Appendix A, D and E). The sub-sample with known countries includes 2,288 effects in 309 studies reported in 282 manuscripts from 32 countries on 6 continents and 112 unique country-year records (Table 5). The combined N = 126,766 is used to calculate the effect size estimates.

Table 4 Summary of variables and representative research
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Table 5 Forest plot of correlation effects by country and country sample characteristics
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To correct reported correlations for measurement error, we divided each correlation coefficient by the product of the square root of the two construct reliabilities (Hunter & Schmidt, 2004). If reliability was not reported, we used the average reliability for that construct across all studies in our sample. We next transformed the reliability-corrected correlations into Fisher’s z coefficients, weighted by the estimated inverse of their variance (N – 3), then converted them back to correlation coefficients (Kirca et al., 2005). Finally, to assess the file drawer problem, we calculated the fail-safe N, or the number of unavailable studies with null results that would be needed to reduce the cumulative effect across studies to non-significance.

We also collected a panel of development and cultural indicators of countries from multiple sources (Table 4) for all countries and years in the sample. To assess the effects of each country-specific contingency, using country-of-study information, we entry the country indicator scores in our meta-analysis data from two years prior to the publication of the study. If the indicator was missing, we entered the score from the closest year. With a continuum perspective on country development, we classified countries as more or less developed, given the level of the country indicator. Finally, we coded control variables for business settings, sales performance measures, data, and study characteristics, as we did in Study 1 (Table 2), using the sample description provided by each study.

Model estimation and analysis

Our analytical approach follows recommendations for correlation-based meta-analytic techniques (Borenstein et al., 2011; Grewal et al., 2018) and uses a comprehensive software suite (Stata 17) for the analyses (Palmer & Sterne, 2016). In the initial analysis, we evaluated the correlation between salesperson drivers and performance outcomes (Table 6, Panel A).Footnote 2 For each studied effect, we calculated the number of raw effects, total N, simple average r, average r adjusted for reliability, reliability-adjusted sample-weighted average r (Fisher’s z), 95% confidence intervals, publication bias (i.e., fail-safe N), and a homogeneity test (i.e., Q-statistic that indicates homogeneity in the true correlations for each effect). We also evaluate how the correlation between each salesperson driver and performance vary for each country-specific contingency moderator (Table 6, Panel B). We estimated the HLM regression using the same specification for Levels 1 and 2 as described in Study 1.

Table 6 Results of salesperson individual and team drivers with performance outcomes and contingency effects
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Results and discussion

The overall mean adjusted for reliability correlation is .20 (SD = .23) (frequency distribution in Web Appendix G). The results of a univariate analysis reveal that individual and team drivers have positive, significant correlations with performance outcomes (Table 6, Panel A). The fail-safe sample size (N), or the number responses in unpublished papers required to nullify an effect, ranged between 828 and 22,120, so publication bias does not appear to be an issue. The check for heterogeneity, which relies on Q-statistics, affirms that the true effects vary across studies (meta-analysis tests in Web Appendix H). On the basis of 306 and 167 raw effects and 119,284 and 64,712 responses, we find that individual drivers (r = .28, p < .01) and team drivers (r = .20, p < .01), respectively, are positively correlated with performance outcomes. Assessing the confidence intervals, the correlation between individual drivers and performance is greater (40%) than between team drivers and performance, as predicted in H4. Specifically, selling skill (r = .32, p < .01), aptitude (r = .33, p < .01), motivation (r = .24, p < .01), intrafirm relationships (r = .20, p < .01), and coordination activity (r = .21, p < .01) display positive correlations with performance outcomes.

Table 6 (Panel B) contains the results of the HLM regression to test the country contingency hypotheses. The null model (intercept-only) produces a higher AIC value (null: 6412; full: 5844), deviance (null: 6406; full: 5802), and lower BIC value (null: 6430; full: 5964), so the full model achieves better fit. The correlation between salesperson drivers and performance outcomes has decreased over time (β = −.148, p < .01), and individual drivers have a higher correlation with performance outcomes than team drivers (β = .102, p < .01). These correlation effects are therefore in line with the elasticity results in Study 1. When assessing specific country contingency effects, we find no significant moderating effect of market heterogeneity (H5a), but the correlation is stronger in countries with high unbranded competition (β = .120, p < .05), in support of H5b. In unbranded competition countries, the correlation of salesperson drivers with performance is stronger when identifying and delivering value to diverse customer segments (Arunachalam et al., 2019), likely by suggesting innovative processes and offerings when the predominant, informal competition offers poor quality products that cannot resolve customers’ problems (Sheth, 2011). They also might enjoy improvisation advantages by adopting nontraditional, groundbreaking strategies to reach consumers (Jones, 2012). The positive correlation between salesperson drivers and performance outcomes is weaker in countries with high resource availability (β = −.127, p < .05), in support of H5c. Due to the superior offerings associated with strong production and commercialization chains (Bahadir et al., 2015), salespeople likely encounter more autonomous and demanding customers (Sheth, 2011), which increases the challenge in attracting their attention (Albers et al., 2010). Finally, we find non-significant moderating effects of infrastructure and sociopolitical governance (H5d and H5e).

When we investigate the cultural values, the positive correlation between salesperson drivers and performance outcomes is stronger in long-term–oriented countries (β = .166, p < .01), in support of H6b. Salespeople and customers are prone and responsive to build and develop strong and long-term customer and intrafirm relationships. Such cultures also support salespeople in their efforts to satisfy basic needs for competence and relatedness (Deci & Ryan, 2004). However, no other cultural values affect the salesperson drivers-performance correlation.

Finally, several control variables are significant. Outcome and conversion performance measures exhibit weaker correlation than relationship measures (β = .092, p < .05), but no business settings are significant. When any study in our sample uses dyadic data, the correlation is weaker than those obtained with single source (β = −.085, p < .05). Regarding study characteristics, the correlation in published studies is stronger than in unpublished (β = .093, p < .01) but the correlation is weaker when published in a high ranked journal (β = −.104, p < .05) and using large sample sizes (β = −.052, p < .05). We conducted several checks to ensure the robustness of the results and present the findings and implications in Web Appendix F.

General discussion and implications

Theoretical implications

Dynamic salesperson performance drivers

The Study 1 findings unveil the dynamics of salesperson drivers and identify a decrease of up to 57% in the effectiveness of personal selling over the past 13 years (2009–2021) and up to 56% relative to decades before 2009 (Albers et al., 2010). This decrease has been noted previously by researchers, who point to the increasing difficulty salespeople face to add value to purchasing processes (Hochstein et al., 2019). The escalating complexity of the marketplace and increasingly aggressive competition have had strong impacts on their roles, including minimizing their relevance as sources of information and support in finding the right product or service (Hochstein et al., 2019). Furthermore, salespeople experience more pressure from their employers to outperform competition by developing a stronger consultative, solution-based role, which is more demanding than past roles (Salonen et al., 2021). In this context, salespeople need to adapt their selling strategies, which requires assessing the extent to which customers are informed (Hochstein et al., 2019), understanding their need and preference for digital versus interpersonal interactions in the communication mix (Zoltners et al., 2022), and determining the extent of reengineering of their sales role to attend to customers’ increasing demands (Hoar, 2017).

Salesperson individual and team drivers

We propose and empirically validate a comprehensive, parsimonious framework that encompasses a wide range of salesperson drivers. Previous sales meta-analyses neglected team drivers (e.g., Albers et al., 2010; Ohiomah et al., 2020; Verbeke et al., 2011), but our results in Study 1 show that both team and individual drivers lead to effective selling strategies. Though both individual and team drivers lead to enhanced performance outcomes, the performance effect of individual drivers still is greater (86% larger elasticity) than that of team drivers drawing on marginally significant results. The individual performance drivers remain the most critical for creating and delivering customer value (Payne et al., 2017). Customer relationships established by individual salespeople cannot be replaced easily (Mayer & Greenberg, 2006). Although the internal resource mobilization, knowledge access, and social capital that result from team drivers can help salespeople in their value-adding role, they also imply challenges, including managing the dark side of intrafirm relationships (Dugan et al., 2019). The Study 2 findings show that the correlation between performance and individual drivers (i.e., selling skill and aptitude) are greater than with the specific team drivers (i.e., intrafirm relationship and coordination activity).

Country contingencies and salesperson effectiveness

We contribute to existing sales literature by showing how specific country characteristics condition the effectiveness of salespeople’s efforts (Albers et al., 2010; Verbeke et al., 2011). In Study 1, we determine that such efforts are less effective in the United States than elsewhere, which likely depends on each country’s level of development (Sheth, 2011) and short-term–oriented culture (Hohenberg & Homburg, 2016). Our analysis helps address conflicting results in prior sales literature and suggests potential explanations for the negative performance effects of salesperson drivers found in research in developed countries (Blessing & Natter, 2019; Coelho et al., 2011). The benefits of salespeople’s adaptive selling have been widely investigated at local levels (Román & Iacobucci, 2010), but few studies consider such contingencies in international contexts (Bush et al., 2001; Koponen et al., 2019). We provide empirical evidence of the appropriateness of adapting selling strategies to different country settings and thereby contribute to emerging international sales theory. In Study 2, evidence from 32 countries show that unbranded competition, resource availability, and long-term orientation all influence the correlation between salesperson drivers and performance. As an empirical contribution to theory, the Study 2 evidence, representing 83% of world GDP, reveals varying levels of development along the considered factors, which suggests the generalizability of the results.

Meta-analyses implications

Finally, we make an important methodological contribution, by providing empirical evidence of the different, yet relevant roles played by elasticity and correlation-based meta-analyses. Serving different purposes and implying diverse advantages and limitations, when used together, these two meta-analyses establish effect sizes that provide different lens for understanding of the investigated phenomena. The elasticity meta-analysis is suitable for assessing salesperson effectiveness and corresponding country-level contingencies, but it is limited in terms of data (i.e., specific salesperson drivers, country and country-year sample size), because few studies report elasticity of objective measures of studied effects. Thus, we can only assess its effectiveness on an aggregate level (e.g., individual versus team drivers). The correlation effect sizes represent larger data sets, because correlations are reported for all the pair of constructs in the study, and there is less restriction with regard to the measures. It is also possible to make comparisons between metrics that use different measurements scales (Babić Rosario et al., 2016). Thus, correlation effect sizes adhere to meta-analysis traditions in sales and related fields (Samaha et al., 2014; Verbeke et al., 2011), also broadening the scope of the meta-analysis, and decreasing sampling and non-sampling errors (Peterson & Brown, 2005). But they cannot capture effectiveness and instead indicate the strength of the correlation between salesperson drivers and performance. Future meta-analyses should consider the trade-offs of the effect sizes and use them to have different insights of a studied phenomenon.

Managerial implications

With customers increasingly questioning whether the salesperson adds value or simply is redundant (Hochstein et al., 2019), firms should adapt their selling strategies to be more effective. For example, hybrid sales structures might combine inside and outside salespeople; inside sales can focus on specialized selling activities and reduce total sales cost (Chaker et al., 2022; Ramos et al., 2023). On a global scale, firms and salespeople might implement adaptive, specific selling strategies that account for the complexity of the local selling environment and development and cultural factors. For example, our Study 1 results show that managers gain more from their selling effort in less developed countries rather than more developed ones such as the United States. In such less developed countries, firms can exploit the lack of competition from branded goods, and their salespeople should leverage individual drivers to learn about customer needs and present innovative solutions, while mobilizing internal team resources to improve the offerings and address unresolved customer problems (Jones, 2012). In turn, salespeople can develop an adaptive selling strategy (Baalbaki & Malhotra, 1995; Bush et al., 2001; Mandler et al., 2021) that matches each country development level and cultural values.

Managers also should implement effective hiring, onboarding, and training practices to tap into critical selling skills (Cespedes & Lee, 2017), then establish one-to-one peer mentorship or monitoring by line managers (Claro et al., 2020) to help salespeople maintain these skills. We recommend that firms gather county-level knowledge and develop market intelligence to inform their selling strategies. In less developed markets, where customers rarely participate in the sales process, firms benefit particularly from developing salespeople’s skills to shape customer expectations and offer innovative products and processes, as well as from team relationships that increase access to internal knowledge (Claro & Ramos, 2018). In more developed countries, firms might invest in digital tools to facilitate technology-driven customer experiences or process automation.

Limitations and research directions

As in any other research, the empirical results should be interpreted with some limitations in mind, and with the understanding that in some cases, these limitations open avenues for continued research. First, we analyze the impact of individual and team drivers on sales performance separately, given the lack of research that includes both drivers in the same study, so we cannot determine their interaction effects. Previous research suggests they are often used simultaneously by salespeople (Bolander et al., 2015), and further research should test for such interaction effects as new databases of published papers become sufficient to do so. Second, we focus on country-level contingencies to understand how salesperson drivers contribute or are correlated to performance outcomes in different countries. However, some countries also feature regional-level variations; the level of market heterogeneity and extent of unbranded competition may differ across regions in China, the United States, and Brazil for example. Finer-grained assessments could provide input for continued, in-depth research.

Third, despite our concerted efforts to include all performance driver–related studies over a 13-year period, we acknowledge that some contributions may have been unintentionally excluded. Salesperson team drivers are a relatively recent research topic, compared with individual drivers, so the number of effects included are imbalanced. However, the fewer effects for team drivers were still sufficient for the meta-analyses of the core relationships (Grewal et al., 2018). As more studies of team drivers become available, updated meta-analyses could complement our findings. Fourth, our findings are based on compelling country evidence from two meta-analyses. We were not able to include the cultural characteristic of individualism in our analyses, due to high multicollinearity, as noted in previous international research (Samaha et al., 2014). Although we conducted robustness checks that exclude identification problems and provide stability to our model and results, additional research might address the effect of an individualistic culture. Fifth, we could not always obtain exact data about each contingency factor for the two years prior to a study’s publication or for each country-of-study context, so we assigned the closest available score in some cases. We anticipate little concern about this limitation though, because country-of-study scores vary little across subsequent years.