Customer orientation of B2B firms in emerging markets: evidence from Russia

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CUSTOMER ORIENTATION OF B2B FIRMS IN EMERGING MARKETS: EVIDENCE FROM RUSSIA

O.V. GULAKOVA, V.A. REBIAZINA,

Faculty of Business and Management,

National Research University Higher School of Economics, Russia

M.M. SMIRNOVA

Graduate School of Management, Saint Petersburg University, Russia



While the field of customer orientation (CO) has been studied extensively since the 1990s, there have hardly been any attempts to revisit the concept for the specifics of B2B markets, especially in the context of emerging economies. This paper explores the peculiarities of B2B firms' CO on the example of Russia. The empirical survey of 272 Russian B2B firms show that well-established CO measurement can be used as integrated complex measure. The results of our analysis demonstrate a critically important aspect of CO, which helps to differentiate the customer-oriented firms from those with only “declared” CO. The study indicates a need to critically assess widely used marketing concepts and their measurement in B2B markets of emerging economies.

Keywords: customer orientation, B2B, emerging markets, Russia.



Клиентоориентированность Б2Б-компаний на развивающихся рынках: результаты исследования российского рынка

О.В. Гулакова, В.А. Ребязина

Факультет бизнеса и менеджмента Национального исследовательского университета «Высшая школа экономики», Россия

М.М. Смирнова

Институт «Высшая школа менеджмента» Санкт-Петербургского государственного университета, Россия

Несмотря на то что клиентоориентированность (КО) начала широко изучаться с 1990-х гг., попыток пересмотреть эту концепцию с учетом специфики промышленных рынков, в частности в контексте развивающейся экономики, практически не предпринималось. В данной статье рассматриваются особенности КО В2В-компаний на примере развивающейся экономики России. Эмпирическое исследование среди 272 российских B2B-компаний показало, что распространенные инструменты оценки КО могут быть использованы в качестве интегрированной шкалы. Результаты анализа выявили очень важный аспект КО, помогающий различить клиенто-ориентированные компании и компании с лишь «декларируемой» КО. Исследование показывает необходимость критической оценки устоявшихся маркетинговых концепций и подходов к их измерению на B2B-рынках в развивающихся экономиках.

Ключевые слова: ориентация на клиента, промышленные рынки, Россия.



Introduction

While the economic effect of customer orientation (CO) implementation has been studied 0y researchers since the 1990s [Narver, Slater, 1990; Ruekert, 1992; Deshpande, Farley, Webster, 1993; Ellis, 2006; Jacob, 2006], the nature of client-oriented firms is still a source of ongoing discussion. As a result, there are various perspectives on CO conceptualization: as a decision making [Shapiro, 1988], as a market business logic [Kohli, Jaworski, 1990], as a corporate culture [Narver, Slater, 1990], and as a strategic marketing focus.

One of the key approaches to CO is its interpretation within the broader concept of market orientation (MO) [Shapiro, 1988; Heins, 2000; Ellis, 2006; Coley, Mentzer, Cooper, 2010; Sheppard, 2011; Roersen, Kraaijenbrink, Groen, 2013; Rozhkov, Rebiazina, Smirnova, 2014]. Researches consider CO as one of the MO components [Na- rver, Slater, 1990], an equal idea [Kohli, Jaworski, 1990] or an independent term [Deshpande, Farley, Webster, 1993].

However, existing studies, even those focused on B2B firms, do not investigate the peculiarities of CO in B2B as opposed to B2C markets. The studies on B2B samples do not consider the specifics of the B2B context either conceptually or through the lenses of concept operationalization [Siguaw, Simpson, Baker, 1998; Agarwa, Krishna Erramilli, Dev, 2003; Bigne et al., 2004; Kirca, Jayachandran, Bearden, 2005; Hsieh, Chiu, Hsu, 2008; Coley, Mentzer, Cooper, 2010; Roersen, Kraaijenbrink, Groen, 2013; Chakravarty, Kumar, Grewal, 2014; Ziggers, Henseler, 2016; Wang, Zhao, Voss, 2016; Smirnova, Rebiazina, Frosen, 2018; O'Dwyer, Gilmore, 2018].

This study aims to explore the nature of CO in B2B firms by verifying several existing measurement tools in the B2B context. The specifics of the research context of Russian emerging market provide an additional focus. With very few exceptions, there is insufficient research evidence on how CO performs and is understood by firms in emerging markets. The few examples are very time dispersed [Greenley, 1995; Golden, Johnson, Smith, 1995; Smirnova et al., 2011; Roersen, Kraaijenbrink, Groen, 2013; Smirnova, Rebiazina, Frosen, 2018]. Russia is a good example of a three decade long transformation from a centrally-planned to a market economy. This transformation still involves substantial changes in managers' perceptions of the core managerial concepts, including CO, as well as the level of customer sophistication and expectations. Moreover, CO was proclaimed to be a core driving force of the transformation process and one of the most important firms' strategic capabilities that replaced supplier orientation dominating the planned economy [Farley, Deshpande, 2006].

This study contributes to understanding the specifics of B2B firms' CO on the example of Russia's emerging economy. First, we critically review the existing literature on specifics of CO for both B2B markets and emerging economies. Then we conduct an empirical research on B2B firms in the Russian market. Our study helps to re-evaluate the specifics of CO in the context of both B2B markets and emerging economies and provides agenda for further research and potential adaptation of this concept for future studies.



Literature review. B2B market perspective: Existing research on CO

While there is a growing interest in CO, the number of publications on this topic in B2B markets is significantly less than in B2C markets. From 1995 to 2008 only about 10% of the total articles on MO are published in top B2B journals (Appendix 1). However, MO and CO are in the area of interest of B2B research [Liao et al., 2011; Frosen et al., 2016; Pekovic, Rolland, Ga- tignon, 2016; O'Dwyer, Gilmore, 2018]. Moreover, many studies use B2B samples but do not adjust methodology or interpret the results through the lenses of the B2B context; they apply well-established concepts in order to explain firm behavior in B2B markets, rather than explain the concept. The majority of B2B studies apply the measurement tools developed by [Narver, Slater, 1990; Jaworski, Kohli, 1993]. Depending on the scientific preferences and goals of the research the authors build their hypotheses and models on the general theory of CO [Liao et al., 2011; Iyer et al., 2018; Park et al., 2018].

The overview of existing B2B studies shows that the relationship between MO and firm performance is mostly positive, equally for the mixed B2B/B2C samples [Narver, Slater, 1990; Jaworski, Kohli, 1993; Slater, Narver, 1994; Homburg, Pfles- ser, 2000; Zhou, Brown, Dev, 2009; Smirnova et al., 2011; Wilden, Gudergan, Lings, 2018; Bommaraju et al., 2019]. [Dickson, 1992; Kohli, Jaworski, Kumar, 1993] explain the dilemma that consumer market producers face when implement the MO without the CO component. [Cooley, Ment- zer, Cooper, 2010, p. 142] emphasize this concern because “market-oriented producers have both retail customers, who help to facilitate the distribution of their products, and consumers, who buy the producer's products from the producer's customers, as well as competitors in their market space”.

B2B literature on CO predominantly focuses on comparisons between developed and emerging markets [Adhikari, Gill, 2011; Singh, Koshy, 2011] or between manufacturing and service firms [Agarwal, Krishna Erramilli, Dev, 2003; Kirca, Jayachandran, Bearden, 2005; Sin et al., 2005; Tsiotsou, 2010; Wang, Zhao, Voss, 2016], rather than on the differences in CO of B2C and B2B markets. However, an analysis of the directions of research shows that there are some specifics of investigating CO and MO in the B2B market [Coley, Mentzer, Cooper, 2010]. The overview of the existing literature identifies the following main dimensions, which are considered through the lenses of a B2B context in exploring the nature and the role of CO (Table 1).

Table 1. Existing research on B2B CO in emerging markets

			Level		Methodology		Focus on B2B context
Article	MO/ CO	Country	of co/ MO	Data collection method(s)	source of the measurement scale	sample	method(s) of analysis
1	2	3	4	5	6	7	8	9
[Golden, Johnson, Smith, 1995]	MO	Russia	Firm	Survey	[Snow, Hrebiniak, 1980]	200 B2B & B2C firms	ANOVA	No
[Chan Hung Ngai, Ellis, 1998]	MO	China	Firm	Survey	[Narver, Slater, 1990] (MKTOR)	73 B2B & B2C firms	Multiple linear regression	No
[Akimo va, 2000]	MO	Ukraine	Firm	Survey, indepth interviews	[Hooley, Lynch, Shepherd, 1990; Marinov et al., 1993]	221 B2B & B2C firms	Cluster analysis, ANOVA	No
[Hajjat, 2002]	CO	Middle East country*	Firm	Survey indepth interviews	[Hajjat, 2002] (CUSTOR)	197 B2B & B2C firms	CFA	No
[Kaynak, Kara, 2004]	MO	China	Firm	Survey	[Kohli, Jarworski, Kumar, 1993] (MARKOR)	179 B2B & B2C firms	EFA, CFA, cluster analysis, correlation analysis	Yes
[Farley, Desh- pande, 2006]	MO	Russia	Firm	Survey	[Deshpande, Farley, Webster, 1993; Deshpande, Farley, 1998]	158 B2B firms	ANOVA	Yes
[Ozer, Kogak, Qelik, 2006]	MO	Turkey	Firm	Survey	[Kohli, Jarworski, Kumar, 1993; Jaworski, Kohli, 1993; Narver, Slater, 1990; Desphande, Farley, 1998; Gray, Hooley, 2002]	1042 B2B firms	EFA, CFA	Yes
[Chung et al., 2011]	MO	China	Inter firm dyad	Survey	[Matsuno, Mentzer, Rentz, 2000]	99 B2B dyads (retailer-sup- plier)	CFA, SEM	Yes
[Smirnova et al., 2011]	MO	Russia	Firm	Survey	[Narver, Slater, 1990] (MKTOR)	158 B2B firms	CFA, SEM	Yes
[Roer- sen, Kraai- jenbrink, Groen, 2013]	MO	Russia	Firm	Survey	[Narver, Slater, 1990] (MKTOR)	10 B2B & B2C firms	Mean values analysis	No
[Sarkar, Mishra, 2017]	MO	India	Inter firm dyad	Survey, interviews	[Kohli, Jarworski, Kumar, 1993] (MARKOR)	174 B2B dyads (buyer- seller)	EFA, SEM	Yes
This study	CO	Russia	Firm	Survey, in-depth interviews	[Narver, Slater, 1990] (MKTOR) [Narver, Slater, MacLachlan, 2004; Deshpande, Farley, Wedster, 1993]	272 B2B firms	EFA, cluster analysis, content analysis	Yes

Note: * -- the author didn't specify country; ANOVA -- analysis of variance, EFA -- exploratory factor analysis, CFA -- confirmatory factor analysis, SEM -- structural equation modeling.

Resulting from our literature review, there are three main directions of research in B2B firms' CO. The first direction tries to identify CO of an individual salesmen even before the concept has been widely tested at the firm-level [Saxe, Weitz, 1982]. For B2B firms, CO on employee level has substantial importance as there are fewer customers and building strong relationships is vital part of business [Singh, Koshy, 2011; Farias, Torres, Cortez, 2017; Babu, 2018; Herhausen, De Luca, Weibel, 2018; Lussier, Hall, 2018].

The second direction of B2B marketing focuses on value creation [Viardot, 2017] and considers CO as a platform for customer value creation [O'Cass, Ngo, Siahtiri, 2012]. The role of CO is to positively affect relationship building and consequently value creation. This factor is even more important for current research as value creation in B2B markets is often only possible when customers are ready to co-create value. This highlights the critical role of CO as a driver of customer involvement and collaboration.

The third direction of B2B CO research is the relationship management framework [Charterina, Basterretxea, Landeta, 2016; Khan, Zolkiewski, Murphy, 2016; Bommaraju et al., 2019]. From this perspective, CO is a tool for developing relationships with customers. It is suggested that CO does not directly influence firm performance, it rather positively affect the ability to build relationships with customers, which in turn influence performance [Smirnova et al., 2011; Guo, Wang, 2015].

The emerging markets perspective in CO research: A focus on the Russian market The increasing interest in CO applies not only for firms in developed markets, but also in emerging markets, in particular in BRICS [Smirnova et al., 2011; Kraaijenbrink, Roersen, Groen, 2009; Rozhkov, 2014; Popov, Tretyak, 2014; Rozhkov, Rebiazina, Smirnova, 2014].

Since the beginning of 1990s the Russian economy has undergone several waves of changes that forced firms to revise their approaches to marketing, including CO. The transition of the Russian economy (from centrally planned to open market) made firms transfer from producer- to market- oriented [Farley, Deshpande, 2006]. The growing number of competitors, including foreign corporations, contributed to the adoption of marketing concepts from developed markets. However, lack of actual studies does not allow us to conclude how firms have adapted such concepts in a process of implementation. Those few studies published earlier demonstrate that the established concepts can be both misinterpreted [e. g. Roersen, Kraaijenbrink, Groen, 2013] or lead to unexpected results in new contexts [Smirnova, Rebiazina, Frosen, 2018].

In the first decade of the 2000s when the Russian economy showed a significant improvement in terms of stability and growth, firms could easily grow by following the market growth. But the newest challenges have been brought to Russian economy by the world economic crisis in 2008-2009, followed by the Russian currency crisis in 2014 and subsequent economic recession. Further growth or even survival during the 2010s required firms to revisit their strategies, including customer-related.

Existing research however can hardly grasp these developments, since the studies on the Russian market are fragmented and insufficient in comparison to existing studies on developed markets. Despite the obvious lack of a benchmark for Russian firms and little understanding of market-oriented strategies and behaviors, research shows that the significance of marketing increased among all types of Russian firms once the centrally planned economy was abandoned [Golden, Johnson, Smith, 1995; Akimova, 2000; Farley, Deshpande, 2006]. The results of the study by [Smirnova et al., 2011] confirmed that Russian B2B firms are more competitor-oriented. On the whole, studies identified a low level of CO in Russian firms [Farley, Deshpande, 2006; Roersen, Kraaijenbrink, Groen, 2013], highlighting need to identify the reasons and factors contributing to it.

The analysis of Russian and developed market literature shows the scholars' interest in CO but the lack of studies that apply this concept specifically in the B2B context. Despite the peculiar features of the B2B context there is no distinctive theoretical base for B2B studies. Most papers use B2B samples but extend their findings to both B2B and B2C markets. Common methods, models, and scales are used both for B2B and B2C research, but the specifics of CO in B2B markets raise a question about the adequateness of using general scales and the need for their adaptation.



Methodology Operationalization

In investigating the conceptual and operational nature of CO several measurement tools are usually used: MKTOR scale [Narver, Slater, 1990], 9-item scale of [Desh- pande, Farley, Webster, 1993] and proactive and reactive MO scale [Narver, Slater, MacLachlan, 2004]. Since the concept of CO is inextricably linked to MO, it was decided to use MKTOR scale as the basis for the questionnaire [Narver, Slater, 1990]. The MKTOR scale is adapted for and used in developed markets context. It evaluates CO in comparison with other elements of MO: competitor orientation and inter-functional coordination. The adoption procedure included potentially diverse items from existing scales, which might provide insights into the dimensionality and the content of the construct in the B2B context. The resulting scale involved MKTOR scale [Narver, Slater, 1990]; proactive and reactive MO scale and 9-item scale of [Desh- pande, Farley, Webster, 1993]. Our final instrument totaled 24 indicators (Table 2).

Table 2. Operationalization of variables for the scale of the quantitative empirical research

Indicator	indicator label	scale
1	2	3
K1	We are committed to customers	MKTOR [Narver, Slater, 1990]
K2	We create customer value
K3	We understand customer needs
K4	Customer satisfaction is one of our objectives
K5	We offered after-sales service
K6	We measure customer satisfaction
K7	We help our customers anticipate developments in their markets	Proactive market orientation [Narver, Slater, MacLachlan, 2004]
K8	We continuously try to discover additional needs of our customers of which they are unaware
K9	We incorporate solutions to unarticulated customer needs in our new products and services
K10	We brainstorm on how customers use our products and services
K11	We innovate even at the risk of making our own products obsolete
K12	We search for opportunities in areas where customers have a difficult time expressing their needs
K13	We work closely with lead users who try to recognize customer needs months or even years before the majority of the market may recognize them
K14	We extrapolate key trends to gain insight into what users in a current market will need in the future
K15	We constantly monitor our level of commitment and orientation to serving customer needs	Reactive market orien- taton [Narver, Slater, MacLachlan, 2004]. 9-item scale [Deshpande, Farley, Wedster, 1993]
K16	Our strategy for competitive advantage is based on our understanding of customers' needs
K17	We are more customer focused than our competitors
K18	I believe this business exist primarily to serve customers
K19	Data on customer satisfaction are disseminated at all levels of this business unit on a regular basis	Reactive market orien- taton [Narver, Slater, MacLachlan, 2004]
K20	We know our competitors well	9-item scale [Deshpande, Farley, Webster, 1993]
K21	We have a good sense of how our customers value our products and services
K22	We compete primarily based on product or service differentiation
K23	The customer's interest should always come first, ahead of the owners'
K24	Our products/services are the best in the business

Data collection process and sample description

The empirical data for the study was collected in 2015 in the form of online survey. The questionnaire was sent to the representatives of marketing and sales departments and top management of B2B firms. As a result, 310 responses were collected, 272 of them were appropriate for the further analysis (Appendix 2). After the data collection some representatives were interviewed to clarify the results. The study was built on the stratified sampling according to two criteria: (a) offering (B2B product or B2B services) and (b) location (federal cities -- Moscow and St. Petersburg -- and the other Russian regions).

The sample consisted of 46.3% B2B firms and 53.7% firms operating on both B2B and B2C markets. 25.4% of sample firms are product-oriented firms, 45.6% represent services firms; 29% produce both goods and services. The respondents belonged to the firms with Russian capital (74.3%), foreign capital (11%) and joint capital (14.7%).



Empirical results Descriptive statistics

Appendix 3 presents the means, standard deviations, and reliability indicators. The overall scale reliability is high (Cronbach's Alpha = 0.918). Most of the indicators related to CO have high average means.

The overall conclusion based on the analysis of descriptive statistics is that the sample firms pay little attention to the measurement of customer satisfaction and their commitment to finding out the latent needs of customers. These results confirm the assumption of the declared CO of Russian firms [Popov, Tretyak, 2014]. In the firms' responses there are only external signs of CO. The respondents noted that their firms have customer satisfaction as objectives, but there is no component of cohesive approach, in other words, there is no evidence of well-established CO practices in these firms.

Factor analysis results To identify the main latent factors that reflect CO we applied exploratory factor analysis (EFA) with varimax rotation for the initial pool of 24 items using SPSS software. Three items (K16, K18, K22) had factor loadings lower than 0.5 and were excluded from further analysis. Three further items (K4, K5, K24) demonstrated substantial cross-loadings and were also eliminated. Table 3 presents the results of EFA for the remaining 18 items (a = 0.898), whereas the four-factor solution explains 60.4% of variance.

The main goal of EFA was to identify a potential structure of the combined scales [Narver, Slater, 1990; Deshpande, Farley, Webster, 1993; Narver, Slater, 2004]. The results demonstrate that indicator allocation does not fully match the latent factors of the original scales of Narver and Slater [Narver, Slater, 1990, 2004], and Deshpande, Farley, and Webster [Deshpande, Farley, Webster, 1993]. Instead, all indicators were divided into 4-factors: proactive CO: grouped the items corresponding to the the original scale for proactive CO by [Narver, Slater, MacLachlan, 2004];



Table 3. Rotated component matrix (18 items)

Indicator	Indicator label	Factor
		1	2	3	4
		Proactive CO	Customer interest and satisfaction importance	value for customer	orientation both for customers and competitors
K11	We innovate even at the risk of making our own products obsolete	0.779
K8	We continuously try to discover additional needs of our customers of which they are unaware	0.718
K14	We extrapolate key trends to gain insight into what users in the current market will need in the future	0.710
K12	We search for opportunities in areas where customers have a difficult time expressing their needs	0.701
K13	We work closely with lead users who try to recognize customer needs months or even years before the majority of the market may recognize them	0.666
K9	We incorporate solutions to unarticulated customer needs in our new products and services	0.621
K10	We brainstorm on how customers use our products and services	0.608
K7	We help our customers anticipate developments in their markets	0.538
K19	Data on customer satisfaction are disseminated at all levels of this business unit on a regular basis		0.781
K15	We constantly monitor our level of commitment and orientation to serving customer needs		0.721
K6	We measure customer satisfaction		0.673
K23	The customer's interest should always come first, ahead of the owners'		0.615
K17	We are more customer focused than our competitors		0.526	0.403
K2	We create customer value			0.834
K1	We are committed to customer			0.823
K3	We understand customer			0.580
K20	We know our competitors well				0.830
K21	We have a good sense of how our customers value our products and services		0.443		0.589

(1) customer interest and satisfaction importance: this latent factor grouped the items from the original MKTOR scale [Narver, Slater, 1990], 9-item CO scale by [Desh- pande, Farley, Webster, 1993] and the reactive CO scale by [Narver, Slater, 1990; MacLachlan, 2004];

(2) value for customer: these items, to a large extent, corresponded to the items from the original MKTOR scale [Narver, Slater, 1990];

1992] customer & competitor orientation: these items correspond to one part of the 9-item CO scale by [Deshpande, Farley, Webster.

Cluster analysis results Based on the revealed factorial structure of CO construct an additional cluster analysis was conducted. It resulted in the identification of five clusters with different focuses on CO elements (Table 4).

Table 4. Clusters description

Cluster No.	Cluster name	Number of respondents	Main features
I	“Truly customer-oriented”	83 (31%)	High values of most of all CO indicators
II	“Declarers”	57 (21%)	Low values of proactive CO indicators; low values of indicators based on customer satisfaction and loyalty
III	“Low customer-oriented”	31 (11%)	Low values of all CO indicators
IV	“Strivers”	72 (26%)	Average values on all indicators of Priority to customer interest factor; average values on learning about customers and their satisfaction
V	“CO newcomers”	29 (11%)	High values of customer commitment; low values of indicators related to innovations, customer monitoring

The cluster analysis was conducted in two stages: at the first stage, a hierarchical clustering was carried out, at the second stage -- non-hierarchical clustering. Since it is difficult to determine the exact number of clusters in a given sample, non-hierarchical clustering was performed by K-means method for the number of clusters in the range of three to six. Further analysis indicated that the optimal results could be achieved with five clusters. Table 4 presents the final cluster solution and clusters' characteristics.

The results of the cluster analysis provide a deeper perspective on how Russian B2B firms understand, implement and adjust CO in practice. 68% of firms try to implement CO in a reduced form, whereas diverse angles of the concept are emphasized (clusters I, IV and V). However, a holistic implementation of all CO dimensions is undertaken only by “truly customer-oriented” firms (cluster I).

Cluster I (“Truly customer-oriented firms”, 31%) is characterized by the highest levels of all the CO indicators (4-5 from 5). This is the largest cluster (83 respondents) that also contains most firms with foreign capital, which might explain the high level of CO. Foreign firms have successfully transferred CO philosophy and practices from developed markets to the Russian market. Moreover, the Cluster I firms are geographically located in large federal cities, and their offering includes both B2B and B2C services. The high level of competition in federal cities can explain the importance of CO for the firms in this cluster. The size of the cluster firms varies with nearly half of the cluster firms representing SMEs with less than 100 employees.

Cluster II (“Declarers”, 21% of sample firms) includes firms with a so-called “declared” CO [Popov, Tretyak, 2014]. A “declared” CO implies the firm accepts most important client values and customer interests, however does not demonstrate any supporting consistent behaviour and organizational processes. Hence, the indicators on proactive CO, evaluating customer satisfaction and loyalty in this cluster firms have very low values. Surprisingly, the cluster is mostly represented by the B2B services firms. During the in-depth interviews some firms explained CO through the notion of quality. It represents a rather faulty understanding of CO concept, which may drive overall offering focus that is not supported by a deeper exploration of customer needs or following up after the service is provided: “CO is perceived as one of the main components of the high [offering] quality”.

Firm A, electronic producer “...For our firm CO is first of all the speed and quality of our services”.

Firm B, leading travel company

Cluster III (“Low customer-oriented”, 11%) consists of firms, where CO is very low. These are mostly B2B services firms from federal cities. All elements of CO assessed by these firms are below the average. These firms are oriented towards existing products and services and aim to protect their market niche. For the same purpose, they monitor the level of customer satisfaction to ensure customer loyalty. There is rather low attention to proactive CO, innovations, product and customer need development.

Cluster IV (“Strivers”, 26%) consists of firms developing a customer-oriented approach and trying to achieve competitiveness through it. Representatives of this cluster currently implement just some aspects of CO, but aim to develop them further for a competitive advantage. They are focused on discovering latent customer needs aiming to increase customer satisfaction and monitoring the CO level. Most of the cluster is represented by the firms based in federal cities, offering mainly services in both B2C and B2B markets.

Finally, cluster V (“CO newcomers”, 11%) includes mostly firms with high customer commitment, but currently lacking a CO. They evaluate their level of CO as low on the core indicators, but provide high-level scores on indicators of value for the customer (e. g. “the customer's interest should always come first, ahead of the owners”). The main characteristic of this cluster is the domination of pure B2B firms, operating mainly in the B2B services area and located in regions. The regional location of the firms and their limited market experience (less than 5 years) might be an essential factor in their lack of customer focus. Lower competition in the regions might also be a factor that leads to a deviation from the CO focus in favour of other strategic orientations.

Table 5 provides an overview of the clusters with focus on the main firm characteristics: region, age, capital affiliation, market, market offer and firm size.



Discussion and conclusion

Theoretical implications The study's aim was to explore the nature and specifics of CO perception and application by B2B firms. Additionally, it focused on the Russian economy as the emerging market context. The firm-level data on a set of well-established CO measures was analysed using a sequential methodological approach. The analysis involved exploring the latent factorial structure through EFA, interpretation of the resulted latent factors and identification of the firms clusters that reflected various degrees of prioritization of the CO and its subdimensions.

The results of EFA indicated the discrepancies in firms' perception of CO concept subdimensions, based on preselected three core scales. As an outcome, four distinctive factors were identified, which did not match the pre-selected original measurement scales [Narver, Slater, 1990; Deshpande, Farley,

Webster, 1993; Narver, Slater, MacLachlan, 2004]. The identified subdimensions help to understand the ways of how firms reflect the CO concept, prioritizing its different angles -- e. g. focus on measuring customer satisfaction or being inconsistently applying corresponding values (thus, only “declaring” CO).

Table 5. Cluster descriptions, %

	Cluster
	I	II	III	IV	V
Region
Federal cities	74.7	68.4	64.5	70.8	62.1
Other regions	25.3	31.6	35.5	29.2	37.9
Firm age
Less than 2 year	8.4	1.8	12.9	5.6	17.2
3-5 years	14.5	17.5	16.1	6.9	37.9
6-10 years	20.5	17.5	22.6	18.1	10.3
11-30 years	32.5	42.1	41.9	51.4	31.0
More than 30 years	24.1	21.1	6.5	18.1	3.4
Capital affiliation
Russian	63.9	77.2	83.9	73.6	89.7
Joint	20.5	15.8	9.7	12.5	6.9
Foreign	15.7	7.0	6.5	13.9	3.4
Market
В2В	36.1	56.1	51.6	44.4	55.2
Both B2B and B2C	63.9	43.9	48.4	55.6	44.8
Market offer
Goods	18.1	26.3	35.5	33.3	13.8
Services	49.4	38.6	41.9	44.4	55.2
Both goods and services	32.5	35.1	22.6	22.2	31.0
Firm size (number of employees)
Less than 100	47.0	61.4	51.6	38.9	72.4
101-500	15.7	22.8	19.4	27.8	17.2
501-1000	13.3	3.5	12.9	13.9	--
More than 1000	24.1	12.3	16.1	19.4	10.3

Note: firms with Russian capital dominates in all clusters since the number of firms with Russian capital in the total sample exceed by several times firms with foreign and joint capital. Therefore, capital affiliation was not used in cluster descriptions, but nearly half of the firms (13 from 30 in the whole sample) with foreign capital are in cluster I.

The overall findings from in-depth interviews demonstrate that respondents increasingly develop an understanding of the need for CO by their firms:

“The stable competitive advantages of the firm can be created thanks to constant CO”.

Firm C, consulting

“Non-price factors of competition are beginning to play an increasing role, the firm which is ready to offer more value has an advantage”.

Firm D, advertising agency

However, quantitative analyses have revealed substantial differences in firms' attitudes reagrding implementation of the CO concept. The identified differences demonstrated the presence of “truly customer- oriented” firms as opposed to firm with “declared” CO. This result matches earlier findings (e. g. [Roersen, Kraaijenbrink, Groen, 2013]). The challenge for the customer side is that it might be substantially difficult, if not impossible, for the customer firms to realize the difference between a “true” (i. e. consistent, committed), and a “declared” (i. e. acknowledged, but failing support through regular practices and follow-up measures) CO. This information asymmetry is causing additional uncertainty for customer choice and shifts the burden of risks to the customer side.

A strong support was found for the existence of proactive CO, which completely reflected its nature. This angle is perceived as a highly distinctive one, and can be a solid signal to the market about the commitment and consistency of CO implementation, helping differentiate between “truly customer-oriented” firms and firms only “declaring” these values. Other signals were found to be the significance of value creation (factor 3) and relationships with customers (factor 2). These angles might be further explored and integrated in CO measurement in the context of B2B markets.

The findings of the study provide for some comparison opportunities with the existing studies on CO in Russia. The focus on the “declared CO” was suggested in previous empirical and conceptual studies (e. g. [Ro- ersen, Kraaijenbrink, Groen, 2013; Popov, Tretyak, 2014]) and confirmed by the results of our analysis. Similarly, the importance of competitor orientation as an alternative strategic focus was earlier raised in the study by [Smirnova et al., 2011], and is reflected in one of the factors identified in the current study as “orientation both for customers and competitors”. The latter aspect may also help to investigate the relationship between the customer and competitors orientations as the core dimensions of MO in existing studies in developed markets (see Appendix 1). Lack of studies that consider the firm clusters does not provide for a direct comparison of the findings, however offer an agenda for further research. Further studies may potentially disintegrate well established existing concepts and measurement approaches into the dimensions that may capture identified latent angles of CO. Existing studies on developed markets tend to consider CO as a drivers within the value chain, which also involve interfirm relationship in the B2B context. The revealed clustering of firms contributes to existing literature by suggesting the broader prospects for collaborative value creation. Our research helps to better understand the latent components of CO concept, as well as the types of the partners within the value chain that prioritize its different components.

We might conclude that current study initiates a discussion on revisiting well-established marketing concepts and their measurement approaches in B2B markets on example of CO in Russia. The results raise a question about the potential adaptation of existing scales in B2B market research and the further development of these scales with the specific focus on the value for customers and the customer relationships.

Practical implications CO of B2B firms is examined using the example of the Russian emerging economy, which is undergoing various stages of transformation from a centrally-planned to a market economy. This market transformation involves substantial changes in managers' perceptions of core managerial concepts, including MO and CO. The results of the study demonstrate the differences in understanding CO by researchers and marketers, which may cause different results from applying existing well-established measurement tools. Acknowledging these differences might be important in developing these measures in order to provide better diagnosing potential for the firms.

Our study shows that firms from Cluster II often demonstrate a so called “declared” CO and a superficial understanding of its core dimensions, when implementing the CO concept, they may not acknowledge their weaknesses and concerns about their processes and behavior [Roersen, Kraaijenbrink, Groen, 2013; Smirnova, Rebiazina, Frosen, 2018]. For example, the absence of a process for evaluating CO and customers satisfaction is possible: “If customers pay for services, they are satisfied with our work”.

Firm E, financial services

“We have no special KPIs for CO evaluation. If a customer is satisfied, we know it”.

Firm F, consulting

The received cluster structure can help developing a practical tool for both CO development and management by B2B firms. The clusters demonstrate the prioritized strong aspects of CO and possible development opportunities we may use as a basis for managerial recommendations. For example, “truly customer-oriented firms” firms from cluster 1 might pay attention to ensuring CO on each business level for a more aligned strategy implementation. For “declarers” (cluster II) the priority might be to turn their CO vision into real procedures and matching KPIs. In case of “low customer-oriented” firms (cluster III) the priority would be to identify the reasons for the low CO, as well as to understand the potential to improve required practices and values. The “strivers” (cluster IV) may aim for a more aligned approach to CO by leveraging the angles that are currently below the average. Finally, “CO newcomers” (cluster V) may struggle to systematically collect customer data and need to identify potential drivers to initiate CO-related activities.

Research limitations

Research limitations are common for the quantitative method. First, the sample of 272 firms cannot be representative for the general population of Russian B2B firms. Second, cluster analysis results show different approaches to CO implementation, but do not provide an in-depth explanation of the cluster specifics. To overcome this limitation, a small-scale qualitative research in the form of in-depth interviews was applied to investigate the specifics of CO of Russian B2B firms in detail. Further research on the Russian market should study all clusters in detail using qualitative methods, for example, multiple case study involving firms from each cluster.

Directions for future research Additional research beyond the provided exploratory study is needed to quantitatively verify the conclusions and generalize the results. Further research is required to support the assumptions, generated by our data analysis. Further studies should focus on the structure and different dimensions of CO with the aim to develop an integrated CO scale that addresses specific issues of the transition economies such as Russia. Another potential research direction would be to conduct a similar study in another market context.

The following questions might be suggested for future research: Are there any differences in how B2B firms from emerging/ transition markets understand the core marketing constructs? How do factors such as capital structure, size and the location of the B2B firm (e. g. rural vs. urban location), their experience and expertise matter for defining and implementing CO? How do the B2B firms interpret the value and behavioural/process side of CO? In particular, by claiming customer values do such firms imply that the right mindset already represents the required actions?

Appendix 1

...

		Definition used (MO/CuO)	adaptation of definition to B2B context	adaptation of scale to B2B context	methodology
Article	mo/ Co				origin of scale for mo/co	Level of mo/ Co	sample (B2B/B2B + B2C)	Context- specific settings	Method(s) of analysis
1	2	3	4	5	6	7	8	9	10
[Bala-	CuO,	[Narver,	No	Yes	[Narver, Slater,	Firm	B2B,139	Machine	Exploratory fac-
krish-	MO	Slater,			1990; Saxe,	level		tool in-	tor analysis.
nan,		1990]			Weitz, 1982]			dustry	Regression
1996]									analysis. ANOVA
[Bigne	MO	--	No	Yes	[Narver, Slater,	Inter-	B2B,179	Ceramic	Confirmatory
et al.,					1990; Kohli,	firm	dyads	tile sec-	factor analysis.
2004]					Jarworski, Kumar, 1993; Deshpande, Farley, Webster, 1993]	level

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