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Inter-firm customer knowledge sharing in logistics services: an empirical study
956 Received September 2010 Revised February 2011 Accepted April 2011
Minna Rollins Marketing and Real Estate Department, University of West Georgia, Carrollton, Georgia, USA, and
Saara Pekkarinen and Mari Mehta¨la¨ Economics and Business Administration, University of Oulu, Oulu, Finland Abstract Purpose – The purpose of this paper is to examine customer knowledge sharing between a buyer of a logistics service and the logistics service provider (LSP). The authors attempt to fill the gap in current research by investigating inter-firm customer knowledge sharing. Design/methodology/approach – A survey study was conducted. Data were collected from buyers of logistic services. Confirmatory factor analysis and multiple regression were used to analyze data and test hypotheses. Findings – Results suggest that open and fluent communication mediates the relationship between customer knowledge sharing and satisfaction with a logistics service provider. In addition, the close relationship with the logistics service provider is needed to strengthen the relationship between customer knowledge sharing and satisfaction with the logistics service provider. Research limitations/implications – This study provided new empirical evidence concerning inter-firm customer knowledge sharing. The authors suggest that logistic service providers should be incorporated into the customer knowledge management process to ensure open and fluent communication about customers. Practical implications – This study provides practical insights for companies that sell logistic services. Originality/value – Customer knowledge sharing has been largely studied in an intra-firm context, for instance information sharing between marketing and research and development departments. This research extends the concept of customer knowledge sharing to the inter-firm context. Keywords Customer information, Customer relations, Logistics management, Business-to-business markets, Supply chain collaboration, Customer knowledge, Logistic services Paper type Research paper
International Journal of Physical Distribution & Logistics Management Vol. 41 No. 10, 2011 pp. 956-971 q Emerald Group Publishing Limited 0960-0035 DOI 10.1108/09600031111185239
1. Introduction A number of firms have recently outsourced their logistics operations to logistics service providers (LSPs) in order to provide efficient services, offer the potential to add value, and enhance customer relations (Sinkovics and Roath, 2004; Power et al., 2007). However, due to outsourcing of logistic services, companies have lost some of the central touchpoints to their customers. Previous research in logistics, marketing, and information systems areas has shown many benefits from sharing customer knowledge (CK) in the supply chain such as reducing transaction costs, lowering stock levels, The authors wish to thank TEKES (Finnish Agency for Technology and Innovation) for funding the project and the Jenny and Antti Wihuri Foundation for support in data collection.
and improving cash flows (Rai et al., 2006; Howard and Squire, 2007). Mithas et al. (2005) find that gains in CK are enhanced when firms share their customer-related knowledge with their supply chain partners. Gadde and Hulthe´n (2009) conclude that when managing third-party logistics relations increased interaction between buyer and LSP would be beneficial to the outcome of outsourcing. Stiess (2010) reports that increased information flow between supply chain members increased material flow through the supply chain. Pekkarinen and Ulkuniemi (2008) bring forth an interesting issue in relation to the role of LSPs which through outsourcing and partnering could be the role of integrator only assembling customer solution through modular processes actually produced by other companies. This creates many challenges such as how to manage information sharing and learning within the dynamic inter-firm context. The vast majority of work concerning knowledge management and knowledge sharing is restricted to intra-firm topics (Davenport and Prusak, 1998; Alavi and Leidner, 2001). There is a severe lack of empirical research on managing knowledge, in particular, sharing customer-related knowledge, in the inter-firm context (Mithas et al., 2005). Whipple and Russell (2007) found collaborative transaction, event and process management capabilities important and concluded that the managers have to develop collaborative strategies across a broad spectrum of relationships in order to determine which type of collaboration best fits each business relationship. The present study aims at contributing to the current literature of knowledge sharing in inter-firm context. We focus on examining the mediating effects of communication and collaboration between customer knowledge sharing (CKS) and satisfaction in a logistic service relationship. This paper is structured as follows. First, we will discuss the conceptual background of our study and after that present our research model and hypotheses. Second, we will discuss our methodological choices, and then present our results. Third, we discuss our findings and present managerial implications. In conclusion, we will discuss the limitations of this study and the avenues for the future research. 2. Conceptual background Organizations create value through information sharing and exchange. The knowledge-based view of the firm provides a theoretical base for explaining situations where knowledge needs to be transferred across the firms’ boundaries (Grant, 1996a, b). Knowledge-based theories of the firm emphasize the strategic importance of leveraging knowledge such as market information and business intelligence to support and enhance firm performance (Esper et al., 2010). In many studies knowledge-based view is viewed as intra-organizational phenomenon (Argote et al., 2003). We apply knowledge base view of the firm for knowledge sharing via inter-firm relationships across the members in the supply chain (Pillai and Min, 2010). Our study examines sharing CK between two firms, the customer (supplier or buyer in supply chain) and LSP. The knowledge-based view has its roots in the resource-based view of the firm (Argote et al., 2003; Penrose, 2008; Ahrend and Bromiley, 2009). In the resource-based view knowledge is treated as a generic resource whereas in knowledge-based view, knowledge is seen as an important resource creating value to the stakeholders where the ease of communication the explicit knowledge across boundaries of the firms (Grant, 1996b; Kogut and Zander, 2003; Chen, 2005). Alavi and Leidner (2001) explain that information technologies and systems can play an important role
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in the knowledge-based view; these systems can be used to “synthesize, enhance, and expedite intra- and inter-firm knowledge management” (Alavi and Leidner, 2001). Based on knowledge-based view, the managing CK may help LSPs who offer expertise and solutions to the operational processes in network organizations to achieve high performance in fulfill the needs of the whole network (Armistead, 1999). The knowledge-based view of the firm provides a starting point for our research model (Figure 1). 3. Hypotheses Figure 1 shows our research model. It shows the effect of CKS between the buyer and provider of a logistic service (CKS) on the buyer’s satisfaction with the LSP (SAT). We also propose the mediating roles of communication (COM) and inter-firm collaboration (COLL) as well as the moderating effect of the relationship (REL) between CKS and the buyer’s satisfaction with the LSP (SAT). Next, we discuss our hypotheses. 3.1 Customer knowledge sharing In this study, the term “customer knowledge” is understood broadly. As Parry and Graves (2008) explain “knowledge is a fluid mix of experiences, value, contextual information and expert insight offering a framework to evaluate and integrate new experiences and information”, we define the term “customer knowledge” same way; knowledge about and from customers; products, technology, and the problems involved in a particular customer relationship (adopted Gebert et al., 2003: CK, Rollins, 2008: customer-specific information). Our definition of CK differs from one Fugate et al. (2008) propose for “logistics market intelligence”. They view logistic market intelligence as a capability to collect and evaluate customer-related information by logistics activities with respect to how well the information can be used in logistics and in other business decisions. We emphasize that sharing CK between the buyer of a logistic service and the LSP should be a dialog between all the parties from the buyer’s and LSP’s side (Kohli and Jaworski, 1990; Mason and Leek, 2007). Both parties should contribute to gaining better knowledge about and from customers and, thus, to produce better customer experience (Frow and Payne, 2006). CK is collected from several sources and parties in the relationship between a customer and LSP, it is related to all the firm’s functions, and it can be used at different organization levels (Kohli and Jaworski, 1990).
COM H3b+
H3a+ H4a+
COLL
CKS
SAT H1+ H2+
Figure 1. Conceptual model and hypotheses
H4b+
REL
Wang and Regan (2003) advise that LSPs should design their services according to the business environment, considering the buyer’s products and industry and giving a big emphasis to customer relationship management with the aim of developing strong and long-lasting ties with their customers. From the logistics service buyer’s point of view, the potential benefit from sharing CK with the LSP could be a higher satisfaction with the LSP, whereas, from the LSP’s point view, the benefits may actualize as a long-term business relationship (Mason et al., 2007). Based on the previous, we propose as follows: H1. Inter-firm CKS between a buyer and LSP is positively related to the buyer’s satisfaction with the LSP. 3.2 The nature of the relationship between the buyer and the LSP Bolton et al. (2003) propose that social and structural bonds described by the length and nature of the relationship and the quality of customers’ prior experiences enhance business-to-business relationships. Kerr (2007) explains that the relationship between the buyer and the LSP in logistics outsourcing relies on empathy and consistency, communication at the several organizational levels, shared future goals and openness to change. The buyer’s reasons to build the relationship with the LSP are different to those of the LSP. The buyer usually prioritizes quality, reliability and optimization of logistics activities, whereas the LSP mainly prefers large, financially steady manufacturers, who can offer long-term contracts with large volumes (Mortensen and Lemoine, 2008; Quinn, 2005). Therefore, it can be proposed that the close relationship between the LSP and the buyer has an influence on how CK is actually transferred and shared influence the buyer’s satisfaction with the LSP (Tu et al., 2004). We propose as follows: H2. A close relationship between a buyer and the LSP strengthens the influence between CKS and satisfaction with the LSP. 3.3 Communication between a buyer and the LSP Communication processes are important facilitators of knowledge transfer within and between organizations (Anantatmula and Kanungo, 2010). CK can be transferred and shared via numerous type of channels, e.g. using dashboards, intra- and extranets, ERP systems, but also through all communication channels developing and improving (non-)personal, informal communication between the customer and the firm. Communication and collaboration enable conducting management of knowledge successfully and they should be encouraged by the appropriate organization culture (Parry and Graves, 2008; Anantatmula and Kanungo, 2010). Coordination of specialized capabilities and knowledge of the firms requires also collaboration of the members in the logistics relationships (Yazdanparast et al., 2010). Frequent communication between parties in the supply chain is necessary to ensure good service quality and customer service (Kohli and Jaworski, 1990; Ryals and Humphries, 2007). In addition, informal relationships between the actors in both organizations, buyer and LSP, improve daily cooperation and hinder the conflicts. Based on this, we put forward the following hypotheses: H3a. CKS is positively related to open and fluent communication between the buyer and the LSP. H3b. Open and fluent communication between the buyer and the LSP is positively related to the buyer’s satisfaction with the LSP.
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3.4 Inter-firm collaboration Inter-firm relationships are defined as “collaboration between independent companies through formal agreements” (Hagedoorn, 2002). In this research, “inter-firm collaboration” refers to relationship-specific assets and investments that include, for instance, investments in physical resources (such as IT systems), human resources (such as employee training), and capabilities. We mainly focus on the social aspect of the inter-firm collaboration, which is one of the poorly considered factors in the current literature (Ruy et al., 2008). Developing a business relationship requires resources from one or both of the parties who have invested assets in the relationship (Havila et al., 2004). Moreover, by committing the appropriate resources, the parties demonstrate their willingness to create relationship-specific assets and to share the belief that the relationship is valuable (Sinkovics and Roath, 2004). In the logistics service industry, if a buyer of logistic service shifts towards sourcing fewer and larger service solutions, the LSP usually needs to invest more in relationship-specific practices and assets (Howard and Squire, 2007). Sinkovics and Roath (2004) suggest that the buyer and the LSP can use inter-firm collaboration to further capitalize their unique resources. They add that achieving the optimal value demands collaboration and partner interaction through open communication and information sharing. We propose as follows: H4a. CKS is positively related to inter-firm collaboration between the buyer and the LSP. H4b. Inter-firm collaboration is positively related to the buyer’s satisfaction with the LSP. 4. Methodology 4.1 Sampling and data collection The research method in the empirical part of this paper is based on the survey data on the buyers of logistics services. The LSPs act as third-party intermediaries in the buyer’s supply chain. Therefore, the data we use either concern the seller or the buyer of the products. The data were collected by an online questionnaire from Finnish companies. An e-mail message was sent to people whose position was related to logistics, marketing, or the managing director and to people whose name was available in the database. The first respondent was asked to forward the questionnaire to the person who had the best knowledge of outsourcing/buying logistics services in that organization to ensure the competence of the key informants. We used two main criteria when selecting the sample frame. First, the companies should use logistics services significantly (e.g. mining, manufacturing, oil, gas, and water maintenance and construction). Second, the sample companies should have at least 50 employees and a turnover of more than e400,000. Questionnaires were sent to 1,043 companies. Our sample frame included some companies twice because a few of the companies had several offices. These overlapping cases were removed from the sample before data analysis. We received 235 acceptable responses for empirical analysis that yields a response rate of 22.5 per cent, with an incentive to win a car navigator. In the sample, approximately 50 per cent of the companies had a turnover of less than e20 million, and approximately 50 per cent had a turnover of more than e20 million. Exporting contributed for
more than 20 per cent of the turnover in more than half (51.2 per cent) of the companies in the sample. As this study examines CKS in the supply chain, our target informants were the ones involved in making the decisions related to production, logistics, and/or transportation. About 48 per cent of the respondents in our sample had a title related to procurement, production, or material management. About 26 per cent had a title related to transportation, logistics or supply chain management, and 10 per cent had a title related to marketing.
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4.2 Measures The constructs were measured using multi-item reflective measures adapted from the literature. In addition, some of the items were specifically created for this research. All the items were assessed on a seven-point Likert-type scale. The scales were anchored by “1 – strongly disagree [. . .] 7 – strongly agree” for all the other constructs except for satisfaction with the LSP, which was anchored by “1 – weak [. . .] 7 – excellent”. Two of the items for the CKS construct (CKS) were developed for this research and one item was adapted from Arantola (2006). The items directly inquired about CKS with the LSP: “we use and share CK with logistics firms” and “significant amount of CK from logistics operations are available to utilize in marketing”. The scale for satisfaction with the LSP was adapted from Bowersox et al. (1986) and it captured the satisfaction with the LSP ranging from expertise of personnel to on-time delivery. Communication between the buyer and the LSP was defined as open and fluent communication with the LSP (Deepen, 2007). The items measuring the buyer’s relationship with the LSP were developed for this research. These measures focused on the closeness of the relationship: “we have settled ways of action to manage problems with our service providers” and “we have good personal relationships with our service providers”. Finally, the last construct, the scale for inter-firm collaboration, was defined as the preconditions for the relationship. Items for this scale were developed for this research. Appendix 1 summarizes the items used. 5. Results 5.1 Measurement model: confirmatory factor analysis The respondents had filled the questionnaires accurately and missing data items were completed with SPSS software’s expectation maximization EM function for the measurement model of the constructs. The normality of the variables was analyzed with Prelis 2 software (Jo¨reskog and So¨rbom, 1993a). We conducted confirmatory factor analysis on the measurement model ( Jo¨reskog and So¨rbom, 1993b) before the regression analysis. Table I summarizes the number of the final items (based on the item-total correlations and excluding the low loading items), the Cronbach’s a Construct CKS Satisfaction with the LSP (SAT) Communication with the LSP (COM) Relationship with the LSP (REL) Inter-firm collaboration with the LSP (COLL)
No. of items
a . 0.6
CR .0.7
AVE . 0.5
3 6 3 2 3
0.74 0.90 0.75 0.76 0.77
0.76 0.89 0.76 0.76 0.77
0.61 0.78 0.61 0.55 0.62
Table I. Reliability and validity of the measures
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for internal validity test, the construct reliabilities, and the average variance extracted (AVE) by the constructs. All of the constructs satisfy the common requirements for measurement models. The individual loadings of operational measures of the constructs produced by the confirmatory factor analysis are given in Appendix 2. Our measurement model with the reduced set of the items was estimated as a confirmatory factor analysis using LISREL 8.7. The final measurement model has the fit indices as follows: x2 ¼ 293.14; df ¼ 104; p ¼ 0.000; RMSEA ¼ 0.071; CFI ¼ 0.96; and SRMR ¼ 0.07. The model fits well with data, except for the fact that SRMR should be less than 0.05 (Jaccard and Choi, 1996). For instance, Hu and Bentler (1999) recommend combining the CFI minimum of 0.95 with RMSEA of 0.06 or below or SRMR of 0.06 or below. For internal validity, the factor loadings of the individual items (Appendix 2), Cronbach’s a and the composite reliability should be greater than 0.7. For convergent validity, the AVE for the given construct needs to be greater than 0.5. Table I shows that the model fulfils the cut-off criteria both for the internal and convergent validity of the model. We included two control variables to test our research model: the industry and size of the company. The industry of the firm was a dummy variable (industry). “1” indicated that the company was either from the metal or machinery industry and “0” indicated other industries. The number of employees was used to indicate the size of the company (size) (Table II). 5.2 Hypotheses testing The hypotheses were tested using multiple regression analysis. The regression results are presented in Tables III-V and Table VI summarizes all the results. First, we tested H3a, in which communication with the LSP (COM) was used as a dependent variable and CKS and the control variables industry and the firm’s size as independent variables. The results in the Table III show that CKS is positively related to communication with the LSP, which supports H3b. The firm’s industry or size did not have a significant effect. Second, we tested H4a, which stated that CKS is positively related to inter-firm collaboration. This hypothesis did not receive support from the data (Table IV). Last, we tested hypotheses H1, H2, H3b, and H4b (Table V). Satisfaction with the LSP was used as dependent variable and CKS, interaction effect of CKS, the relationship
Table II. Correlation matrix
CKS COM COLL REL SAT Size Industry No. of items
CKS
COM
COLL
REL
SAT
Size
Industry
1.000 0.518 * * 20.072 0.304 * * 0.267 * * 0.051 20.103 3
1.000 2 0.045 0.578 * * 0.528 * * 0.096 2 0.002 3
1.000 2 0.133 * 2 0.120 0.033 0.016 3
1.000 0.530 * * 0.063 0.043 2
1.000 0.023 2 0.019 6
1.000 20.002 1
1.000 1
Note: Correlation is significant at: *0.05 and * *0.01 levels (two-tailed)
between the LSP, communication with the LSP, inter-firm collaboration, and the control variables industry and the firm’s size as independent variables. The effect of CKS on satisfaction with the LSP is significant and negative, which is the opposite of what we expected. Therefore, H1 is not supported. The interaction effect of CKS and relationship with the LSP is significant and positive. Therefore, H2 is supported. In H3a, we proposed that communication with the LSP is positively related to satisfaction with the LSP. The effect is significant and positive, which supports H3a. The H4b, considering the effect of inter-firm collaboration on satisfaction with the LSP was not supported. The effect is negative, but not significant. Control variables (industry and the firm’s size) did not have a statistically significant effect. The variance of inflation value was below ten, which suggests that there is no multicollinearity issue. Three of the hypotheses were supported and three were not supported. Next, we will discuss the results and present implications for managers.
Independent variables
St. beta
t-value
Sig.
15.28 9.05 0.893 1.398
0.000 * * 0.000 * * 0.373 0.163
St. beta
t-value
Sig.
Dependent variable: inter-firm collaboration Constant CKS 20.073 Industry 0.006 Size 0.031
10.914 21.051 0.091 0.433
0.000 * * 0.295 0.928 0.659
Dependent variable: communication with LSP Constant CKS 0.518 Industry 0.051 Size 0.080 2
Notes: *p , 0.05, * *p ¼ 0.01; R ¼ 0.27
Independent variables
Notes: *p , 0.05, * *p ¼ 0.01; R 2 ¼ 0.006
Independent variables
St. beta
t-value
Sig.
Dependent variable: satisfaction with the LSP Constant CKS (H1) CKS*relationship with LSP (H2) Communication (H3b) Inter-firm collaboration (H4b) Industry Size
2 0.45 0.617 0.327 2 0.079 2 0.015 2 0.024
12.745 23.25 4.03 4.24 21.330 20.252 20.396
0.000 * * 0.001 * * 0.000 * * 0.000 * * 0.189 0.801 0.693
Notes: *p , 0.05, * *p ¼ 0.01; R 2 ¼ 0.31
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Table III. Regression analysis for H3a
Table IV. Regression analysis for H4a
Table V. Regression analysis for H1, H2, H3b, and H4b
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Table VI. Summary of the results
6. Discussion of the results and managerial implications In this study, we have empirically examined inter-firm CKS in the logistic service relationships. We have also explored the roles of communication and inter-firm collaboration in the context of inter-firm CKS. Table VI summarizes the results and implications from this study. Our findings demonstrate the importance of building close relationships in inter-firm knowledge sharing. We found that sharing CK with the LSP has a positive influence on the buyer’s satisfaction with the LSP through the close relationship that is formed between the two parties. We did not find the support to the direct link between CKS and satisfaction with the LSP. This finding contradicts the current view on the positive impact of knowledge sharing in inter-firm context in general (Mithas et al., 2005). Our findings suggest that the closeness of the relationship may even play a larger role than previously thought in inter-firm knowledge sharing (Tu et al., 2004). Based on our findings, we suggest that is essential that the buyer and seller of logistics services work together in CK management issues and build trust before implementing CKS practices. It can also be argued, if a buyer of logistic services shares a considerable amount of customer-related knowledge with its LSP, this may raise expectations of the service level considerably. We suggest that it is essential that the logistics partners be incorporated into the communication processes of the buyer as open and fluent communication support. Knowledge management processes in order to deliver superior value to the end customer. In addition, both the buyer and the seller of a logistic service, the LSP, should derive some rewards for investing in the relationship. Our findings emphasize the role of open and fluent communication between the buyer and the LSP in sharing CK. Our findings point to the importance of communication as one of the mediating mechanisms that explains the association between CKS and satisfaction with the LSP. Open and fluent communication has been found to have an essential role in inter-firm CKS in many studies (Kohli and Jaworski, 1990). We recommend that LPS should create the avenues for the open communication with their customers. In addition, from the LSP’s point of view, open communication with the buyer might also promote customer satisfaction. In our study, preconditions for inter-firm collaboration of the relationship such as relationship-specific investments were not positively associated with CKS or satisfaction with the LSP. One explanation for this finding may be that our research Hypothesis
Result
H1. Inter-firm CKS between a buyer and LSP is positively related to the buyer’s satisfaction with the LSP H2. A close relationship between a buyer and the LSP strengthens the influence between CKS and satisfaction with the LSP H3a. CKS is positively related to open and fluent communication between the buyer and the LSP H3b. Open and fluent communication between the buyer and the LSP is positively related to the buyer’s satisfaction with the LSP H4a. CKS is positively related to inter-firm collaboration between the buyer and the LSP H4b. Inter-firm collaboration is positively related to the buyer’s satisfaction with the LSP
Not supported Supported Supported Supported Not supported Not Supported
focused on the social aspect of the inter-firm collaboration only (Ruy et al., 2008), excluding the traditional transaction cost analysis aspects such as costs associated with acquiring resources or monitoring exchange partners (Das and Teng, 2000). 7. Conclusions Our study explores inter-firm CKS in the context of logistic service industry. Data were collected from the buyers of logistic services in Finland and multiple regression and confirmatory factor analysis were used to analyze data. Our findings show that building close relationships and open and fluent communication in inter-firm knowledge sharing between a buyer and provider of logistic services is more beneficial than relationship-specific investments. In addition, both buyer and LSP should invest sharing CK. This study has limitations that need to be addressed and some of these limitations open a number of avenues for further research. The first limitation is our data collection design. We used key informant method in data collection, e.g. same person answered all the questions in the questionnaire. The second limitation is our study focus; we examined the CKS from the buyer’s perspective only. Future research could compare the views of CKS from both sides of the dyad, from LPS’ and buyer’s perspectives. We would like to call for more empirical research on CKS in the inter-firm context among supply chain partners. For instance, the future research could explore in more detail how and to what extent CK is actually shared in the logistic service sector and what kinds of performance applications this might have for the companies involved. In addition, an interesting research topic could be the organizational challenges from IT systems and human resources perspectives faced in CKS in inter-firm context. Further, future research could also explore the power balance between the buyer and the LSP and its effect on CKS between them. The role of customers and continuous interaction in the customer interface in developing new services has caught the attention of researchers (Chapman et al., 2003; Flint et al., 2008; Pekkarinen and Ulkuniemi, 2008). From the new service development perspective, future research could explore how CK generated and shared among supply chain partners facilitates creating new innovative logistic services. The concept of modular logistics services also creates many future research avenues in inter-firm CKS (Pekkarinen and Ulkuniemi, 2008). For instance, future research could explore the modular services offerings and modular process systems. References Ahrend, R.J. and Bromiley, P. (2009), “Assessing the dynamic capabilities view: spare change, everyone?”, Strategic Organization, Vol. 7 No. 1, pp. 75-90. Alavi, M. and Leidner, D.E. (2001), “Review: knowledge management and knowledge management systems: conceptual foundations and research issues”, MIS Quarterly, Vol. 15 No. 1, pp. 107-36. Anantatmula, V.S. and Kanungo, S. (2010), “Modeling enablers for successful KM implementation”, Journal of Knowledge Management, Vol. 14 No. 1, pp. 100-13. Arantola, H. (2006), Customer Insight. Uusi va¨line liiketoiminnan kehitta¨miseen, WSPOPro WSBookwell Oy, Juva.
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1. CK has a great importance in procurement (or sourcing) and logistics processes. 2. We use and share CK with logistics firms. 3. Significant amount of CK from logistics operations are available to utilize in marketing. Satisfaction (SAT) with the LSP; items 1-3 see Chow et al. (1994) and Bowersox et al. (1986); scale: 1 – weak, [. . .], 7 – excellent: 1. on-time delivery; 2. availability of logistic service; 3. capacity; 4. customer service skills; 5. availability of personnel; and 6. expertise of personnel. Communication (COM) with the LSP; items 1-3 Deepen (2007, p. 184); scale: 1 – strongly disagree, [. . .], 7 – strongly agree: 1. Open information transfer with our LSPs works well. 2. We often discuss developing of the operations with our logistics firms. 3. Information transfer works well at all the levels of organization. Relationship with the LSP (REL); scale: 1 – strongly disagree, [. . .], 7 – strongly agree: 1. We have settled ways of action to manage problems with our service providers. 2. We have good personal relationships with our service providers. Collaboration preconditions of the relationship (COLL); scale: 1 – strongly disagree, [. . .], 7 – strongly agree: 1. Service providers need to develop customized solutions to us. 2. Offering logistics services providers have to invest in assets specific for us. 3. Offering logistics services providers have to train their personnel for our specific needs.
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Table AI. Individual item loadings from the confirmatory factor analysis by Lisrel 8.7 (Cronbach’s a and item-total correlations by reliability analysis of SPSS 16.0)
Sharing customer knowledge (CKS) Customer knowledge has a great importance in sourcing and logistics processes (CKS1) We use and share CK with logistics firms (CKS2) Significant amount of CK from logistics operations are available to utilize in marketing (CKS3) Satisfaction (SAT) with the LSP On-time delivery (SAT1) Availability of logistic service (SAT2) Capacity (SAT3) Customer service skills (SAT4) Availability of personnel (SAT5) Expertise of personnel (SAT6) Communication (COM) with the LSP Open information transfer with our LSPs works well (COM1) We often discuss developing of the operations with our logistics firms (COM2) Information transfer works well at all the levels of organization (COM3) Relationship with the LSP (REL) We have settled ways of action to manage problems with our service providers (REL1) We have good personal relationships with our service providers (REL2) Collaboration with the LSP (COLL) Service providers need to develop customized solutions to us (COLL1) Offering logistics services providers have to invest in assets specific for us (COLL2) Offering logistics services providers have to train their personnel for our specific needs (COLL 3) 1.47 1.45 1.40 1.13 1.07 1.21 1.13 1.18 1.06 1.13 1.47 1.25 1.20 1.22 1.62 1.51 1.63
4.92 3.31 3.40 5.20 5.39 5.29 5.41 5.45 5.53 4.80 4.17 4.16 5.11 5.47 4.23 2.87 4.00
0.78
0.69
0.72
0.73 0.84
0.74 0.75
0.65
0.70 0.77 0.65 0.85 0.81 0.78
0.76
0.48 0.89
–
8.62
8.76
9.51 –
– 10.24
8.97
11.52 11.65 9.41 13.25 – 13.94
10.81
7.04 –
Mean Std. Loading (CA (. 0.5 *)) t-value
0.620
0.597
0.606 0.606 0.774 0.609
0.561 0.575 0.693
0.610 0.896 0.707 0.768 0.603 0.801 0.717 0.722 0.750 0.510
0.429 0.660
0.738
C. A. (.0.7)/item 2 total correlations (. 0.5)
970
Construct/items (indicator)
IJPDLM 41,10 Appendix 2
About the authors Minna Rollins (DSc in Economics & Business Administration) is Assistant Professor of Marketing at the University of West Georgia. Her dissertation research examined customer information usage in business-to-business markets. Dr Rollins’ research interests include customer relationship management, customer information usage, supply chain management, and international marketing. She has published in a number of international conference proceedings and in the Journal of Business Research. Minna Rollins is the corresponding author and can be contacted at:
[email protected] Saara Pekkarinen (DSc in Economics & Business Administration) is University Researcher of Logistics at the University of Oulu, Finland. She directs a two-year international research project, ModSeC: Modularity enabling the development of new innovative business service offerings 2008-2010, funded by Tekes, Finnish Funding Agency for Technology and Innovation. She explores modularity applied in business-to-business services, co-creation in new service development and organizational solutions required for modular service implementation from the perspective of service operations management and marketing. She has published in the International Journal of Logistics Management, Journal of Purchasing and Supply Management, International Journal of Logistics: Research and Applications and Journal of Business and Industrial Marketing. Mari Mehta¨la¨ (MSc in Economics & Business Administration) is a PhD Candidate at the University of Oulu, Finland. She works as a Marketing Manager at Optomed Oy in Oulu. In her doctoral dissertation, she explores how CRM system implementation and usage of these systems impact marketing processes.
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