Sales–Supply Chain Management Collaboration: Performance Effects and Boundary Conditions for International Salespeople

Abstract

While interfunctional collaboration remains well-studied within the marketing literature, this research is the first to empirically explore the effects of sales–supply chain management (S-SCM) collaboration among salespeople selling internationally. Survey data from 310 international salespeople provide initial empirical evidence showing that S-SCM collaboration can positively predict international salesperson performance outcomes. To show that the effect is unique and provide rare empirical evidence, the authors simultaneously account for the effects of multiple forms of cross-functional collaboration (i.e., sales–marketing collaboration and sales–research and development collaboration). Matching the survey responses with objective country-level data, the authors also find that the value of S-SCM collaboration varies across countries. In particular, the positive effects of S-SCM collaboration were amplified by logistics capacity (or “logistics friendliness”) at the country level. The study's findings also indicate that the positive performance returns provided by S-SCM collaboration are even stronger for international salespeople focused on customer acquisition (vs. customer retention). Broadly, the study implies that, for optimal firm performance, those who are responsible for managing global supply chains should coordinate activities with those responsible for selling to global customers.

Keywords

sales–supply chain management collaboration international salespeople interfunctional collaboration supply chain management supply chain disruption

Global supply chain disruptions (e.g., Goodman 2021; Helper and Soltas 2021) have recently created additional challenges for salespeople selling internationally.¹ For example, product shortages due to factory closures in parts of the world, shipping delays due to congested ports and labor shortages, increased prices, and the like have only increased the levels of uncertainty and risk that salespeople must manage with their international buyers. Moreover, unfulfilled orders due to supply chain issues have left many buyers in search of new suppliers (i.e., wanting to diversify the supply base; Alicke et al. 2022). To effectively navigate such challenges (e.g., manage global customer expectations) and capitalize on emergent opportunities (meet global customer demand), salespeople and sales organizations must adapt. Accordingly, this research explores cross-functional collaboration with supply chain management (SCM) as a factor that might help international salespeople adapt (Mohsen and Eng 2016) and be a source of competitive advantage (Allred et al. 2011; Foerstl et al. 2013).

Against this background, the current research was motivated by two related literature gaps and makes two primary contributions. First, with few exceptions (e.g., Hohenberg and Homburg 2016; Zhou and Charoensukmongkol 2022), very little is known about the drivers of job performance for international salespeople in general (Schrock et al. 2018). Further, the lack of knowledge about specific forms of cross-functional collaboration driving salesperson performance in an international context has been noted (Panagopoulos, Rapp, and Ogilvie 2017). While the sales function's relationships with research and development (R&D; Ernst, Hoyer, and Rübsaamen 2010), service (Rapp et al. 2017), and marketing (e.g., Chernetsky, Hughes, and Schrock 2022) have received various attention in the literature, the sales function's relationship with SCM operations within a firm remains overlooked. This gap is noteworthy to the extent that, in practice, sales and SCM are indeed interdependent (e.g., sales forecasting activities; Glatzel, Großpietsch, and Silva 2011) and the ability of salespeople—particularly international salespeople—to meet customer needs is aided or constrained by a firm's SCM capabilities.² Compared with domestic analogues, international purchase and fulfillment processes can be more complex (e.g., customs clearance processes, inventory and transportation from origin considerations; David 2022) and carry more uncertainty and risk (e.g., information security risk, regulatory risk; Luo 2022). Thus, we believe an exploration of the effects of S-SCM collaboration in an international selling context is both apt and timely, as managing uncertainty and mitigating risk are top priorities for salespeople and global supply chain managers alike (Alicke et al. 2022; Ulaga and Kohli 2018). It is worth noting here that intrafirm collaboration is an area of focus among SCM scholars (e.g., Esper et al. 2010; Oliva and Watson 2011; Pellathy et al. 2019). Table 1 delineates ways in which our research complements and extends this important work (e.g., distinct research focus, level of analysis, research implications). With a focus on international salespeople, the current research thus contributes initial empirical evidence to advance understanding of the effects of sales–supply chain management (S-SCM) collaboration. Importantly, the evidence accounts (controls) for the effects of other forms of cross-functional collaboration (i.e., sales–marketing collaboration, sales–R&D collaboration).

Table 1.

This Article and Other Relevant Literature Focused on SCM's Cross-Functional Collaboration.

	Pellathy et al. (2019)	Esper et al. (2010)	Oliva and Watson (2011)	This Article
Research focus	Antecedents and consequences of “SCM's cross-functional integration”	A strategic conceptual framework of demand/supply integration	Antecedents of cross-functional alignment	Drivers of international salesperson performance
Functions in focus	SCM and all departments or functions (i.e., integration in general)	SCM, sales, and marketing (e.g., advertising, market research, branding)	SCM, sales, and finance	SCM and sales
Unit of analysis	Firm level	Firm level	Firm level	Salesperson level
International focus	No	No	No	Yes
Methodological approach	Regression analysis (survey data)	Conceptual	Case study	Regression analysis (survey data and secondary, country-level data)
Sample	364 “SCM professionals currently holding managerial positions in U.S. companies” (p. 88)	N.A.	Single firm (consumer electronics industry)	310 international salespeople based in the U.S. (across industries)
Some key findings	SCM's cross-functional integration is predicted by supply chain–IT integration SCM's cross-functional integration predicts supply chain performance	N.A.	Alignment can be achieved even without aligned formal incentives Involving sales in supply chain planning can facilitate alignment, and attributes of the process matter	S-SCM collaboration positively predicts salesperson performance The effects are conditional on country-level characteristics and the salesperson’s behavioral focus (i.e., customer acquisition)
Key implication	When areas of the supply chain work across functional boundaries, supply chains perform better.	When supply-focused and demand-focused activities are integrated, SCM helps create customer value and competitive advantage.	Despite differences in outlook, goals, and incentives across functions, cross-functional alignment can be achieved.	Within the firm, those responsible for managing increasingly global supply chains should coordinate activities with those responsible for selling to global customers.

Notes: N.A. = not applicable.

Second, although a positive impact of S-SCM collaboration on international sales performance is logical and expected in the main, assuming equally positive effects across countries and sales activities is questionable and may lead to inefficient resource allocation or suboptimal strategies. Indeed, cross-functional collaboration literature in marketing (e.g., sales–marketing interface literature) has been “concentrated geographically” and lacks insight into how effects might vary across countries (Chernetsky, Hughes, and Schrock 2022). Thus, and to augment understanding of boundary conditions for the effects of S-SCM collaboration, we conceptualize S-SCM collaboration as a job resource for salespeople and leverage the job demands–resources (JD-R) theory (e.g., Bakker and Demerouti 2007). Accordingly, we examine logistics capacity as a country-level resource that has synergistic effects with S-SCM collaboration. Moreover, we examine customer acquisition focus as a job demand that strengthens S-SCM collaboration's performance effects. As such, this research also contributes to an improved understanding of varying performance implications of S-SCM collaboration as a job resource across international selling contexts. For managers, this research broadly suggests that, for optimal performance, S-SCM collaboration should be a strategic consideration within the firm. More specifically, the study indicates that international salespeople selling to countries with high levels of logistics capacity and/or those focused on customer acquisition receive higher returns to S-SCM collaboration.

The rest of this article is organized as follows. We next describe our theoretical background, introduce the study's focal constructs, and develop hypotheses. We then discuss the research methodology and results. Finally, we offer research limitations and directions for future research.

Theoretical Background and Hypothesis Development

Applying the Job Demands–Resources Theory

Proposition 1 of the JD-R theory (Bakker and Demerouti 2017) states that all job characteristics or working conditions fall into one of two categories: job demands and job resources. Job demands are “physical, psychological, social or organizational aspects of the job that require sustained physical or psychological (cognitive and emotional) effort or skills” (Bakker and Demerouti 2007, p. 312). Job resources are all aspects of the job that facilitate work goal attainment and personal development (Bakker and Demerouti 2007). The theory states that job demands and job resources have main and multiplicative effects that can predict or explain job performance as well as other job outcomes (Bakker and Demerouti 2014). For a theoretical understanding of relationships among the key constructs in our model, we leverage JD-R theory as a guide.

Consistent with extant research on the nature of collaboration (e.g., Bedwell et al. 2012; Lin, Wang, and Kung 2015), we define S-SCM collaboration as the degree to which the sales and supply chain management functions within a firm coordinate objectives, actively engage in joint activities, and have a productive working relationship. Importantly, S-SCM collaboration encompasses more than a simple willingness to politely email documents back and forth (Ashkenas 2015). Rather, at high levels of S-SCM collaboration, the two functions share goals and incentives (Chernetsky, Hughes, and Schrock 2022), cooperate (e.g., Malshe and Al-Khatib 2017), learn from each other and develop mutual understanding (e.g., Le Meunier-FitzHugh and Piercy 2007a), and work together as a team (e.g., Malshe, Johnson, and Viio 2017). This conceptualization parallels extant views of sales–marketing collaboration (e.g., Le Meunier-FitzHugh and Piercy 2007b) and marketing–SCM collaboration (e.g., Jüttner, Christopher, and Baker 2007). Accordingly, we theorize S-SCM collaboration as a job resource for salespeople, to the extent that the collaboration represents an organizational or social aspect of the job facilitating work goal attainment (Demerouti et al. 2001).

Logistics capacity refers to the “logistics friendliness” of a given country, a conceptualization consistent with the World Bank's country-level operationalization of “logistics performance” (The World Bank 2018a). The World Bank's Logistics Performance Index accounts for six components, selected based on empirical research and the input from logistics professionals from around the globe (World Bank 2018a). The components are (1) border management clearance and customs efficiency, (2) trade and transportation infrastructure quality, (3) “the ease of arranging competitively priced shipments” (World Bank 2018a), (4) the quality and competence of logistics services, (5) the “ability to track and trace consignments” (World Bank 2018a), and (6) the timeliness with which shipments reach their destinations. In the most recent survey available (The World Bank 2018b), Germany received the highest score on this measure; Afghanistan received the lowest. Taking a JD-R theoretic perspective, we conceptualize logistics capacity as a collection of resources (e.g., infrastructure such as ports, roads, or railroads) that varies by country and can be leveraged to the salesperson's advantage. To the extent that SCM capabilities can be enhanced by infrastructure, technology, and visibility (Dolgui and Ivanov 2022), a theoretical accounting for this form of resource is of modern and practical importance.

Customer acquisition focus refers to the degree to which salespeople spend their time engaged in activities aimed at developing relationships with new customers (e.g., generating and following leads; Sabnis et al. 2013). This focus reflects the extent to which salespeople spend time exploring new business opportunities and “hunting” prospects (Lam, DeCarlo, and Sharma 2019). This focus can be contrasted with a customer retention focus (Carter et al. 2014), or the degree to which salespeople spend time exploiting existing customer relationships or “farming” (Lam, DeCarlo, and Sharma 2019). Importantly to a JD-R theoretic perspective, customer acquisition involves high levels of uncertainty, pressure, learning, risk, discomfort, and rejection (Lam, DeCarlo, and Sharma 2019). Accordingly, we theorize customer acquisition as a job demand that carries psychological costs and requires significant effort and skill (Bakker and Demerouti 2007). For two primary reasons, our research focuses on customer acquisition as a job demand. First, as Lam, DeCarlo, and Sharma (2019) describe, customer acquisition can be considered a more “difficult task” associated with “a higher rate of failure than farming existing customers” (Lam, DeCarlo, and Sharma 2019, p. 672). Second, to the extent that global customers are increasingly looking to diversify their supply bases (e.g., during and since the COVID-19 pandemic; Alicke et al. 2022), a theoretical accounting for this job demand is of real-world importance for marketing and sales organizations today.

S-SCM Collaboration as a Driver of International Sales Performance

Proposition 2 of JD-R theory states that job resources have positive motivational effects, which should increase job engagement and job effectiveness (Bakker and Demerouti 2017). Correspondingly, and for two main reasons, we expect that S-SCM collaboration, a job resource, will positively affect salesperson performance. First, we expect that salespeople well-integrated with SCM operations at their firm can effectively reduce some uncertainty and risk inherent to customer decision making. Particularly during—and after—international crises such as the COVID-19 pandemic (Gunessee and Subramanian 2020), we anticipate that effective salespeople can better resolve buyer uncertainties about product availability, processing times, carrier prices, whether deliveries will be made when and where needed, and so on. This expectation complements perspectives that view managing customer uncertainty as a primary role of salespeople (i.e., a role that can indeed require cross-functional support; Ulaga and Kohli 2018). Second, salespeople well-integrated with SCM operations at their firm should be better able to effectively manage—and thus meet—customer expectations. We anticipate that these salespeople can, for example, more quickly and accurately share pertinent information with customers about inventory issues or parts shortages (which could slow production, delay shipping, lengthen lead times, lead to stockouts and rationing, cause conflict and customer dissatisfaction, etc.).

Conceptualizing cross-functional relationships as a job resource for salespeople is consistent with the work of Sleep, Bharadwaj, and Lam (2015, p. 477), who took a JD-R theory perspective when suggesting the following: “In order to meet long-term customer-oriented objectives, the sales function should develop relationships with other functions within the firm to acquire resources.” This suggestion aligns with the longstanding view that salesperson effectiveness is a function of selling-firm resources (Weitz 1981), including information and expertise stemming from intrafirm relationships (e.g., Steward et al. 2010). The foregoing considered, we propose the following hypothesis:

H₁: S-SCM collaboration is positively related to international salesperson performance.

The Moderating Role of Logistics Capacity

As noted previously, we conceptualize logistics capacity as a collection of resources that varies by country and can be leveraged to the salesperson's advantage. We propose that salespeople who are well-integrated with SCM operations at their firm can better utilize those resources (e.g., high-quality logistics services). From the organizational buyer's perspective, we expect that S-SCM collaboration is an evaluative criterion that receives more (less) attention and is deemed more (less) important in countries with maximum (minimum) logistics capacity.

Accordingly, we expect a synergistic interaction between S-SCM collaboration and logistics capacity (see Figure 1). For example, we expect that the ability of salespeople who are well-integrated with SCM operations to reduce customer uncertainty about lead times should be strengthened when border control agency processes are quick, relatively simple, and predictable. Similarly, these same salespeople's ability to reduce buyer uncertainty about carrier prices should be strengthened when it is relatively easy to arrange competitively priced shipments from many carriers. Otherwise, we expect that the ability of salespeople who are well-integrated with SCM operations to manage (and thus meet) customer expectations is enhanced in countries with high levels of logistics capacity. For example, these salespeople's ability to share timely information and manage customer expectations should be enhanced when relevant telecommunications/IT infrastructure is in place at ports and when the ability to trace shipments is high. Consistent with this rationale, we expect that S-SCM collaboration and logistics capacity are resources that complement each other's ability to drive international salesperson performance. It is worth noting that JD-R literature has not focused on resource × resource interactions to date. Thus, a test of the following interactive effect hypothesis also represents a novel application of JD-R theory:

H₂: The positive relationship between S-SCM collaboration and international salesperson performance is strengthened as the logistics capacity at the country level increases.

Figure 1.

Conceptual Model.

The Moderating Role of Customer Acquisition Focus

Proposition 4 of JD-R theory states that job resources become “particularly useful and motivating” when job demands are high (Bakker and Demerouti 2017, p. 275). That is, challenging job situations (e.g., converting an unknown prospect into a customer) can activate employees to engage, learn, and take advantage of available and needed resources at work (Bakker and Demerouti 2017). In accordance with this theoretical proposition, we propose that S-SCM collaboration is a more (less) advantageous resource for salespeople in selling situations geared toward customer acquisition (retention). In particular, we anticipate that S-SCM collaboration's capacity to reduce customer uncertainty and positively affect sales performance is heightened in selling situations characterized by the uncertainty and risk inherent to a lack of personal relationships (e.g., no history of trust and fairness) and a lack of business results (e.g., unknown ability to meet customer expectations).

We expect that buyer mindsets differ in buying situations that consider taking on new suppliers, compared with buying situations with existing suppliers. In selling situations focused on retaining or growing existing business, we expect that the salesperson's history of promises kept (or not kept) is a chief evaluative criterion for buyers. For buyers in these situations, there are fewer unknowns. Moreover, in these situations, we expect that S-SCM collaboration, as a selling point, is already accounted for and thus creates less incremental revenue for salespeople. In contrast, in buying situations that consider taking on a new supplier, we expect that promises made—and, importantly, the resources that allow salespeople to keep their promises (Grönroos 2009)—are chief concerns. There are more unknowns for buyers in these situations (e.g., the selling firm's capability to deliver on promises made). Accordingly, we expect that S-SCM collaboration gains importance in these selling situations, particularly at a time when supply chain disruptions are prevalent globally. Ultimately, and consistent with Proposition 4 of JD-R theory, we expect that S-SCM collaboration, as a salesperson resource and driver of buyer behavior, becomes more advantageous in international selling situations focused on acquiring new business.

H₃: The positive relationship between S-SCM collaboration and international salesperson performance is strengthened as the salesperson's focus on customer acquisition increases.

Methodology

Sample and Data Collection

With the assistance of a leading market research firm, we collected data from salespeople working in the United States who sell internationally. To qualify for the study, participants needed one of the following job titles: salesperson, sales manager, export manager, global account manager, or account executive. Additionally, qualifying respondents had to report that at least 5% of their individual sales since 2019 were generated from international buyers. Respondents passing these screening questions were then asked to identify the country responsible for the majority of their international sales revenue. Three hundred ten salespeople qualified and participated in the study. On average, 51% of the salespeople's revenue was from international buyers. The salespeople identified 31 countries as primarily responsible for their international sales revenue. The top ten countries were the United Kingdom, Canada, Germany, China, Japan, France, Mexico, Australia, South Korea, and India. Table 2 shows summary information about the sample.

Table 2.

Sample/Respondent Summary.

Experience
			Mean	Min	Max
Years working at current company			7.2	1	47
Years selling to customers in selected country			5.5	1	37
Industry (Top 6)
Manufacturing (e.g., tools, automotive)					37%
Consumer goods (e.g., food and beverage, apparel)					19%
Financial services					10%
Construction and real estate					8%
B2B professional services (e.g., IT, human resources)					7%
Agriculture					7%
Company Size (Distribution Based on Number of Employees)
1–10	11–50	51–100	101–500	501–1,000	>1,000
6%	9%	15%	34%	24%	12%
Frequency of Formal Face-to-Face Meetings with Customers in Selected Country
Never		Rarely	Sometimes	Often	Always
12%		14%	23%	26%	25%

Measures

Items measuring international sales performance indicated how well salespeople performed in the specific country identified in the screening question since the COVID-19 pandemic (1 = “much worse,” and 5 = “much better”). According to Bolander et al. (2021), this financial performance measure can be classified as outcome-based and comparative. The S-SCM collaboration measure was developed based on items from Troilo, De Luca, and Guenzi (2009) as well as intrafirm collaboration literature highlighting the importance of relationship quality (e.g., Le Meunier-FitzHugh, Massey, and Piercy 2011; Malshe, et al. 2017; Massey and Dawes 2007). The measure of customer acquisition focus was adapted from Carter et al. (2014). Salespeople were given 100 percentage points to allocate and asked to indicate how they spend their time in three categories (acquiring new customers, retaining existing customers, and educating customers) for two time periods: before and since the COVID-19 pandemic. The two time periods were used to create a change score (i.e., after COVID − before COVID). Thus, the acquisition focus measure reflects the extent of a “strategic pivot” on the part of the salesperson and aligns with the nature of the outcome variable (i.e., sales performance since COVID). The country-level measures of logistics capacity were from The World Bank's “Logistics Performance Index” (The World Bank 2018a). We controlled for several country- (ease of doing business, global connectivity), firm- (sales–marketing collaboration, sales–R&D collaboration, company size), industry- (market uncertainty), and salesperson- (age, experience) level variables. Table 3 shows descriptive statistics and correlations. The Appendix shows all constructs, items, and data sources.

Table 3.

Descriptive Statistics and Correlations.

Construct	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. International salesperson performance	3.70	.81	.68
2. S-SCM collaboration	4.15	.62	.29	.58
3. Logistics capacity	3.79	.34	.25	.09	—
4. Customer acquisition focus	−1.89	16.14	.16	−.08	−.03	—
5. Sales–marketing collaboration	4.19	.58	.31	.52	.00	−.03	.55
6. Sales–R&D collaboration	4.13	.58	.28	.60	.01	−.01	.57	.55
7. Global connectivity	60.17	8.86	.21	.03	.81	.02	−.04	−.03	—
8. Ease of doing business	26.82	21.54	.15	.09	.73	−.04	.00	.00	.79	—
9. Company size	3.96	1.33	.02	.08	.08	−.13	.06	.00	−.03	−.02	—
10. Market uncertainty	3.87	.65	.21	.29	.06	.01	.26	.26	−.09	−.07	.05	.51
11. Salesperson experience	7.19	4.91	−.19	.05	−.09	−.15	−.04	.01	−.05	−.08	.05	−.03	—
12. Salesperson age	41.18	8.41	−.13	−.06	−.09	−.12	−.01	−.12	−.04	−.06	.02	−.02	.47	—

Notes: Bold font = statistically significant at the .05 level (two-tailed). AVE values are on the diagonal.

Results

Measurement

We evaluated reliability, convergent validity, and discriminant validity for all latent constructs. Composite reliabilities for the latent variables ranged from .75 to .92, indicating that the measures are internally consistent. Factor loadings for all manifest indicators on their related latent variables were significant and positive. Moreover, the average variance extracted (AVE) values for all latent constructs were higher than .50. The AVE values were also higher than the squared correlations with other variables, indicating that discriminant validity is not a concern (Fornell and Larcker 1981). A measurement model with all latent constructs studied fit the data well (comparative fit index = .945; root mean square error of approximation = .047; standardized root mean square residual = .047).

We believe that common method variance (CMV) should not significantly impact our effects of interest for two reasons. First, we use distinct data sources, including secondary sources (e.g., The World Bank) and primary sources with questions in different formats (e.g., time allocation percentages; see the Appendix). Second, given that it generally deflates interaction effects in regression models, CMV should not be able to account for any statistically significant interaction effects (Podsakoff, MacKenzie, and Podsakoff 2012; Siemsen, Roth, and Oliveira 2010). Yet, to assess the presence of CMV, we use the marker variable technique with a measure of “blue attitude” (Miller and Simmering 2022). High correlations between the (theoretically unrelated) marker variable and the model's focal constructs would indicate the presence of common method bias (Lindell and Whitney 2001). We find that the average correlations between “blue attitude” and the study's focal constructs (r_performance = −.006, n.s.; r_{S−SCM collab.} = .067, n.s.; r_{acq. focus} = −.061, n.s.) were not statistically different from zero. Moreover, when we partial out the effects of the marker variable, the sign and significance of all correlations in our study do not change (Lindell and Whitney 2001). Collectively, these findings provide evidence that CMV does not bias our results.

Endogeneity

To account for potential endogeneity, we include a robust set of control variables (Sande and Ghosh 2018). Further, we took measures to assess the possibility of endogeneity issues in the model with two-stage least squares estimation (Ullah, Zaefarian, and Ullah 2021). We use a measure of product variety as an instrument. Prior research indicates that the need for supply chain collaboration within the firm increases with levels of product variety (Shou et al. 2017), in support of the relevance criterion. Simultaneously, extant research indicates that product variety's effects on performance are equivocal (Zhao et al. 2020), in support of the exclusion criterion. As expected, we find that product variety is positively correlated with the endogenous regressor (S-SCM collaboration; r = .19, p < .05) but uncorrelated with the dependent variable, sales performance (r = .07; n.s.). The first-stage F-statistic (10.963) was positive and significant, suggesting that the chosen instrument is strong and relevant. The Durbin (p = .717) and Wu–Hausman (p = .719) tests were also both insignificant, indicating that endogeneity is not an issue in our model (the null hypothesis is that the predictors are exogenous; e.g., Ullah, Zaefarian, and Ullah 2021). Based on the suggestion that ordinary least squares (OLS) is more efficient in such situations (Ullah, Zaefarian, and Ullah 2021), we report the OLS results in Table 4 (Sande and Ghosh 2018).

Table 4.

OLS Results.

Dependent Variable = International Salesperson Performance
Variables		β	Hypothesis
Controls
	Global connectedness	.06
	Ease of doing business	−.05
	Market uncertainty	.11*
	Sales–marketing collaboration	.15*
	Sales–R&D collaboration	.03
	Company size	−.01
	Salesperson experience	−.16**
	Salesperson age	.02
Simple effects
	S-SCM collaboration (H₁)	.15*	Supported
	Logistics capacity	.23*
	Customer acquisition focus	.18**
Interactive effects
	S-SCM collaboration × Logistics capacity (H₂)	.14*	Supported
	S-SCM collaboration × Customer acquisition focus (H₃)	.10*	Supported

*p < .05.

**p < .01.

Notes: All p-values are based on two-tailed tests.

Hypothesis testing

We tested our hypotheses using OLS regression in Stata 15. We centered the independent and moderator variables when creating interaction terms. H₁ posits that S-SCM collaboration is positively associated with international salesperson performance. The results in Table 3 indicate a positive and significant relationship between the two variables (β = .15, p < .05), supporting H₁. H₂ suggests that the positive relationship between S-SCM collaboration and international salesperson performance is strengthened at high levels of logistics capacity. As indicated in Table 3, the interaction term was positive and significant (β = .14, p < .05). To confirm the nature of the interaction, we plotted the results (Figure 2, Panel A) and conducted simple slopes analysis. The interaction plot and simple slopes analysis provide support for H₂. At high levels of logistics capacity, the relationship between S-SCM collaboration and international sales performance (B = .39, p < .01) is stronger than the relationship between the two variables at low levels of logistics capacity (B = .01, n.s.). H₃ suggests that the positive relationship between S-SCM collaboration and international sales performance is strengthened as customer acquisition focus levels increase. As indicated in Table 3, the interaction term was positive and significant (β = .10, p < .05). To confirm the nature of the interaction, we plotted the results (Figure 2, Panel B) and conducted simple slopes analysis. The interaction plot and simple slopes analysis provide support for H₃. At high levels of customer acquisition focus, the relationship between S-SCM collaboration and international salesperson performance (B = .32, p < .01) is stronger than the relationship between the two variables at low levels of customer acquisition focus (B = .07, n.s.).

Figure 2.

S-SCM Collaboration and International Salesperson Performance Under Varying Levels of Logistics Capacity and Customer Acquisition Focus.

Discussion

Motivated by in-depth interviews with international salespeople, this research explored S-SCM collaboration as a job resource that might help salespeople navigate global SCM challenges. We found that S-SCM collaboration can explain significant variance in international sales performance, controlling for various country-, industry-, firm- (e.g., sales–marketing, sales–R&D collaboration), and salesperson-level variables. Results also show that the value of S-SCM collaboration as a resource varies across countries. Specifically, the positive effects of S-SCM collaboration were amplified by logistics capacity (“logistics friendliness”) at the country level. The study's findings also indicate that S-SCM collaboration can particularly facilitate performance for those international salespeople focused on customer acquisition (vs. retention).

Our study complements and pushes the boundaries of extant international marketing and sales literature, including studies on cross-functional teamwork in global SCM (Hult et al. 2000) and studies noting the importance of coordinating international sales activities with other functional departments (Schrock et al. 2018). The theoretical implications are threefold. First, we contribute needed insight into drivers of performance for international salespeople. While meta-analyses are dedicated to salesperson performance drivers (Verbeke, Dietz, and Verwaal 2011), according to a recent review (Schrock et al. 2018), only roughly 6% of sales articles are international in scope. Moreover, salesperson performance drivers specified in an international context are often personal characteristics or selling techniques, such as cultural intelligence (Zhou and Charoensukmongkol 2022), emotional intelligence (Kadic-Maglajlic et al. 2016), and adaptive selling (Rippé et al. 2016). Thus, our study helps build practically relevant and needed knowledge about organizational determinants of international salesperson success. Broadly, our results indicate that international salespeople benefit³ from information flows about SCM operations at their firm, which may now be “inherently global” in nature (e.g., foreign suppliers and foreign buyers; David 2022, p. 54).

Second, and relatedly, this study contributes to interfunctional coordination literature. While the sales function's relationships with R&D, service, and marketing functions have received considerable research attention over time, its relationship with the SCM function has not. Thus, our exploration of S-SCM collaboration augments understanding of cross-functional collaboration in marketing literature and responds to calls for research into the relationship between sales and nonsales employees in an international context (Panagopoulos, Rapp, and Ogilvie 2017). Further, within the broader interfunctional coordination literature, sales–marketing interface research specifically has recently called for studies that account for “various country-level indices” and noted a lack of insights about country-level contingencies (Chernetsky, Hughes, and Schrock 2022, p. 167). Although the focus of this study is not the sales–marketing interface, the results indicate that the impact of cross-functional collaboration does vary across countries.

Third, building on the work of Sleep, Bharadwaj, and Lam (2015), we leverage JD-R theory to study a specific form of cross-functional collaboration as a job resource for salespeople. In particular, our theoretical model specifies that the value of S-SCM collaboration as a job resource is contingent on job demands (customer acquisition activities) and other job resources (logistics capacity at the country level). From a JD-R theory perspective, our test of a resource × resource interaction is theoretically novel and provides a new lens for examining complementary job resources that might facilitate job performance. Moreover, and for international salespeople in particular, our results indicate that job resources can be conceptualized and measured at the country level.

As performance returns to S-SCM collaboration may vary significantly across countries, we recommend as an early step that managers assess relevant countries’ logistics capacity levels. According to our data, it is important for salespeople selling in high-logistics-capacity countries (e.g., Germany) to be well-integrated with SCM operations at their firm. It is in these countries where S-SCM collaboration can pay the most dividends for salespeople. Differently, S-SCM collaboration may be less advantageous for salespeople selling to low-logistics-capacity countries (e.g., Afghanistan), as the value of such collaboration is constrained by various elements of infrastructure, customs clearance process efficiencies, the availability and quality of transportation services, and so on. Finally, our data suggest that S-SCM collaboration pays the most dividends for salespeople focused on acquiring new customers. Thus, for international sales organizations with hunter–farmer structures, our data imply that hunters should be especially attuned to SCM operations at their firm. Otherwise, sales force structure notwithstanding, our data suggests that S-SCM collaboration can be particularly helpful (i.e., a performance-enhancing job resource) for salespeople looking to establish new business relationships globally. Broadly, we hope that our research redirects some of the significant practitioner attention paid to the sales–marketing interface (Chernetsky, Hughes, and Schrock 2022). More specifically, we hope to spur a wider conversation about internal collaboration in global sales settings, such that it also includes the importance of international logisticians and supply chain managers (David 2022).

Limitations and Future Research Directions

Our research has limitations that we hope will impel future studies. First, we stop short of exploring how S-SCM collaboration develops. Thus, future research specifying antecedents and providing step-by-step guidance for international sales managers would be valuable. Second, this research does not specify mechanisms linking S-SCM collaboration to international salesperson performance. As such, future research can identify salesperson-level (e.g., self-efficacy) and customer-level (e.g., perceptions of expertise; McClure et al. 2022) mediators of our focal relationship. Third, given our across-firm survey methodology, we rely on self-reported performance measures. While we recognize support for the validity of such measures (e.g., Sharma, Rich, and Levy 2004), we also recognize that objective performance measures have benefits. Fourth, financial performance is the only outcome that we investigate in the current research. Interesting future research could account for a wider range of outcomes (e.g., measures of customer retention, customer education outcomes). Examining multiple outcomes simultaneously could shed light on interesting trade-offs or unintended consequences.

Fifth, we recognize that our study does not distinguish between specific areas within the SCM function (e.g., procurement, operations, logistics), and a given firm may not have a single SCM department. Rather, and consistent with existing research (e.g., Pellathy et al. 2019), our survey instrument asked about “supply chain management operations” more generally. As such, one potentially fruitful opportunity for future research is inquiry aimed at teasing out the effects of collaboration between the sales function and specific departments that might constitute the SCM function within the firm. Sixth, our research is focused on S-SCM collaboration (given our measures, among other factors). Yet, we acknowledge that scholars have distinguished between collaboration and cooperation (e.g., Ashkenas 2015), and others have distinguished between collaboration and integration (e.g., Le Meunier-FitzHugh and Piercy 2007b). To the extent that these constructs exist on a continuum (e.g., cooperation as lowest form and integration as highest form), future research unraveling the effects of these related-but-different forms of cross-functional exchange would provide novel insights.

Footnotes

Appendix: Construct Measures

Acknowledgments

The authors would like to express their gratitude to Evangelia Demerouti and Justin Lawrence for their helpful input in the development of this paper. The authors would also like to thank the JIM review team for their helpful guidance throughout the review process.

Special Issue Editors

Nawar Chaker, Johannes Habel, Alex Zablah, and Kelly Hewett

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported financially by a Dean’s Office Summer Research Grant from the Eli Broad College of Business and a UCRCA research grant from the University of Nebraska at Omaha.

ORCID iD

Wyatt A. Schrock

Notes

References

Alicke

Knut

Barriball

Edward

Foster

Tacy

Mauhourat

Julien

Trautwein

Vera

(2022), “Taking the Pulse of Shifting Supply Chains,” McKinsey & Company (August 26), https://www.mckinsey.com/business-functions/operations/our-insights/taking-the-pulse-of-shifting-supply-chains.

Allred

Chad

Fawcett

Stanley

Wallin

Cynthia

Magnan

Gregory

(2011), “A Dynamic Collaboration Capability as a Source of Competitive Advantage,” Decision Sciences, 42 (1), 129–61.

Ashkenas

Ron

(2015), “There’s a Difference Between Cooperation and Collaboration,” Harvard Business Review (April 20), https://hbr.org/2015/04/theres-a-difference-between-cooperation-and-collaboration.

Bakker

Arnold

Demerouti

Evangelia

(2007), “The Job Demands-Resources Model: State of the Art,” Journal of Managerial Psychology, 22 (3), 309–28.

Bakker

Arnold B.

Demerouti

Evangelia

(2014), “Job Demands–Resources Theory,” in Wellbeing: A Complete Reference Guide, Vol. 3: Work and Wellbeing, Peter Y. Chen and Cary L. Cooper, eds. John Wiley & Sons.

Bakker

Arnold

Demerouti

Evangelia

(2017), “Job Demands–Resources Theory: Taking Stock and Looking Forward,” Journal of Occupational Health Psychology, 22 (3), 273–85.

Bedwell

Wendy L.

Wildman

Jessica L.

DiazGranados

Deborah

Salazar

Maritza

Kramer

William S.

Salas

Eduardo

(2012), “Collaboration at Work: An Integrative Multilevel Conceptualization,” Human Resource Management Review, 22 (2), 128–45.

Bolander

Willy

Chaker

Nawar N.

Pappas

Alec

Bradbury

Daniel R.

(2021), “Operationalizing Salesperson Performance with Secondary Data: Aligning Practice, Scholarship, and Theory,” Journal of the Academy of Marketing Science, 49 (3), 462–81.

Carter

Robert

Henderson

Conor M.

Arroniz

Inigo

Palmatier

Robert

(2014), “Effect of Salespeople’s Acquisition–Retention Trade-Off on Performance,” Journal of Personal Selling & Sales Management, 34 (2), 91–111.

10.

Chernetsky

Victor V.

Hughes

Douglas E.

Schrock

Wyatt A.

(2022), “A Synthesis of Research on the Marketing-Sales Interface (1984–2020),” Industrial Marketing Management, 105, 159–81.

11.

David

Pierre

(2022), International Logistics: The Management of International Trade Operations. Cicero Books.

12.

Day

George S.

(1994), “The Capabilities of Market-Driven Organizations,” Journal of Marketing, 58 (4), 37–52.

13.

Demerouti

Evangelia

Bakker

Arnold

Nachreiner

Friedhelm

Schaufeli

Wilmar

(2001), “The Job Demands-Resources Model of Burnout,” Journal of Applied Psychology, 86 (3), 499–512.

14.

Dolgui

Alexandre

Ivanov

Dmitry

(2022), “5G in Digital Supply Chain and Operations Management: Fostering Flexibility, End-to-End Connectivity and Real-Time Visibility Through Internet-of-Everything,” International Journal of Production Research, 60 (2), 442–51.

15.

Ernst

Holger

Hoyer

Wayne D.

Rübsaamen

Carsten

(2010), “Sales, Marketing, and Research-and-Development Cooperation Across New Product Development Stages: Implications for Success,” Journal of Marketing, 74 (5), 80–92.

16.

Esper

Terry L.

Ellinger

Alexander E.

Stank

Theodore P.

Flint

Daniel J.

Moon

Mark

(2010), “Demand and Supply Integration: A Conceptual Framework of Value Creation Through Knowledge Management,” Journal of the Academy of Marketing Science, 38, 5–18.

17.

Foerstl

Kai

Hartmann

Evi

Wynstra

Finn

Moser

Roger

(2013), “Cross-Functional Integration and Functional Coordination in Purchasing and Supply Management: Antecedents and Effects on Purchasing and Firm Performance,” International Journal of Operations & Production Management, 33 (6), 689–721.

18.

Fornell

Claes

Larcker

David F.

(1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, 18 (1), 39–50.

19.

Glatzel

Christoph

Großpietsch

Jochen

Silva

Ildefonso

(2011), “Is Your Top Team Undermining Your Supply Chain?” McKinsey & Company (January 1), https://www.mckinsey.com/business-functions/operations/our-insights/is-your-top-team-undermining-your-supply-chain.

20.

Goodman

Peter

(2021), “How the Supply Chain Broke, and Why It Won’t Be Fixed Anytime Soon,” The New York Times (October 22), https://www.nytimes.com/2021/10/22/business/shortages-supply-chain.html.

21.

Grönroos

Christian

(2009), “Marketing as Promise Management: Regaining Customer Management for Marketing,” Journal of Business & Industrial Marketing, 24 (5–6), 351–59.

22.

Gunessee

Saileshsingh

Subramanian

Nachiappan

(2020), “Ambiguity and Its Coping Mechanisms in Supply Chains Lessons from the Covid-19 Pandemic and Natural Disasters,” International Journal of Operations & Production Management, 40 (7–8), 1201–23.

23.

Helper

Susan

Soltas

Evan

(2021), “Why the Pandemic Has Disrupted Supply Chains,” The White House (June 17), https://www.whitehouse.gov/cea/written-materials/2021/06/17/why-the-pandemic-has-disrupted-supply-chains/.

24.

Hohenberg

Sebastian

Homburg

Christian

(2016), “Motivating Sales Reps for Innovation Selling in Different Cultures,” Journal of Marketing, 80 (2), 101–20.

25.

Hult

G. Tomas M.

Nichols

Ernest L.

Jr. Giunipero

Larry C.

Hurley

Robert F.

(2000), “Global Organizational Learning in the Supply Chain: A Low Versus High Learning Study,” Journal of International Marketing, 8 (3), 61–83.

26.

Min

Jin

Jason Lu

Zhou

Kevin Zheng

(2018), “How Can International Ventures Utilize Marketing Capability in Emerging Markets? Its Contingent Effect on New Product Development," Journal of International Marketing, 26 (4), 1–17.

27.

Jüttner

Uta

Christopher

Martin

Baker

Susan

(2007), “Demand Chain Management-Integrating Marketing and Supply Chain Management,” Industrial Marketing Management, 36 (3), 377–92.

28.

Kadic-Maglajlic

Selma

Vida

Irena

Obadia

Claude

Plank

Richard

(2016), “Clarifying the Influence of Emotional Intelligence on Salesperson Performance,” Journal of Business & Industrial Marketing, 31 (7), 877–88.

29.

Lam

Son

DeCarlo

Thomas E.

Sharma

Ashish

(2019), “Salesperson Ambidexterity in Customer Engagement: Do Customer Base Characteristics Matter?” Journal of the Academy of Marketing Science, 47 (4), 659–80.

30.

Le Meunier-FitzHugh

Kenneth

Massey

Graham R.

Piercy

Nigel F.

(2011), “The Impact of Aligned Rewards and Senior Manager Attitudes on Conflict and Collaboration Between Sales and Marketing,” Industrial Marketing Management, 40 (7), 1161–71.

31.

Le Meunier-FitzHugh

Ken

Piercy

Nigel F.

(2007a), “Does Collaboration Between Sales and Marketing Affect Business Performance?” Journal of Personal Selling & Sales Management, 27 (3), 207–20.

32.

Le Meunier-FitzHugh

Ken

Piercy

Nigel F.

(2007b), “Exploring Collaboration Between Sales and Marketing,” European Journal of Marketing, 41 (7–8), 939–55.

33.

Lin

Yichen

Wang

Yichuan

Kung

LeeAnn

(2015), “Influences of Cross-Functional Collaboration and Knowledge Creation on Technology Commercialization: Evidence from High-Tech Industries,” Industrial Marketing Management, 49, 128–38.

34.

Lindell

Michael K.

Whitney

David J.

(2001), “Accounting for Common Method Variance in Cross-Sectional Research Designs,” Journal of Applied Psychology, 86 (1), 114–21.

35.

Luo

Yadong

(2022), “A General Framework of Digitization Risks in International Business,” Journal of International Business Studies, 53 (2), 344–61.

36.

Malshe

Avinash

Al-Khatib

Jamal A.

(2017), “A Repertoire of Marketers’ Trust-Building Strategies Within the Sales-Marketing Interface,” Journal of Personal Selling & Sales Management, 37 (3), 213–27.

37.

Malshe

Avinash

Friend

Scott B.

Al-Khatib

Jamal

Al-Habib

Mohammed I.

Mohamed Al-Torkistani

Habiballah

(2017b), “Strategic and Operational Alignment of Sales-Marketing Interfaces: Dual Paths Within an SME Configuration,” Industrial Marketing Management, 66, 145–58.

38.

Malshe

Avinash

Johnson

Jeff S.

Viio

Paul

(2017), “Understanding the Sales-Marketing Interface Dysfunction Experience in Business-to-Business Firms: A Matter of Perspective,” Industrial Marketing Management, 63, 145–57.

39.

Massey

Graham R.

Dawes

Philip L.

(2007), “Personal Characteristics, Trust, Conflict, and Effectiveness in Marketing/Sales Working Relationships,” European Journal of Marketing, 41 (9–10), 1117–45.

40.

McClure

Colleen E.

Lawrence

Justin M.

Arnold

Todd J.

Scheer

Lisa K.

(2022), “The Opportunities and Costs of Highly Involved Organizational Buyers,” Journal of the Academy of Marketing Science, 1–22.

41.

Miller

Brian K.

Simmering

Marcia J.

(2022), “Attitude Toward the Color Blue: An Ideal Marker Variable,” Organizational Research Methods (published online February 1), https://doi.org/10.1177/10944281221075361.

42.

Mohsen

Kholoud

Eng

Teck-Yong

(2016), “The Antecedents of Cross-Functional Coordination and Their Implications for Marketing Adaptiveness,” Journal of Business Research, 69 (12), 5946–55.

43.

Oliva

Rogelio

Watson

Noel

(2011), “Cross-Functional Alignment in Supply Chain Planning: A Case Study of Sales and Operations Planning,” Journal of Operations Management, 29 (5), 434–48.

44.

Panagopoulos

Nikolaos

Rapp

Adam

Ogilvie

Jessica

(2017), “Salesperson Solution Involvement and Sales Performance: The Contingent Role of Supplier Firm and Customer–Supplier Relationship Characteristics,” Journal of Marketing, 81 (4), 144–64.

45.

Pellathy

Daniel A.

Mollenkopf

Diane A.

Stank

Theodore P.

Autry

Chad W.

(2019), “Cross-Functional Integration: Concept Clarification and Scale Development,” Journal of Business Logistics, 40 (2), 81–104.

46.

Piercy

Nigel F.

Cravens

David W.

Lane

Nikala

Vorhies

Douglas W.

(2006), “Driving Organizational Citizenship Behaviors and Salesperson In-Role Behavior Performance: The Role of Management Control and Perceived Organizational Support,” Journal of the Academy of Marketing Science, 34 (2), 244–62.

47.

Podsakoff

Philip M.

MacKenzie

Scott B.

Podsakoff

Nathan P.

(2012), “Sources of Method Bias in Social Science Research and Recommendations on How to Control It,” Annual Review of Psychology, 63 (1), 539–69.

48.

Rapp

Adam

Bachrach

Daniel

Flaherty

Karen

Hughes

Douglas

Sharma

Arun

Voorhees

Clay

(2017), “The Role of the Sales-Service Interface and Ambidexterity in the Evolving Organization: A Multilevel Research Agenda,” Journal of Service Research, 20 (1), 59–75.

49.

Rippé

Cindy

Weisfeld-Spolter

Suri

Dubinsky

Alan

Arndt

Aaron

Thakkar

Maneesh

(2016), “Selling in an Asymmetric Retail World: Perspectives from India, Russia, and the US on Buyer–Seller Information Differential, Perceived Adaptive Selling, and Purchase Intention,” Journal of Personal Selling & Sales Management, 36 (4), 344–62.

50.

Sabnis

Gaurav

Chatterjee

Sharmila

Grewal

Rajdeep

Lilien

Gary

(2013), “The Sales Lead Black Hole: On Sales Reps’ Follow-Up of Marketing Leads,” Journal of Marketing, 77 (1), 52–67.

51.

Sande

Jon Bingen

Ghosh

Mrinal

(2018), “Endogeneity in Survey Research,” International Journal of Research in Marketing, 35 (2), 185–204.

52.

Schrock

Wyatt

Zhao

Yanhui

Richards

Keith

Hughes

Douglas

Amin

Mohammad Sakif

(2018), “On the Nature of International Sales and Sales Management Research: A Social Network–Analytic Perspective,” Journal of Personal Selling & Sales Management, 38 (1), 56–77.

53.

Sharma

Arun

Rich

Gregory

Levy

Michael

(2004), “Comment: Starting to Solve the Method Puzzle in Salesperson Self-Report Evaluations,” Journal of Personal Selling & Sales Management, 24 (2), 135–39.

54.

Shou

Yongyi

Ying

Park

Young Won

Kang

Mingu

(2017), “The Impact of Product Complexity and Variety on Supply Chain Integration,” International Journal of Physical Distribution & Logistics Management, 47 (4), 297–317.

55.

Siemsen

Enno

Roth

Aleda

Oliveira

Pedro

(2010), “Common Method Bias in Regression Models with Linear, Quadratic, and Interaction Effects,” Organizational Research Methods, 13 (3), 456–76.

56.

Sleep

Stefan

Bharadwaj

Sundar

Lam

Son

(2015), “Walking a Tightrope: The Joint Impact of Customer and Within-Firm Boundary Spanning Activities on Perceived Customer Satisfaction and Team Performance,” Journal of the Academy of Marketing Science, 43 (4), 472–89.

57.

Steward

Michelle

Walker

Beth

Hutt

Michael

Kumar

Ajith

(2010), “The Coordination Strategies of High-Performing Salespeople: Internal Working Relationships That Drive Success,” Journal of the Academy of Marketing Science, 38 (5), 550–66.

58.

Sujan

Harish

Weitz

Barton A.

Kumar

Nirmalya

(1994), “Learning Orientation, Working Smart, and Effective Selling,” Journal of Marketing, 58 (3), 39–52.

59.

Troilo

Gabriele

de Luca

Luigi

Guenzi

Paolo

(2009), “Dispersion of Influence Between Marketing and Sales: Its Effects on Superior Customer Value and Market Performance,” Industrial Marketing Management, 38 (8), 872–82.

60.

Ulaga

Wolfgang

Kohli

Ajay

(2018), “The Role of a Solutions Salesperson: Reducing Uncertainty and Fostering Adaptiveness,” Industrial Marketing Management, 69, 161–68.

61.

Ullah

Subhan

Zaefarian

Ghasem

Ullah

Farid

(2021), “How to Use Instrumental Variables in Addressing Endogeneity? A Step-by-Step Procedure for Non-Specialists,” Industrial Marketing Management, 96, A1–6.

62.

Verbeke

Willem

Dietz

Bart

Verwaal

Ernst

(2011), “Drivers of Sales Performance: A Contemporary Meta-Analysis. Have Salespeople Become Knowledge Brokers?” Journal of the Academy of Marketing Science, 39 (3), 407–28.

63.

Weitz

Barton

(1981), “Effectiveness in Sales Interactions: A Contingency Framework,” Journal of Marketing, 45 (1), 85–103.

64.

The World Bank (2018a), “The Logistics Performance Index,” https://lpi.worldbank.org/about.

65.

The World Bank (2018b), “The Logistics Performance Index Methodology,” https://wb-lpi-media.s3.amazonaws.com/LPI%20Methodology.pdf.

66.

The World Bank (2020), “Doing Business 2020: Comparing Business Regulation in 190 Economies,” https://documents1.worldbank.org/curated/en/688761571934946384/pdf/Doing-Business-2020-Comparing-Business-Regulation-in-190-Economies.pdf.

67.

Zhao

Yanhui

Zhang

Yufei

Wang

Joyce

Schrock

Wyatt A.

Calantone

Roger J.

(2020), “Brand Relevance and the Effects of Product Proliferation Across Product Categories,” Journal of the Academy of Marketing Science, 48, 1192–1210.

68.

Zhou

Jihong

Charoensukmongkol

Peerayuth

(2022), “Cultural Intelligence and Adaptive Selling Behaviors in Cross-Cultural Selling: The Cognitive Resource Theory and Social Role Theory Perspective,” Journal of Business Research, 146, 477–88.