Dipl.-Stat. Christan Hoops, IPSOS Observer, This email address is being protected from spambots. You need JavaScript enabled to view it..
Michael Bücker, Ph.D., Technical University of Dortmund, 44221 Dortmund, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it..


Interacton orientaton reflects the ability of a company to interact with the individual customer and to gather informaton from successful interactons. Four dimensions of interacton orientaton are identfed in the literature: customer concept, interacton response capacity, customer empowerment and customer value management (Ramani and Kumar, 2008). This study shows that indeed a ffh dimension of interacton orientaton exists and investgates the determinants, moderators and consequences of this construct. The frst notable fnding is that B2B companies exhibit a greater degree of interacton orientaton than B2C frms. Ramani and Kumar hypothesized that in their study. We show that there are B2C industries such as fnancial services, whose companies also have a greater interacton orientaton. This could be the reason why the authors could not prove their hypothesis. Furthermore, we examine the influence of strategic orientatons on organizatonal performances and compare various orientatons with each other.


In recent years, many studies have atempted to fnd new ways to positvely influence various strategic orientatons since the organizatonal culture plays an important role in achieving the company’s goals (Baker and Sinkula, 1999b; Farrell, 2000; Hult, Hurley and Knight, 2004). Interacton orientaton, for example, can help companies to extend their knowledge about the customer’s needs and preferences (Ramani and Kumar, 2008). For companies with a higher level of organizatonal learning, it is easier to achieve these goals because of greater abilites and more effectve ways (see Buckler, 2003, p. 121).

The majority of the existng literature identfes market, entrepreneurial and learning orientaton as three major constructs which directly impact organizatonal performance. However, only a few studies have investgated the antecedents, moderators and consequences of an interacton orientaton. This study atempts to fll this gap and to develop an empirical analysis based on current literature. Furthermore, we focus on fnding differences between industries and draw conclusions about the importance of several groups of determinants. Finally, we will examine whether any synergetc effects exist between interacton and market orientaton.

Interacton orientaton

According to Ramani and Kumar (2008), interacton orientaton reflects the ability of a company to interact with the individual customer and to gather informaton out from successful interactons in order to create a proftable relatonship with the customer. Based on statements by 48 managers the authors conceptualize interacton orientaton as a second-order construct consistng of four dimensions: customer concept, interacton response capacity, customer empowerment and customer value management.

The customer concept is conceptualized as the company’s belief to an ideal customer treatment. This includes customized services and products as well as individual analyses of the needs and marketng actons The customer image, which is benefcial to interacton orientaton, sees the individual customer level as the examinaton unit and startng point of company’s actvites (cf. Kumar and Reinartz, 2006).

Interacton response capacity illustrates the degree of successful transactons or relatonships that are due to the customer behavior in the past, both for one relevant demander and for the entre group of customers. Knowledge about as well as feedback from a certain customer is stored by companies with higher interacton orientaton so that the company could draw on this knowledge in the future.

Thus, the interacton response capacity reflects the requirement of an organizaton to serve the heterogeneous customers individually (cf. Ramani and Kumar, 2008). Krohmer (1999, p. 176) fnds out that the responsiveness to market informaton plays a signifcant role in the performance-related variables of efciency, effectveness and adaptability. So it can be assumed that the interacton response capacity impacts these variables and other performance indicators, too.

Though a company is not able to provoke an interacton directly, it can be imagined that the company takes the frst step. Thus, the customer empowerment as a construct of interacton orientaton reflects the extent to which the company enables its customers to contact the organizaton in order to influence the business and cooperaton. This implies that the interacton is subject to an acton-reacton-cycle, thus demonstratng the need for individual actvity in the theory of multple perspectves (see Pantaleo and Wicklund, 2000).

In contrast to the other sub-constructs, customer value management does not take the extent of interacton into account, but implies the quality of the interacton partners. Homans’ theory assumes that interactons are not only of beneft to at least one of the partcipants but also create costs (cf. Homans, 1951). Effectve customer value management can help an organizaton to evaluate certain interactons or whole relatonships in order to take this informaton into account in relaton with later marketng actvites. Since it reflects as specifc customer level, this construct becomes relevant for interacton orientaton (cf. Ramani and Kumar, 2008, p. 29).

Danzinger focuses on the industrial goods market, and the reflectve second-order construct by Ramani and Kumar serves as a basis. Secondorder means that the latent variable interacton orientaton is measured by different sub-constructs which are in contrast to formatve models posited as the common cause of item behavior. However, exploratory depth interviews concluded that there is no evidence of the dimension of the belief in the customer concept for this market. Instead, the interviews identfy a new sub-construct perceived as perspectve taking and conceptualized as the understanding of the customer’s problems. The other dimensions of interacton response capacity, customer empowerment and customer value management are confrmed by the interview data (Danzinger, 2010).

Ramani and Kumar identfy different determinants of interacton orientaton. Thus, they could not disprove the hypothesis that the lower the dependence on trademarks, the greater the frm’s interacton orientaton. This could be explained by the fact that the greater the dependence on patents and trademarks, the less the frm has to fulfll the customer’s needs since the patents serve as a protecton against any compettors. Furthermore, Ramani and Kumar (2008, p. 30) show that the normatve insttutonal pressure, the employee reward system and the outsourcing expertse correlate positvely with the organizatonal interacton orientaton.

Instead of being satsfed with a subset of opportunites to make relevant offers to customers, it is beter for a company to atract or retain customers through a variety of offers (Newell, 2003). Outsourcing increases the ability to provide the demander with a wide range of products and services (King, 2004). One can also assume that a superior control of the back-end supply systems increases the interacton response capability (Ramani and Kumar, 2008).

In additon to that, the determinant of the reward system can be linked to the phenomenon of interacton orientaton by the sub-construct of customer value management. If informaton about the individual employee performance exists (i.e. there is a reward system), it is obvious that the company is also able to identfy each customer’s proporton in the total amount of sales and achievements (meaning it has a corresponding customer value management).

The last examined determinant that correlates positvely with the construct of interacton orientaton is the normatve insttutonal pressure. Kumar and Ramani acknowledge the positve relatonship (to the level of α = 0.05) and thus the assumpton that the pressure exerted by compettors measured by the adopton of interactve technologies requires a greater interacton orientaton of the company. At a signifcance level of 1%, this effect is not signifcantly different from zero.

Lastly, the authors atempt to identfy signifcant differences in the orientaton interacton between B2B (business-to-business) and B2C (businessto-consumer) companies. However, the hypothesis that B2B companies have a higher degree of interacton orientaton than B2C companies had to be clearly rejected (see p-value of 0.46; Ramani and Kumar, 2008). In additon to the antecedents tested by Ramani and Kumar, Danzinger (2010) has identfed learning orientaton as a determinant of interacton orientaton in his work as well.

Regarding the consequences of interacton orientaton, Ramani and Kumar frstly distnguish between the aggregated “Customer-Based Relatonal Performance” (measured for example by customer satsfacton or incurred arising from word-of-mouth) and the aggregated total performance indicator “Customer-Based Proft Performance” (measured by customer loyalty or proftability of demanders). Thereby, interacton orientaton has a signifcant positve effect on both aggregatons. Danzinger, however, examines the relatonship performance, the overall economic performance and the new product success as consequences of interacton orientaton. With the excepton of the later feature, interacton orientaton exercises a signifcant influence on both performance constructs (see Danzinger, 2010, p. 343).

On the one hand, Ramani and Kumar have also tested the competton intensity, which has no signifcant moderatng effect in the relatonship between interacton orientaton and customer-based relatonal performance. On the other hand, they have revealed that the customer initated contacts moderate the positve effect of a frm’s interacton orientaton on its customer-based relatonal performance. These contacts are measured by the percentage of customers who have communicated with the company that year. According to the authors, if the organizaton has communicated with many customers, interacton orientaton has a greater impact on the aggregated consequences (cf. Ramani and Kumar, 2008, p. 38). Acknowledging these results, Danzinger confrms the non-signifcant moderatng effect of competton intensity. He also fnds a positve effect of frm size, which moderates the relatonship between relatonship performance and interacton or learning orientaton. The degree of soluton orientaton has a non-signifcant moderatng effect between one strategic orientaton and one performance indicator (see Danzinger, 2010, p. 344).

learning orientaton

In literature on organizatonal learning, the theoretcal consideratons are more prevalent than empirical results (cf. Schwaab and Scholz, 2000, p. 354). There are several defnitons of learning orientaton. For instance, Agryris and Schön (1999, p. 19) defne a learning organizaton as a company that assimilates informaton (e. g. knowledge, techniques or experiences) in any form. Organizatonal learning is equated with the identfcaton and correcton of errors.

The authors distnguish between three types of learning: Single-loop-, double-loop- and deutero-learning. Single-loop-learning occurs when errors are detected and corrected but the frm carries on with its present policies and goals. Double-loop-learning means that, in additon to singleloop, fundamental issues are questoned and reviewed. However, deuterolearning occurs when organizatons “learn to learn”. This is very important since the reflectng on the context and the identfcaton of learning barriers and reliefs consttutes an important functon (see Argyris and Schön, 1978, p. 26 et seq.).

Furthermore, a distncton must be made between individual and organizatonal learning. However, theories-in-use exist between the aggregated and individual learning orientaton, which can act as a link between these. If the percepton of the individual changes, organizatonal learning can take place. This is successful if the theories are adapted and applied by other persons of the organizaton. In order to achieve a high level of learning orientaton, the creaton and applicaton of new theories must become normal since learning should not be seen as a closed process but as a contnuous sequence of behavior (Argyris and Schön, 1978, p. 17 et seq.).

In literature there are different conceptualizatons of organizatonal learning. Sinkula, Baker and Noordewier (1997) measure learning orientaton as a second-order construct consistng of three dimensions: commitment to learning, shared vision and open-mindedness. Calantone, Cavusgil and Zhao (2002) argue that the construct should be complemented by intraorganizatonal knowledge sharing. However, Perez Lopez, Montes Peon and Vazquez Ordas (2005) use a conceptualizaton which is heavily based on knowledge generaton (see sub-constructs such as acquisiton of knowledge, knowledge distributon, organizatonal memory or knowledge interpretaton. Danzinger (2010) combines both approaches and develops the new subconstruct of human resource practces.

Empirical research has identfed a great number of determinants of learning orientaton, which can be categorized as internal and external antecedents. Company-internal determinants include the organizatonal structure (cf. Farrell, 1999; Slater and Narver, 1995), the organizatonal culture (Peng, 2008; Zheng and Cui, 2007; Lee and Tsai, 2005; Grinstein, 2008; Jimenez-Jimenez and Cegarra-Navaroo, 2007) and the organizatonal strategy (Perez Lopez et al., 2005; Farrell, 2000) while external antecedents consist of the environment where the company operates (Slater and Narver, 1995; Farrell, 1999).

Alternatve strategic orientatons

Besides interacton and learning orientaton, there are a number of other orientatons in literature. Most of them can be summarized under the generic term of “strategic orientaton“. Neal, West and Paterson (2004) defne strategic orientaton as the structures, strategies and processes which a company adopts to be able to compete with other organizatons in the market. However, all defnitons see the strategic orientaton as the basis for the frm’s strategy.

There are different strategic orientatons, but most of the publicatons only deal with market orientaton which specifes the orientaton of the business actvites on the market. It means the implementaton of the marketng concept (see Kohli and Jaworski, 1990) and became the cornerstone of modern marketng ideas (Kirca, Jayachandran and Bearden, 2005). Companies with a high level of market orientaton focus all of their actvites on the customers’ needs and requirements (cf. Utzig, 1997). In literature, two perspectves of market orientaton have become established. Firstly, the conceptualizaton by Narver and Slater (1990) from a corporate culture point of view. Secondly, the defniton by Kohli and Jaworski (1990) based on a behavioral view. A large number of variables (for an extract relevant to our model see Table 1) are deemed to be determinants or control variables of interacton orientaton, learning orientaton or market orientaton.

Table 1. Appearance of the investgated variables in literature
ConstructAppearance in the literature of
Interacton OrientatonLearning OrientatonMarket Orientaton
Company Characteristcs
Distributon     X
Industry   X X
Number of Employees   X X
Sales Previous Year     X
Type of Operaton X   X
Employee Characteristcs
Age   X X
Gender   X X
Tenure   X X
Employee Perceptons
Affectve Commitment   X X
Contnuance Commitment   X X
Employee Satsfacton   X X
Compettve Intensity X X X
Market Turbulence   X X
Normatve Insttutonal Pressure X   X
Technological Turbulence   X X
Organizatonal Culture
Dependence on Trademarks X    
Learning Orientaton X   X
Willingness to Cannibalize     X
Organizatonal Strategy
Adaptve Selling   X X
Employee Reward System X    
Outsourcing Expertse X    
Organizatonal Structures
Formalizaton   X X
Interdepartmental Conflicts     X
Interdepartmental Connectedness     X
sources: Chandy and Tellis (1998), Deng and Dart (1994), Dharmadasa (2009), Duff, Boyle, Dunleavy and Ferguson (2004), Farrell and Oczkowski (2002), Farrell (1999), Grinstein (2008), Homburg (2004), Jaworski and Kohli (1993), Kirca et al. (2005), Krohmer (1999), McGuinness and Morgan (2006), Mengüc (1996), Park and Holloway (2003), Ramani and Kumar (2008), Scholderer (2000), Selnes, Jaworski and Kohli (1996), Severiens and ten Dam (1998), Siguaw, Brown and Widing (1994), Siguaw and Honeycut (1995), Steiners (2005) and Verhoef and Leeflang (2009).

The term “entrepreneurial orientaton” describes management attudes and forms of behavior which are directed towards an innovatve business orientaton and the pursuit of new company actvites. The idea goes back to studies by Miller and Friesen (1978), who have identfed eleven dimensions. In additon, they conclude that innovatveness, risk-taking and proactveness are the central dimensions (Miller, 1983). Each of these sub-constructs can individually exert a positve influence on the company’s goals such as adaptability or product innovatons. In this study we focus on entrepreneurial proactveness, which consists in the actve pursuit of promising business optons and the associated creaton of compettve edges (cf. Lumpkin and Dess, 1996).

The customer orientaton of salespeople is explained by, for instance, the “customer-oriented selling” (see Saxe and Weitz, 1982) or the “adaptve selling” (Speiro and Weitz, 1990) behavior of salespeople. Adaptve selling is the salesperson’s ability to recognize promising atributes of specifc selling interactons and adapt their behavior to these (see. Weitz, Sujan and Sujan, 1986, p. 174). This adaptaton can take place during the interacton with one customer as well as between the interactons with two different customers. In contrast, customer-oriented selling is defned as “the degree to which salespeople practce the marketng concept to try to help their customers make purchase decisions that will satsfy customer needs” (Saxe and Weitz, 1982, p. 344). Despite the conceptual differences the contents of both constructs are very similar. Table 2 compares these constructs as well as shows differences regarding the contents of these organizatonal strategies and structures.

Table 2. Overview of the various constructs including differentaton
ConstructFocus on customerFocus on organisatonIndividualityRelaton to the customerComponents
Adaptve Selling X   X with the client   X    
Customer-oriented Selling X   X with the client   X X X
Entrepreneurial Orientaton*   X   for the client X X X  
Interacton Orientaton (IO) X   X with the client   X X  
Learning Orientaton (LO)   X   for the client   X    
Market Orientaton (MO)** X X X for the client X   X  
* Dimension adopted by Covin and Slevin (1989).
** Defniton and conceptualizaton specifed in Kohli and Jaworski (1993).

It can be seen that interacton orientaton is the only construct with an individuality focus on the customer which contains a relatonship with the customer and monetary as well as product-related components.

Research propositons

Business-to-business frms organize themselves into account management teams and b2c providers have relatons with many similar customers. Ramani and Kumar (2008) hypothesize that b2b frms exhibit a greater degree of interacton orientaton than business-to-consumer frms due to a greater acceptance and diffusion of the belief in the customer concept. Organizatons in the b2b sector rather believe that it is not possible to satsfy each customer with the same products or services and aim to acquire new customers individually rather than business-to-consumer frms. Thus:

H1: Business-to-business frms have a higher interacton orientaton than business-to-consumer frms.

Normatve pressure derives from the ability to learn from organizatons which adopted an innovaton through direct or indirect channels. If two frms communicate with each other frequently and directly, the probability of an adaptng behavior increases.

Experts make a distncton between stakeholder pressures and compettve pressures. Stakeholder pressures on a frm are exerted by its customers, investors, media, partners or similar shape. Some theorists argue that an organizaton meets its customers’ expectatons and requirements because conformity gives it access to the resources it needs to be successful (Di Maggio and Powell, 1991).

Compettve pressures are forces on the frm to adopt a technology or to run the risk of losing compettve edges because of too litle customer loyalty and high costs (Abrahamson and Rosenkopf, 1993). Researchers do not agree on whether frms adopt technologies because of insttutonal pressures from their environments.

Normatve insttutonal pressure relates to the behavior of responding to numerous expectatons (Karahanna, Straub and Chervany, 1999). The number of compettve frms that adopt new interactve technologies precipitate the frm’s adopton of interactve tools (Wu, Mahajan and Balasubramanian, 2003). Hence,

H2: The greater the normatve insttutonal pressure for a frm, the greater its interacton orientaton is.

As, with growing compettve intensity, earnings opportunites of a business unit sink, a frm must encourage customers even more strongly to share opinions of its products with the frm than in a situaton with low compettve intensity. In additon, the organizaton will try harder to understand the customers’ problems to contnue to be successful. So the greater the compettve intensity a frm faces, the greater a frm’s customer empowerment and understanding of customer problems would be. Therefore,

H3: The greater the compettve intensity, the greater a frm’s interacton orientaton would be.

Market turbulence will basically be determined by the fact that the customers’ preferences change in the course of tme. If they change rapidly, a frm is forced to analyze previous consumer transactons to antcipate future needs and potentals at an early stage, i.e. greater market turbulence results in superior interacton response capacity, the frm’s ability to use dynamic database systems and processes. Thus:

H4: The greater the market turbulence, the greater a frm’s interacton orientaton would be.

There is empirical evidence that the willingness to cannibalize has a positve effect on the number and success of innovatons (Chandy and Tellis, 1998). Companies which can easily adapt to requirements that new products involve motvate customers more to express own ideas for new and further developments. Accordingly:

H5: The greater the frm’s willingness to cannibalize, the greater its interacton orientaton is.

The value creaton process frstly is about the acquisiton of user knowledge. To achieve this purpose, the company exchanges informaton with the customer as the carrier of that informaton. This exchange is an interacton cycle between provider and customer. In additon to the acquisiton of knowledge it also is about the adopton of user knowledge (Zahra and George, 2002). During this phase the company tries to anchor the informaton and make use of it. This change can be seen as an organizatonal learning process so that this phase can be described as learning orientaton. Thus, one could assume that learning orientaton requires interacton orientaton. However, Arrow’s informaton paradox claims that the value of informaton (in this case user knowledge) is not known untl one already knows the informaton. But then the informaton does not have to be acquired anymore (Arrow, 1962).

Suggestng that there is a causal link between the two orientatons, it would follow that interactons can only reach their longer-term effect if the companies had a strong organizatonal learning. So learning orientaton would be understood as a preconditon of interacton orientaton. As far as the relatonship between the two strategic orientatons is empirically verifable, its directon should, based on these consideratons, be from learning orientaton towards interacton orientaton. Thus:

H6: The greater the learning orientaton of an organizaton, the greater its interacton orientaton is.

If the employees at the company are older, i.e. they have gained more experience in their profession, they probably have a higher competence. Consequently, they can offer the company advanced knowledge about the frm’s idea of what each individual customer has contributed to its profts and provide beter predictons (i.e. they will allow for a beter customer relatonship management). Accordingly:

H7: The older the employees are, the greater the frm’s interacton orientaton.

Companies such as huge banks forming part of the fnancial industry can match each transacton (e.g. money transfer or debit entry) with a single customer because of individual account management. Equally the employees must have the opportunity to get access to customer informaton at any tme so that they can give individual advice to the customer independently.

Furthermore, there are a lot of opportunites for consumers to interact with the bank, e.g. by appropriate applicatons for payment transactons in smart- or i-phones. Though customers in the fnancial industry are individual rather than organizatonal customers (that means these companies are primarily B2C focused), the extent of higher interacton response capacity allows for the following thesis:

H8: Financial frms exhibit a greater degree of interacton orientaton than companies in other industries.

Firms with a high level of interacton orientaton encourage customers to partcipate in designing products and services (Ramani and Kumar, 2008). Ideas for innovatons can be generated from this interacton process and it is known that innovatons arise in interfaces between customers and organizatons (Pirinen and Fränt, 2008). Hence,

H9: The greater the frm’s interacton orientaton, the more product innovatons are generated by the frm.

The construct of entering new markets describes the start of a new business within an existng organizaton such as the establishment of a new business unit. If the frm encourages customers to partcipate interactvely in designing new products, which means that the frm has a high level of interacton orientaton, the company will be able to offer signifcantly more products or services to pursue new business. Thus:

H10: The greater the frm’s interacton orientaton, the more the frm is engaged in entering new markets.

The frm’s adaptability refers to the ability of the company to adapt to any environmental changes (see Rueckert, Walker and Roering, 1985). For example, this ability implies the adapton of the products to the changing needs of customers and quick reacton to new threats in the market (Irving, 1995). The implementaton of these measures implies a high level of interacton orientaton, e. g. by an understanding of the customers’ problems or by customer empowerment to collaborate in new or further product developments. This argumentaton leads us to the below hypothesis:

H11: The greater the interacton orientaton of a frm, the greater the frm’s adaptability is.

The frm’s effectveness can be operatonalized by parameters such as achieving the degree of customer satsfacton, reaching the target market share or acquiring new customers (Irving, 1995; Rueckert et al., 1985). A higher degree of interacton response capacity and customer empowerment results in a higher level of customer satsfacton (Ramani and Kumar, 2008, p. 29). Through the customer empowerment, which lets the customer take part in the ongoing development of products, the company can respond to the customers’ needs in a beter way, which creates compettve edges (see Kohli and Jaworski, 1990). These consideratons justfy the following hypothesis:

H12: The greater the interacton orientaton of a frm, the greater the frm’s effectveness is.

Customer-specifc success refers to parameters like customer retenton, achieving authentcity or minimizing customer complaints. We can say that the aim of interacton orientaton is towards the understanding of the customer’s problem. The arrangement of interacton is represented by the behavior of customer contact staff, where customer satsfacton and trustng customer relatonships are primary goals. A high degree of interacton orientaton includes a great understanding of customer problems, which leads to increased success (Danzinger, 2010). Accordingly:

H13: The greater the interacton orientaton of a frm, the greater the frm’s customer-specifc success is.

It is known from literature that market orientaton and entrepreneurial orientaton have synergetc effects on the product innovaton actvites and performance (Atuahene-Gima and Ko, 2001). Furthermore, Baker and Sinkula (1999b) fnd a synergetc effect of market orientaton and learning orientaton, showing that they both combine positvely to impact the change in relatve market share. In additon, they identfy a synergistc effect of market orientaton and learning orientaton on new product success. This is why we assume that there are positve or negatve synergetc effects of market orientaton and interacton orientaton on suitable constructs, too.

Firms that combine high levels of interacton and market orientaton should perform beter in consequence in effectveness or customer-specifc success than other combinatons of both orientatons. Since frms with lower market orientaton might have an inflexible structure of interacton orientaton, we also argue that the greater the organizaton’s market orientaton, the stronger the positve relatonship between its interacton orientaton and effectveness or success is. Therefore:

H14: There are synergetc effects of interacton orientaton and market orientaton on effectveness.

H15: There are synergetc effects of interacton orientaton and market orientaton on customer-specifc success.

Data and measures

We have derived data from structured questonnaires drawn from a random sample of people who are occupied with selling and enter into direct contact with customers. The surveys are also checked for obvious instances of incompleteness and yes-saying. This process eliminates less than 2% of the sample. The fnal sample consists of 231 partcipants, who have answered a total of 165 questons

Most of our measures have been used in past research and consist of items on a seven point Likert scale with the response items ranging from 1 (= “applies completely”) to 7 (=“doesn’t apply at all”). Number of employees (variable: employees; 1 = “> 100”), sales previous year (sales; 1 = “> EUR 10 million”), type of operaton (b2b; 1 = “business-to-business”, 0 = “businessto-consumer”), gender (sex; 1 = “man”) and distributon (sphere; 1 = “(inter) natonal”, 0 = “local”) are binary just as the industry variables energy (1 = “company is a energy frm”) and fnance (1 = “company is a fnancial services frm”), which are based on the latest NACE Codes using the NACE Revision 2 Classifcaton (Eurostat, 2008). Tenure and age are measured in years.

We have adapted the scales of interacton orientaton from Ramani and Kumar (2008), consistng of four dimensions relatng to the frm’s belief in the customer concept, the interacton response capacity, the customer empowerment and the customer value management. Furthermore, we also developed another sub-construct as some exploratve interviews have indicated that the understanding for the customer problem is a central aspect of interacton’s success of the company (Danzinger, 2010, p. 145). In additon, we developed some new items to measure normatve insttutonal pressure (normatve3), outsourcing expertse (outsource3) and dependence on trademarks (trademarks3).

Learning orientaton is operatonalized by the scales from Sinkula et al. (1997) and Jerez-Gomez (2005). The interviews have revealed clearly that learning orientaton without human resources practces is not completely defned. Therefore we add that construct as another dimension of learning orientat on, so it consists of four sub-constructs: experimentat on and openness, learning commitment, shared vision and human resources pract ces. The measure of market orientat on is adopted from the original MKTOR scale (see Narver and Slater, 1990). For proact veness (PRO), we use the items developed by Venkatraman (1989).

One part of the measures in Figure 1 is taken from Ramani and Kumar (2008), who include them as determinants of interact on orientat on. This f gure also shows that the other hypothet cal antecedents have been tested to be determinants of organizat onal learning or market orientat on. That is certainly the case for the consequences of interact on orientat on, which are formerly verif ed consequences of market or learning orientat on. With regard to the formulated hypotheses and presented determinants the following model is constructed:

Figure 1. The hypothesized model


We carry out a conf rmatory factor analysis to extract the factors to conf rm the validity of our new sub-construct understanding customer problems (ucp) as a part of the latent variable interact on orientat on. Thus, we invest gate our quest onnaire to check if it correctly determines the proposed substructure. Init ally the internal consistency of the grouped quest ons is studied by Cronbach’s alpha for our sample. Each construct has an alpha greater than 0.7, so the data has an acceptable degree of reliability. As extract on method for the subsequent factor analysis we use principal components and a varimax rotat on of the loadings. For the discriminant validity of the factor analysis we claim the diff erence of the loadings of one item on diff erent factors to be less than 0.2 (Nunnally and Bernstein, 1994). For convergent validity the relevant loadings should be greater than 0.4 (Anderson and Gerbing, 1988; Chen, Paulraj and Lado, 2008).

Linear relat onship between interact on orientat on and its determinants is assumed. We ident fy the crucial eff ects on interact on orientat on by a linear regression model. Since we observe several outliers in our data set, we eliminate extreme observat ons. We exclude respondents exhibit ng a Cook’s distance that exceeds the convent onal threshold 4/(n-k-1), where n denotes the sample size and k the number of covariates (Fox, 1997, p. 281). Another linear model is applied to determine the eff ect of interact on orientat on, learning orientat on, market orientat on and proact veness to the above ment oned consequences. In this case, we do not delete outliers for each model for the sake of comparability. In either regression we check for mult collinearity by the variance infl at on factor. All analysis are carried out using SPSS 19 and R 2.7.

Descriptive statistics

Our data set comprises 231 cases whereof 133 quest onnaires have been answered by male and 98 by female interviewees. The mean age of the respondents is 34 (sd=11.39), with a minimum of 20 and a maximum of 63 years, hence covering the range of relevant age. We dist nguish between several industries. The boxplots in Figure 3 illustrate the impact of the sector on interact on orientat on. We hypothesize that companies in the f nancial sector are aff ected to interact on orientat on to a greater extent than any other line of business. This hypothesis is encouraged by Figure 2 showing that f nancial services features the smallest median of all industries and that 25% of all companies in this industry have a value between 1.94 and 2.38 for the aggregated interact on orientat on item.

Figure 2. Box plots for interacton orientaton separated by industrial sector

Also, the energy sector reveals an above average interacton orientaton. This may be due to the fact that it is mainly business-to-business (cf. Table 3). Furthermore, we see that in our sample the fnancial business sector is mostly business-to-client. Also, frms that deal mainly with private customers dominate the sectors hospitality, retail and health while companies that primarily serve business clients are of the producton segment. The remaining business areas are well-balanced.

Table 3. Contngency table for customer type, averaged strategic orientaton and industry
B2B 47% 69% 4% 13% 6% 53% 61% 23% 51%
IO 3.12 2.94 2.62 3.59 3.60 2.98 3.29 3.55 3.13
LO 3.32 2.92 2.77 3.17 3.95 3.11 3.27 3.32 3.18
MO 3.29 3.24 2.96 3.60 3.31 3.18 3.47 3.39 3.33
PRO 4.24 3.75 4.02 4.25 4.48 3.83 4.39 4.13 3.99

Factor analysis

We run the factor analysis involving relevant items for the latent construct of interacton orientaton. The Kaiser-Meyer-Olkin criterion suggests good sampling adequacy (KMO=0.858). All observed communalites are greater than the usual threshold of 0.3, lying between the minimum of 0.535 and the maximum of 0.818. The eigenvalue criterion recommends picking the factors with an eigenvalue greater than 1. In our case we therefore obtain fve factors. The fracton of the variance conserved by these extracted components is 70%, which indicates a good explanatory power of the factors. All extracted and rotated factors explain more than 10 percent of the variance each, with a maximum of nearly 19% for factor 2. We can assign each factor to one of the intended sub-constructs of customer management value, customer empowerment, understanding customer problems, interacton response capacity and belief in the customer concept. For example we can interpret factor 1 as a customer management value since only items crm1 to crm3 exhibit a substantal loading on this factor (see Table 4). All relevant loadings are greater than 0.4. The item ucp2 does not have acceptable discriminatve power as it reveals a high loading both on the ce and ucp factors. By contrast, we can see that the new items ucp3 and ucp4 differentate more clearly.

Our fndings implicate that indeed a ffh dimension understanding customer problems of interacton orientaton exists. For future studies we recommend to evolve a new item ucp2, since it lacks discriminatve power. Note that the loading of the item ucp3 is highly negatve, because it is a reverse item.

Table 4. Extracted factors and rotated factor loadings
UtemFactor 1Factor 2Factor 3Factor 4Factor 5
cvm1 0.798 0.094 0.166 0.234 0.115
cvm2 0.858 0.116 0.029 0.225 0.088
cvm3 0.867 0.099 0.048 0.113 0.146
ce1 0.140 0.748 0.166 0.242 -0.100
ce2 0.082 0.785 -0.012 0.188 0.065
ce3 0.115 0.878 0.109 0.052 0.113
ce4 0.015 0.850 0.114 0.035 0.172
ucp1 0.210 0.410 0.627 0.161 0.276
ucp2 0.234 0.438 0.563 0.051 0.148
ucp3 0.039 0.164 -0.822 -0.111 0.123
ucp4 0.078 0.263 0.607 0.074 0.292
irc1 0.123 0.229 0.055 0.782 0.052
irc2 0.166 0.143 0.132 0.865 0.061
irc3 0.335 0.310 0.066 0.604 0.344
irc4 0.174 -0.035 0.095 0.767 0.199  
cc1 0.041 -0.024 -0.038 0.066 0.816
cc2 0.164 0.183 0.293 0.352 0.584
cc3 0.275 0.187 0.222 0.187 0.652

Reliability and validity

For the subsequent analysis we examine the reliability of our items by Cronbach’s alpha and Item-To-Total-correlatons. For the former we impose a threshold of 0.7, and in case of a lower alpha-value we choose a subset of items for each group satsfying the restricton. The Fornell-Larcker-Criterion requires that the average variance extracted of the constructs should be greater than the square of the correlatons among the constructs (Fornell and Larcker, 1981). This conditon has been met and all items have high factor loadings, so discriminant and convergent validity are proved.

Determinants of interacton orientaton

Now we perform a regression analysis to identfy the determinants of interacton orientaton. As predictors we introduce a lot of variables (see Measures). With a frst regression we compute Cook’s distance for each observaton. The histogram of all distances in Figure 3 suggests to eliminate observatons that show a Cook’s D greater than 0.02, which is consistent with the threshold of 4/(n-k-1)=0.019 which we use here. In doing so, 216 observatons remain. Figure 3. Histogram of Cook’s distances The ft of the regression model is very promising (R²=0.694, and F=17.314, p=0.000). The resultng parameter estmates, errors, standardized estmates and p-values are given in Table 5. Also, tolerance values and variance inflaton factors are reported. None of the later exceeds 10 so that obviously we do not face multcollinearity issues (see Belsley et al., 1980, p. 93). suggests to eliminate observations that show a Cook's D greater than 0.02, which is consistent with the threshold of 4/(n-k-1)=0.019 which we use here. In doing so, 216 observatons remain.

Figure 3. Histogram of Cook’s distances

The fit of the regression model is very promising (R2=0.694, and F=17.314, p=0.000). The resultng parameter estmates, errors, standardized estmates and p-values are given in Table 5. Also, tolerance values and variance inflaton factors are reported. None of the later exceeds 10 so that obviously we do not face multcollinearity issues (see Belsley et al., 1980, p. 93).

Table 5. Results of the regression on interacton orientaton
VariablecoefcientSdStd. Coeff.p-ValueVIF
constant 0.238 0.591 0.688
B2B -0.384 0.103 -0.179 0.000 1.442
LO 0.418 0.057 0.465 0.000 2.508
reward -0.011 0.032 -0.016 0.738 1.504
trademarks -0.036 0.031 -0.060 0.243 1.633
outsource 0.018 0.031 0.027 0.550 1.253
normatve 0.075 0.038 0.109 0.050 1.903
affectve 0.019 0.051 0.023 0.707 2.426
contnuance -0.091 0.049 -0.084 0.063 1.271
satsfacton 0.040 0.069 0.038 0.561 2.632
conflicts -0.049 0.037 -0.059 0.181 1.200
connectedness -0.048 0.048 -0.047 0.319 1.405
adaptve 0.079 0.049 0.077 0.112 1.470
technoturbu 0.033 0.031 0.054 0.293 1.653
compettve 0.109 0.038 0.137 0.005 1.421
marketurbu 0.126 0.050 0.126 0.013 1.578
cannibalize 0.175 0.041 0.226 0.000 1.767
formalizaton -0.047 0.033 -0.065 0.156 1.284
employees 0.015 0.130 0.007 0.909 2.559
sales 0.092 0.139 0.046 0.509 2.951
sphere 0.142 0.105 0.070 0.179 1.671
tenure -0.001 0.008 -0.010 0.867 2.131
fnance -0.533 0.154 -0.157 0.001 1.280
energy -0.093 0.183 -0.022 0.613 1.160
sex 0.042 0.089 0.020 0.640 1.196
age 0.011 0.005 0.118 0.044 2.113

Signifcant effects (at the level of 0.05) can be observed for the variables B2B, LO, normatve, contnuance, compettve, marketurbu, cannibalize, fnance and age. The assumpton of a high interacton orientaton in fnancial services is supported by the results whereas the energy sector does not have a signifcant effect since it is mainly B2B. Learning orientaton has obviously the highest absolute standardized estmate and thus a large impact on interacton orientaton. This is most likely due to the fact that both are strategic orientatons. Although we expected contnuance to have a positve effect, it appears to be negatve. In fact, contnuance is correlated with affectve since both are commitments, thus the exclusion of either of them could change the indicaton. The variable trademarks confrms the result of Ramani and Kumar (2008), although the effect is not signifcant. A variable selecton could possibly lead to signifcant results.

Separate regressions for different groups of covariates reveal which group conserves most of the variance of interacton orientaton by means of the model’s R². In this regard, the organizatonal culture strongly influences interacton orientaton. Also the environment and employee percepton are good indicators. Organizatonal structure and employee characteristcs seem to be less important. The observatons above show that age does have a signifcant influence, nevertheless we see here that experience does not sufciently state interacton orientaton.

Table 6. R2 by group of determinants
GroupR2Adjusted R2
Company Characteristcs 0.170 0.146
Employee Characteristcs 0.041 0.027
Employee Percepton 0.202 0.190
Environment 0.280 0.266
Organizatonal Culture 0.608 0.602
Organizatonal Strategy 0.169 0.157
Organizatonal Structure 0.063 0.049

Consequences of interacton orientaton

Now we investgate the consequences of interacton orientaton, learning orientaton, market orientaton and proactveness as a dimension of entrepreneurial orientaton. Interacton orientaton appears not to influence adaptveness, entering new markets or product innovaton (see Table 7). However, a signifcant effect on customer-specifc success and effectveness can be observed. All p-values are rather small so that an augmentaton of the sample size could lead to signifcant results. Furthermore, we see that innovaton requires a proactve attude and also the opening of new markets is mainly influenced by proactveness and market orientaton. The results indicate that high adaptveness arises from proactveness, market and learning orientaton whereas proactveness is less important for customer-specifc success and effectveness. The later is influenced signifcantly by market orientaton and interacton orientaton. Hence, learning orientaton does not have an impact on effectveness as it has on customer-specifc success, just like market and interacton orientaton. We conclude that market orientaton stll is an important factor. The estmaton of the interacton effect between interacton orientaton and market orientaton does not yield signifcant results. For the other regressions we did not estmate the interacton effects since the main effects are not signifcant.

Verifcaton of hypotheses

Now we examine the validity of our hypotheses. To begin with we examine H1, which claims that business-to-business frms have a higher interacton orientaton than business-to-consumer frms. This hypothesis is clearly supported by the regression (refer to Table 4). The signifcant parameter estmate of -0.384 (P<0.001) is negatve, thus indicatng the validity of hypothesis 1. Also, our regression afrms H2. The estmate related to normatve insttutonal pressure is 0.075 (P=0.050) so that an increase in this item causes a rise in interacton orientaton. Therefore, our fndings verify hypothesis 2. Compettve intensity also features a positve estmate in our regression model 2 (estmate 0.109, P=0.005) and thus we can approve H3 since this indicates a positve influence of compettve intensity on interacton orientaton. Hypothesis H4 states that the greater the market turbulence, the greater a frm’s interacton orientaton. The corresponding parameter estmate of 0.126 (P=0.013) is consistent with this statement. The next hypothesis H5 argues that the frm’s willingness to cannibalize supports its interacton orientaton. Since our estmate for the cannibalizaton effect is signifcantly positve (estmate 0.175, P<0.001) this conjecture proves to be true. The fnding that the estmated effect of learning orientaton is statstcally signifcant and positve (0.418, P<0.001) indicates, furthermore, that H6 is true. This determinant is more important than the others, because the standardized coefcient has the greatest impact on interacton orientaton.

Table NO.
VariableProduct InnovatonEntering New MarketsEffectvenessCustomer-specific SuccessAdaptveness
constant -0.614 (0.114) -0.311 (0.424) 0.003 (0.995) 0.111 (0.828) -0.582 (0.063)
IO 0.186 (0.086) 0.154 (0.157) 0.335 (0.031) 0.316 (0.042) 0.155 (0.186)
LO -0.001 (0.989) 0.059 (0.551) 0.256 (0.090) 0.360 (0.017) 0.159 (0.045)
MO 0.182 (0.106) 0.244 (0.031) 0.282 (0.001) 0.352 (0.000) 0.326 (0.000)
PRO 0.863 (0.000) 0.653 (0.000) 0.045 (0.550) -0.087 (0.251) 0.496 (0.000)
IO x MO     -0.027 (0.464) -0.035 (0.346)  
R2 (Adj.) 0.411 (0.401) 0.355 (0.343) 0.363 (0.348) 0.392 (0.379) 0.461(0.452)

The estmated parameter for employees’ age is also statstcally signifcant and positve (0.011, P=0.044) so that older employees offer a higher interacton orientaton than their younger colleagues (H7). As we have seen before, fnancial frms exhibit a greater degree of interacton orientaton than companies in other industries (H8). This result is supported by the boxplots in Figure 3 as well as by the parameter estmate in the regression model, which is -0.533 (P=0.001)

Now we look at the hypotheses regarding the consequences of interacton orientaton. Hypothesis H9 claims that the greater the frm’s interacton orientaton, the more product innovatons are generated. This can be afrmed by the positve estmate (0.186, P=0.086). Also we conclude that the frm’s interacton orientaton enhances the commitment to opening up new market (H10). This is supported by the estmated parameter value of 0.154 (P=0.157). In additon, the impact of interacton orientaton on the adaptveness (H11) is verifed by the parameter estmate of our regression model (0.155, P=0.186). Also effectveness (0.335, P=0.031) and customer specifc success are achieved by interacton orientaton (H12 and H13). However, the last two hypotheses H14 and H15 are not substantated by our results since both interacton effects do not turn out to be statstcally signifcant.

Discussion and conclusion

The results of our study reveal operatve recommendatons for companies. Interacton orientaton is a crucial factor for the fulfllment of business objectves. The business culture turns out to be an essental determinant of interacton orientaton. Furthermore, companies should be willing to cannibalize and provide a distnct learning orientaton. Indeed, organizatonal learning is of partcular importance, that is to say not only should the companies pursue single-loop or double-loop learning but rather Deutero learning, i.e. they should learn to learn. Market Orientaton, interacton orientaton and learning orientaton can increase business success whereas learning is not of importance for business efciency. Older and thus generally more experienced employees offer a superior interacton orientaton and should therefore be recruited preferably. Nevertheless, the work experience is not a sufcient indicator for interacton orientaton. This paper shows that business-to-business frms have a greater interacton orientaton than business-to-consumer frms. Companies in the energy industry achieve the highest level of proactveness, whereas fnancial services are strongly oriented to interacton, learning and market. The health and hospitality sectors have a very weak level of strategic orientaton. In additon, the orientaton is influenced by the environment. Thus, industries with a high level of compettve intensity and market turbulence tend to show distnct interacton and market orientaton.

The greater the strategic orientaton of a frm, the greater the frm’s adaptability, effectveness and customer-specifc success. Furthermore, such companies are able to be more engaged in entering new markets. However, innovatons frst require a high degree of proactve attude.

In contrast to adaptve selling, interacton orientaton is more productrelated. The term focuses on the individual customer and usually a mutual relatonship will develop during this interacton. This orientaton has monetary elements, but neither compettve nor social components. We see that indeed a ffh dimension of interacton orientaton exists.

A challenge for further research is the reconstructon of our sub-construct understanding customer problems. Differentaton between business-tobusiness and business-to-customer is not satsfactory and should be refned to an industry confguraton. The business environment is worth being explored more deeply since three items of this group have a signifcant impact on interacton orientaton. The results of our study queston the existence of synergetc effects between market orientaton and learning orientaton.

Possibly a panel survey could elaborate the fndings of our crosssectonal study. Also, it could be helpful to have multple respondents of the same company to avoid single-informant bias. Increasing the sample size could lead to more signifcant results and an internatonal survey could help to generalize our results. Furthermore, the influence of natonal cultures can be examined. It should be considered whether individualism or small power distance result in a higher degree of interacton orientaton.

In our work we adopted the construct of market orientaton by Narver and Slater (1990), another opton is the design by Kohli and Jaworski (1990) which could be examined in another survey. In our study we did not perform any variable selecton technique since we did not fnd any evidence for multcollinearity. Thereby, we were able to present an overview of all effects. Omitng the insignifcant items could potentally lead to slightly different estmates and p-values, maybe even some of the insignifcant effects turn out to be signifcant afer all. Not only proactveness but also the complete construct entrepreneurship orientaton could serve as determinant of the business performance. Several variables like market and technological turbulences or absorptve capacity are known to have moderator effects on strategic orientatons and could be the objectve of further research. We also think of group wise regressions on interacton orientaton for a beter understanding of the effects and to avoid possible problems of correlated covariates.

From the implicatons of our research we conclude that interacton orientaton is relevant in every market environment. Firms should focus on building an interacton orientaton, regardless of whether they have a higher degree of learning or market orientaton.


  • Abrahamson, E., Rosenkopf, L. (1993). Insttutonal and compettve bandwagons: Using mathematcal modeling as a tool to explore innovaton diffusion. Academy of Management Review, 18(3), 487-517.
  • Anderson, J. C., Gerbing, D. W. (1988). Structural equaton modeling in practce: A review and recommended two-step approach. Psychological Bulletn, 103(3), 411-423.
  • Argyris, C., Schön, D. (1999) Organizatonal Learning II, Addison-Wesley, Reading.
  • Arrow, K. J. (1962). Economic Welfare and the Allocaton of Ressources for Inventon. In: Nelson, R. R. (Ed.), The Rate and Directon of Inventve Actvity: Economic and Social Factors. UMI: New York, 609-625.
  • Atuahene-Gima, K., Ko, A. (2001). An empirical investgaton of the effect of market orientaton and entrepreneurship orientaton alignment on product innovaton. Organizaton Science, 12, 54-74.
  • Baker, M. J., Sinkula, J. M. (1999a). Learning orientaton, market orientaton, and innovaton: Integratng and extending models of organizatonal performance. Journal of Market Focused Management, 4, 295-308.
  • Baker, M. J., Sinkula, J. M. (1999b). The synergistc effect of market orientaton and learning orientaton on organizatonal performance. Journal of the Academy of Marketng Science, 27(4), 411-427.
  • Belsley, D. A., Kuh, E., Welsch, R. E. (1980) Regression Diagnostcs: Identfying influental data and sources of collinearity. John Wiley: New York.
  • Buckler, F. (2003). NEUSREL: Mit Neuronalen Netzen kausale Zusammenhänge aufdecken und verständlich darstellen‘. In: Wiedmann, K.-P., Buckler, F. (Eds.), Neuronale Netze im Marketng-Management. Gabler: Wiesbaden.
  • Calantone, R. J., Cavusgil, S. T., Zhao, Y. (2002). Learning orientaton, frm innovaton capability, and frm performance. Industrial Marketng Management, 31, 515-524.
  • Chandy, R. K.,Tellis, G. J. (1998). Organizing for radical product innovaton: The overlooked role of willingness to cannibalize. Journal of Marketng Research, 35(4), 474-487.
  • Chen, I. J., Paulraj, A., Lado, A. (2008). Strategic purchasing, supply management, and frm performance.Journal of Operatons Management, 22(5), 505-523.
  • Covin, J. G., Slevin, D. P. (1989). Strategic management of small frms in hostle and benign environments. Strategic Management Journal, 10(1), 75-87.
  • Danzinger, F. (2010) Kundeninteraktonskompetenz in Industriegütermärkten: Eine empirische Studie zur Interaktons- und Lernorienterung. Gabler: Wiesbaden.
  • Deng, S., Dart, J. (1994).. Measuring market orientaton: A mult-factor, multitem approach. Journal of Marketng Management, 10, 725-742.
  • Dharmadasa, P. (2009) Organisatonal Learning, Innovaton and Performance in Family-Controlled Manufacturing Small and Medium-Sized Enterprises (SMEs) in Australia. Dissertaton: Bond University.
  • Duff, A., Boyle, E., Dunleavy, K., Ferguson, J. (2004). The relatonship between personality, approach to learning and academic performance. Personality and Individual Differences, 36, 1907-1920.
  • Eurostat (2008). NACE Revision 2: Statstcal Classifcaton of Economic Actvites’. Retrieved from: htp://epp.eurostat.ec.europa.eu (Accessed 20th Dezember 2011).
  • Farrell, M. A. (1999). Antecedents and consequences of a learning orientaton. Marketng Bulletn, 10, 38-51.
  • Farrell, M. A. (2000). Developing a market-oriented learning organisaton. Australian Journal of Management, 25(2), 201-222.
  • Farrell, M. A., Oczkowski, E. (2002). Are market orientaton and learning orientaton necessary for superior organizatonal performance? Journal of Market-Focused Management, 5, 197-217.
  • Fornell, C., Larcker, D. F. (1981). Evaluatng Structural equaton models with unobservable variables and measurement error. Journal of Marketng Research, 18(1), 39-50.
  • Fox, J. (1997) Applied regression analysis, linear models, and related methods. Sage: Thousand Oaks.
  • Grinstein, A. (2008). The relatonships between market orientaton and alternatve strategic orientatons: A meta-analysis. European Journal of Marketng, 42(1), 115-134.
  • Homans, G. C. (1951). The Human Group, Harcourt: Brace & World, New York.
  • Homburg, C. (2004)Perspektven der marktorienterten Unternehmensführung. Gabler: Wiesbaden.
  • Hult, G. T. M., Hurley, R. F., Knight, G. A. (2004). Innovatveness: Its antecedents and impact on Business Performance. Industrial Marketng Management, 33, 429-438.
  • Irving, E. (1995) Marketng Quality Practces, Dissertaton, University of North Carolina.
  • Jaworski, B. J., Kohli, A. K. (1993). Market orientaton: antecedents and consequences. Journal of Marketng, 57(3), 53-70.
  • Jerez-Gomez, P. (2005). Organizatonal learning capability: a proposal of measurement. Journal of Business Research, 58(6), 715-725.
  • Jimenez-Jimenez, D., Cegarra-Navarro, J. G. (2007). The performance effect of organizatonal learning and market orientaton. Industrial Marketng Management, 36, 694-708.
  • Karahanna, E., Straub, D.W., Chervany, N.L. (1999). Informaton technology adopton across tme: A cross-sectonal comparison of pre-adopton and post-adopton beliefs. MIS Quarterly, 23(2), 183-213.
  • King, W. R. (2004). Outsourcing and the future of it. Informaton Systems Management, 21(4), 83-84.
  • Kirca, A. H., Jayachandran, S., Bearden, W. O. (2005). Market orientaton: a meta-analytc review and assessment of its antecedents and impact on performance. Journal of Marketng, 69(2), 24-41.
  • Kohli, A. K., Jaworski, B. J. (1990). Market orientaton: The construct, research propositons, and managerical implicatons. Journal of Marketng, 54(2), 1-18
  • Krohmer, H. (1999) Marktorienterte Unternehmenskultur als Erfolgsfaktor der Strategie-implementerung. Gabler: Wiesbaden.
  • Kumar, V., Reinartz, W. (2006). Customer Relatonship Management: A Databased Approach. John Wiley & Sons: New York.
  • Lee, T-S., Tsai, H-J. (2005). The effects of business operaton mode on market orientaton, learning orientaton and innovatvenesss. Industrial Management & Data Systems, 105(3), 325-348.
  • Lumpkin, G. T., Dess, G. G. (1996). Clarifying the entrepreneurial orientaton construct and linking it to performance. Journal of Academy of Management Review, 21(1), 135-172.
  • McGuinness, T., Morgan, R. E. (2005). The effect of market and learning orientaton on strategy dynamics: The contributng effect of organisatonal change capability. European Journal of Marketng, 39(11), 1306-1326.
  • Mengüc, B. (1996). The influence of the market orientaton of the frm. Internatonal Journal of Research in Marketng, 13(3), 277-291
  • Miller, D. (1983). The correlates of entrepreneurship in three types of frms. Management Science, 29(7), 770–791.
  • Miller, D., Friesen, P. H. (1978). Innovaton in conservatve and entrepreneurial frms: Two models of strategic management. Strategic Management Journal, 3, 1-25.
  • Narver, J. C., Slater, S. F. (1990). The Effect of a market orientaton on business proftability. Journal of Marketng, 54(4), 20-35.
  • Neal, A., West, M. A., Paterson, M. G. (2004). Do Organizatonal Climate and Strategic Orientaton Moderate the Relatonship between Human Resource Management Practces and Productvity. Working Paper, London School of Economics and Politcial Science.
  • Newell, F. (2003). Why CRM Doesn’t Work? Bloomberg Press, Princeton. Nunnally, J. C., Bernstein, I. H. (1994). Psychometric Theory. McGraw-Hill: New York.
  • Pantaleo, G., Wicklund, R. A. (2000). Multples perspectves: Social Performance beyond the single criterion. Zeitschrif für Sozialpsychologie, 31(4), 231-242.
  • Park, J-E., Holloway, B. B. (2003). Adaptve selling behavior revisited: An empirical examinaton of learning orientaton, sales performance, and job satsfacton. Journal of Personal Selling and Sales Management, 23(3), 239-252.
  • Peng, C.-H. (2008). The Relatonships between the Antecedents of Innovatveness and Business Performance. ISECS ’08 Proceedings of the 2008 Internatonal Symposium on Electronic Commerce and Security, 805-809.
  • Perez Lopez, S., Montes Peon, J. M., Vazquez Ordas, C. J. (2005). Human resource practses, organizatonal learning and business. Human Resource Development Internatonal, 8(2), 147-164.
  • Pirinen, R., Fränt, M. (2008). Framework and Culture of Proactve Competencies Learning Learning by Developing. WSEAS Internatonal Conference on Educaton and Educatonal Technology, 83-88.
  • Ramani, G., Kumar, V. (2008). Interacton orientaton and frm performance. Journal of Marketng, 72(1), 27-45.
  • Rueckert, R. W., Walker, O. C.,Roering, K. J. (1985). The organizaton of marketng actvites: A contngency theory of structure and performance. Journal of Marketng, 49(1), 13-25.
  • Saxe, R., Weitz, B. A. (1982). The SOCO scale: A Measure of the customer orientaton of salespeople. Journal of Marketng Research, 19, 343-351.
  • Scholderer, J. (2000). Marktorienterung und Unternehmensperformance in der deutschen Biotechnologieindustrie. Working Paper: Potsdam.
  • Schwaab, C., Scholz, T. (2000). Was wird gelernt beim Organisatonalen Lernen? Eine qualitatve empirische Untersuchung. Zeitschrif Führung und Organisaton, 6, 354-361.
  • Selnes, F., Jaworski, B. J., Kohli, A. K. (1996). Market orientaton in United States and Scandinavian companies: A cross-cultural study. Scandinavian Journal of Management, 12(2), 139-157.
  • Severiens, S., ten Dam, G. (1998). A multlevel meta-analysis of gender differences in learning orientatons. Britsh Journal of Educatonal Psychology, 68, 595-608.
  • Siguaw, J. A., Brown, G., Widing, R. E. (1994). The Influence of the market orientaton of the frm. Journal of Marketng Research, 31, 106-116.
  • Siguaw, J. A., Honeycut, E. D. (1995). An Examinaton of gender differences in selling behaviors and job attudes. Industrial Marketng Management, 24(1), 45-52.
  • Sinkula, J. M., Baker, W. E., Noordewier, T. (1997). A Framework for marketbased organizatonal learning. Journal of the Academy of Marketng Science, 25(4), 305-318.
  • Slater, S. F., Narver, J. C. (1995). Market orientaton and the learning organizaton. Journal of Marketng, 59(3), 63-74.
  • Spiro, R. L., Weitz, B. A. (1990). Adaptve selling: Conceptualizaton, measurement, and nomological validity. Journal of Marketng Research, 27(1), 61-69.
  • Steiners, D. (2005). Lernen mit Controllinginformatonen. Gabler: Wiesbaden.
  • Utzig, B. P. (1997). Kundenorienterung strategischer Geschäfseinheiten. Gabler: Wiesbaden.
  • Venkatraman, N. (1989). Strategic orientaton of business enterprises: The construct, dimensionality, and measurement. Management Science, 35(8), 942-962.
  • Verhoef, P. C., Leeflang, P. S. H. (2009). Understanding the Marketng Department’s Influence Within the Firm. Journal of Marketng, 73(1), 14-37.
  • Weitz, B., Sujan, H., Sujan, M. (1986). Knowledge, Motvaton, and Adaptve Behavior: A Framework for Improving Selling Effectveness. Journal of Marketng, 50(4), 174-191.
  • Wu, F., Mahajan, V., Balasubramanian, S. (2003). An Analysis of e-business adopton and its impact on business performance. Journal of the Academy of Marketng Science, 31(4), 425-447.
  • Zahra, S. A., George, G. (2002). Absorptve capacity. A Review, reconceptualizaton, and extension. Academy of Management Review, 27(2), 185-203.
  • Zheng, X., Cui, Y. (2007). Entrepreneurial Orientaton, Market Orientaton and Firm Performance: the mediator role of Organizatonal Learning. Proceedings of 2007 IEEE Xplore, 4391-4394.