IMPACT OF COMPETITOR AND CUSTOMER ORIENTATION ON OPERATIONAL PERFORMANCE- 3RD PARTY LOGISTICS’ PERSPECTIVE
Yousuf Agha
Iqra Khalid
Abstract
Third party logistics has become an important element of supply chain management due to its longer and complex involvement. The key to 3PL’s success is through maintaining an excellent quality of relation between the organization and orientation of competitor and customers. It is believed that 3rd party logistics providers can handle multiple elements and operational approaches to create value in their business. But the problem arises when firms are only customer-orientated and not competitor-oriented. This research paper further studied the impact of competitor orientation and customer orientation on operational performance of an organization through relationship quality. The objective of this study was to fill the voids and to expand the understanding of 3rd party logistics’ point of view on how competitor and customer orientation impacts on operation performance of an organization. In this research, the theoretical framework indicates a number of variables which includes operational performance as dependent variable, competitor and customer orientation as independent variable and relationship quality, serving as mediator between customer-competitor orientation and operational performance. The sample size taken for this study was 258 and the respondents for this research were the employees of 3rd party logistics provider organizations. One of the reason for selecting employees of 3rd party logistics providing firms is because this study is checking the impact of competitor and customer orientation on operational performance through maintaining relationship quality and employees are the key element in this relationship. With regard to this research paper, the statistical testing includes confirmatory factor analysis to check construct and reliability of this study and the software used for this research were SPSS, AMOS and Excel. This research highlights the key elements and will be beneficial for the 3rd party logistics providers and their organizations as this study would help them in elevating the standards of their operational performances.
Keywords: Competitor orientation, customer orientation, Relationship quality and Operational performance.
Introduction
Overview and Background
In today’s world, logistics, an important part of supply chain, is gradually becoming an essential element of the firms and the reason for this increase in important is due to logistics’ longer and complex involvement with supply chain. (Chopra & Meindl, 2009; Christopher, 2011). Nowadays, companies are trying to improve their service quality and reduce their cost, trying to add value into supply chain and for this purpose they are building collaborative mediums with the other supply chain partners. (Fawcett, Fawcett, Watson, & Magnan, 2012). The collaborative mediums are applicable on the carriers, shippers and logistics services providers and the partnership between companies and logistics services providers helps in promoting the improved performances. This partnership could help in reducing the costs and enhancing the performance of logistics via merged activities and sharing of the information. (Raue & Wieland, 2015).
In the same manner, if supply chain management is not implemented effectively, it can cause inability to deliver value to the customer (Humphries & Wilding, 2004) because companies are in seek to increase globalization and specialization as logistics services are becoming more complex and the firms have to face different and unpredicted events. (Moslemi, Hilmola, & Vilko, 2016). It is also important to explore the relationship between flexibility and supply chain integration from practical and theoretical point of view (Yu, Luo, Feng, & Liu, 2018).
As it was realized long ago that the key elements of profitability, market operations and generation of revenue is logistic excellence and quality of service. (Lun, 208). An essential element of supply chain management includes integration (Huo, 2012) when a company is willing to collaborate with other partners, integration will remain a critical element in terms of service performance. (Zhang & Huo, 2013). However, the depending factors of the relationship between a company and the selected supplier should be evaluated to be aware of the history of a supplier and shipper because the relationship may alter sometimes. (Min, et al., 2005) but with regards to the shipper, collaborative relationships can increase the effectiveness and lessen the inventories between collaborators. (Ellram & Cooper , 1990) Keeping in tabs that immense level of logistics service is putting crucial pressure on logistics services providers (LSPs) to address the issues referring to environmental performance. (Wu, J., & Dunn, 1994). Another crucial aspect of logistics is that operations of logistics requires more fuel burning for transmit of goods from one location to the other, in comparison to the other operations. (Blanco & Cotrill, 2013).
Lately, the public administrations and researchers are trying to concentrate on figuring out the solutions for initiating City logistics as increase in problems are noticed due to freight transportations demand in the city. Logistics Service Providers are trying their best to meet their customer’s requirement as it is a pre-eminent role for shipper. (Christopher, 2011). The progress of integrated logistics systems, which links all the stakeholders together in order to help lessen the impact on citizens is City Logistics responsibility. (De Marco, Cagliano, Mangano, & Perfetti, 2014). In logistics, sustainability, measures of safety and quality efforts will always remain a principal factor (Cantor, Macdonald, & Crum, 2011; Richey, Adams, & Dalela, 2012; Schoenherr, Modi, Talluri, & Hult, 2014). It is believed that social sustainability and environmental related risk management regarding logistics is clearly acknowledged as an essential factor of stable performance of companies operating supply chain which is from scratch material till the customer and there are some speculations on realizing the importance of logistics in sustainability plan of a firm. (Dey, LaGuardia, & Srinivasan, 2011). Another growing aspect of logistics is that the logistics activities are being outsourced by shippers. (Langley Jr, et al., 2014). The shippers are adding more value into their business by using the services provided by 3PL or 3rd Party Logistics that might have not been possible to achieve by the shipper’s themselves. (Deepen, Goldsby, & Knemeyer, 2008). To fulfil the shipper’s demand and requirements, 3rd Party Logistics can coordinate in a way so they can fulfil the requirements of the shippers. One of the way the requirements can be fulfilled is if the 3PL providers combine the loads from the suppliers who are in close quadrants. (Rabinovich, Windle, Dresner, & Corsi, 1999). Recently it has been inquired that how the contributions are made by the 3PL providers to improve the performance of their logistics services to satisfy their customers. (Tian, Ellinger, & Chen , Third-party logistics provider customer orientation and customer firm logistics improvement in China, 2010). It has been acknowledged that the fine practices of logistics are in a continuous process of change which are in collaboration with enhancement of strategy and structure of supply chain. (Bowersox, Closs, Cooper, & Bowersox, 2013). Logistics is believed to have an innovating phenomenon that involves experts of logistics in various responsibilities of supply chain management activities. (Stank, Davis, & Fugate, 2005). Firms are rapidly outsourcing their logistics department/services to Logistics Services Providers, which gives them a window to emphasize on their fundamental proficiency. (Lambert, Emmelhainz, Gardner, & Gardner, 1999; O'Marah & Afghan , 2011). The old and traditional freight forwarding firms and are developing into contemporary logistics providers. The logistic companies are working in a strict quadrant to achieve profitability and competitive advantage in the market as well as excellence. (Murphy & Daley, 2001; Shang & Lu, 2012).
Problem Statement
It is a known fact that nowadays, an increase in outsourcing logistics activity by the shippers can be seen distinctly. Shippers are enhancing their businesses value by outsourcing some of their service activities to 3rd party logistics that may not be possible for a shipper to achieve by himself. (Deepen, Goldsby, & Knemever, 2008). The previous researches identify that 3rd party logistics can handle multiple elements and operational approach to create and increase value of a business. (Marchet, Melacini, Perotti, Sassi, & Tappia, 2017). Another research has worked on the policies of environment and how those policies are worked out in an imploded industry. (Stenberg, Germann, & Klass-Wissing, 2013). But that research paper has not worked on the policies of corporate social responsibilities of logistics service providers.
In another occasion, a study from Mainland China describes a conceptual model that has been reinforced that states how exactly customer orientation contributes in the performance of 3rd party logistics providers in an economy that has started to flourish. And considering the data from China, a positive connection has been found between performance and customer orientation. (Zhaofang, Qiang, & Augustine, Customer orientation, relationship quality, and performances: third party logistics provider's perspective, 2016). But other proportions such as orientation of competitors and integration of cross function were not inscribed in this research.
Following the above-mentioned statement, we are going to proceed the study by finding the impact of competitor orientation and customer orientation on operational performance from the perspective of 3rd party logistics provider. Also, the prior research was conducted in Mainland China and our research will be conducted in Karachi, Pakistan to acquire a deep understanding of the business operations and to test the model in various cultures to compare the differences when the geography of the research will be changed.
Research Objectives
The main objective of this paper is fill the voids and to expand the understanding of 3rd party logistics’ point of view and for that we need to study and understand the impact of competitor orientation, customer orientation on performance through 3rd party logistics perspective. A firm needs constant assessment of the weakness and strengths of their competitor to know what impact competitor orientation has on a firm’s performance. Another purpose for writing this research paper is to assess the effect of customer orientation on the performance of an organization. And also, to understand how customer-oriented business can maintain a positive relationship with their customers that eventually effects the performance level of an organization. Another aspect for analyzing customer orientation is to understand whether high quality and low prices has negative or positive affect on customer orientation.
To evaluate the mediating effect of relationship quality on performance of an organization and to understand how quality can affect the relationship between customer, competitor and performance of the firm, we need to evaluate the pros and cons of an organization. The relationship quality between a firm’s performance and customer or competitor orientation can affect a firm’s success in the long run and this study will explain how this relation can positively affect the customer, competitor and firm’s performance. In logistics, 3rd party logistics firms are developing more and more every day and this study will help in understanding 3rd party logistics’ perspective for a firm’s performance.
Literature Review
Literatures review indicates a number of variables which includes customer orientation (Deshpande, Farley, & Webster, 1993), relationship quality (Zhaofang, Qiang, & Augustine, Customer orientation, relationship qulity and performance: the third party logistics provider's perspective, 2016), competitor orientation (Bendle & Vandenbosch, 2014) and Operational performance (Uhrin, Bruque-Camara, & Moyano-Fuentes, 2017)
Operational Performance:
“Manufacturing process that are faster and more precise with regard to first-time-through quality are so inherently less costly”, says (Shah & Ward, 2003, p. 138). The capability of an organization to manufacture and supply their customers, with goods and services, methodically is called as performance of the operations. (Zhu, Sarkis, & Lai, 2008). Efficiency of an organization is depicted by performance of operations which indicates that firms need to generate profits with restricted resources. (Coelli, Rao, O'Donnell, & Battese).
Operational performance is a dependent variable from a 3rd party logistics service providers point of view. When an organization can deliver the services on time and receives customer’s satisfaction, operational performance tends to increase.
Competitor Orientation
(Narver & Slater, The effect of a market orientation on business profitability, 1990) expressed, “competitor orientation alerts on consideration of the force and weakness of accessible and potential competitors as well as on discovering their approach to adapt into improved ideas to meet the customer satisfaction”. Nowadays, it is important for firms to be competitor oriented and firms should really be aware of the durability and frailty of its competitor. (Narver & Slater, The effect of market orientation on business profitability, 1990). Managers of the firms who are working in competitor-oriented manner needs to be provided with all the relevant data and information regarding their competitor so that they are able to take a decision that could benefit the organizations interest. (SØrensen, 2009).
Competitor orientation is an independent variable that can have an effect on operational performance of an organization if the organization participates in learning about the strengths and weakness of their competitor.
Customer Orientation
According to (Narver & Slater, The effect of a market orientation on business profitability, 1990), customer orientation is “the sufficient understanding of one’s target buyer to be able to create superior value for them continuously”. Also, orientation of customers helps in satisfying the customers need by working on the modern-day marketing techniques and perceptions. (Saxe & Weitz, 1982). and it can also help in maintaining the abiding relationship with the customers (Anderson, 1996)
Customer orientation is another independent variable that impacts the performance of an organization as organizations are based on catering the needs of the customers. Organizations success and failure is dependent on customer’s satisfaction level. This is one of the reason why organizations thrive on customer orientation.
Relationship Quality
According to (Palmatier, Dant, Grewal, & Evans, 2006, p. 138), quality of relationship is explained as “overall assessment of the strength of a relationship, conceptualized as a composite or multidimensional construct capturing the different but related factors of a relationship”. Serving as a bridge, quality of relationship determines the measures and also links the customers to an organization. (Crosby, Evans, & Cowles, 1990)
Relationship quality is a mediating variable that has an effect on operational performance and both the independent variables has impact on operational performance through relationship quality, of an organization. It symbolizes as a bond that exists between a customer/competitor and the business/organization
Relationship Between Variables
Relationship between Competitor Orientation and Operational Performance
It has been shown in the prior research by (Subramanian & Gopalakrishna, 2001) that the organizations that are competitor oriented and involve in competitor-oriented exercises tends to perform better than their competitors and as they know their competitor, it’s easier for them to be proactive in this regard. The organizations who have stronger grip on their competitor orientation will be able to positively determine the direction their competitor’s products are headed and can use that information in their benefit. (Debruyne, Frambach, & Moenaert, 2010).
H1: There is a significant positive correlation between competitor orientation and operational performance.
Relationship between Competitor orientation and Relationship quality
The competitor orientation of an organization shows the importance that is given to their competitor related activities and information analysis. (Lukas & Ferrell, 2000). When a firm has a command on their competitor orientation, they generate the capability to create and retain relationship between their organizations and customers. (Debruyne, Frambach, & Moenaert, 2010)
H2: There is a significant positive correlation between competitor orientation and relationship quality.
Relationship between Customer orientation and Relationship quality
According to (Macintosh, 2007), one of the major element for effective outcome is orientation of the customer. On another occasion, expertise in orientation of the customers also proves to have an affirmative impact on relationship quality. (Crosby, Evans, & Cowles, 1990). A positive relationship has been found in the prior researches between customer orientation and performance of the employee. (Boles, Babin , Brasher, & Brooks, 2001). And (Macintosh, 2007) also stated a positive link among relationship quality and orientation of customer.
H3: There is a significant positive correlation between customer orientation and relationship quality.
Relationship between Relationship quality and Operational Performance
Having a firm quality of relationship between suppliers and the buyers can enhance the performance of operations in supply chain. (Athanasopoulou, 2009). To have smooth-running operational performance, better quality of relationship gives an opinion on how to fill the voids and overcome problems related to operational performance and how to keep the performances up and running. (Roberts, Varki, & Brodie, 2003). According to (Chu & Wang, 2012), a positive connection has been established among performance of finances and quality of relationship. On another occasion, (Wagner & Sutter, 2012) stated that relationship between 3rd party logistics providers and performance is modified when elevated quality of service is provided to the customers.
H4: There is a significant positive correlation between relationship quality and operational performance.
Relationship between Customer Orientation and Operational Performance
Various studies have demonstrated a link between operational performance and orientation of the customers. (Jaworski & Kohli, 1993). With regards to logistics, there is a positive relationship between customer orientation and operational performance (Fugate, Mentzer, & Flint, 2008). Also, it has been a topic of discussion that to have elevated performance of 3rd party logistics providers, customer orientation is very important as it can make ways towards loyalty of a customer and improvement in the services of a 3PL. (Zhaofang, Qiang, & Augustine , Customer orientation, relationship quality and performance: the third party logistics provider's perspective, 2016).
In addition to the study presented by (Tian, Ellinger, & Chen, Third-party logistics provider customer orientation and customer firm logistics improvement in China, 2010), it is proposed that orientation of the customer may add into the operational performance of a 3rd party logistics provider.
H5: There is a significant positive correlation between customer orientation and operational performance.
Effect of Relationship quality (mediator) on the relation of Competitor orientation and Operational performance
For an organization, having strong knowledge of their competitors is beneficial as it gives un-duly understanding on what their competitors are doing (Debruyne, Frambach, & Moenaert, 2010) and how realizing those activities helps 3rd-Party Logistics providers to succeed in satisfying their customers and achieving excellent operational performance because relationship quality with customers would impact positively on operational performance. The firms that are able to preserve the behavior of competitor orientation can assure a constant growing position in the challenging market, that encounters a positive relationship in terms of operational performance. (Day & Wensley, 1988). Also, the level of the performance will be elevated as these firms have already captured the competitor-related activities to provide the customers with the best services (SØrensen, 2009)
H6: Relationship quality mediates the link among competitor orientation and operational performance.
Effect of Relationship quality (mediator) on the relation of Customer orientation and Operational Performance
One of the reason why customers stay true to their selected logistics providers is because the long-term relation can gain equivalent benefit from the suppliers. (Yongtao, Qin, Qiang , & Tieshan, 2012) which leads to elevated operational performance. With regard to the present situation, the through communication among the consumers/customers and the 3rd party logistics providers have strengthened the bondage through relationship quality (acting as a mediator) of operational performance and orientation of the customers for the organizations that deals in logistics management. (Zhaofang, Qiang, & Augustine, 2016)
H7: Relationship quality mediated the link among customer orientation and operational performance.
Methodology
Data collecting method
The method through which data has been collected for this research paper was both offline and online. Respondents that were targeted for this research paper were the employees of 3RD Party Logistics service, based in Karachi, Pakistan. The reason for selecting these respondents was because of their link with the 3RD Party Logistics service as they are familiar with the management of customer and competitor relationship. Another reason these employees were elected was based on their experience with the firm. This survey was conducted by both google docs and visiting the 3PL firms in person. A letter was issued from our institute pertaining the request to visit the 3PL firms to explain the purpose of this research that is a deep understanding on the impact of orientation of competitor and orientation of the customer on performance of the operations of any firm, which proved to be an effective as most of the employees understood the concept of the research and filled out the survey conveniently. One issue that arose with the data was that some of the online respondents did not understood the concept of this research paper which led to the incorrect filling of the survey. This created biasness with the results of this research paper.
Sampling
The sample size of the respondent for this study was a minimum of 258. As mentioned before the respondents were the employees of 3rd Party Logistics firms, basing on their experience level with regard to orientation of the customer and orientation of the competitor and their impact on the performance of operations. A total of 300 questionnaires were sent out via google docs link and by visiting the 3rd party logistics organizations/companies/firms. The employees were at both temporary and permanent positions in the 3rd party logistics firms. The focus was more on the employees who are affiliated with the firm for more than 6 months as they are fairly experienced in understanding the relation between customer orientation, competitor orientation and operational performance. Out of 300, 272 questionnaires were completed and collected for further processing. 28 responses were not received by us as they were not filled out by the respondents. 272 questionnaires that were received, was then moved on for further scrutiny to figure out if all the questions stated in the questionnaire were filled out or of some of the responses of the questions were missing from the questionnaire. The questionnaires with missing questions were rejected as they create misleading results. The remaining 258 questionnaires were accepted as they fulfilled all the criteria needed for this research.
Statistical Techniques
The approach used for Structural Equation Modeling (SEM) is a Two-Way approach which includes Measurement model and Structural model.
Measurement Model
In measurement model, we performed construct reliability and validity test via Cronbach alpha (using SPSS) to check the reliability and validity of the variables for this research study.
Structural Model
In structural model, model fitness test and hypothesis testing was performed. Hypotheses were analyzed via SEM, which has been proved to be an effective method to assess the data which has variety of variables. Also, the software used to test model fitness and CFA (confirmatory factor analysis) was AMOS and construct reliability & validity test was conducted through the use of SPSS. Microsoft excel was also used in order to give AMOS and SPSS their base file and to compile the data with regard to the instrument.
Result Analysis
Demographics Statistics
Gender
|
Gender |
|||||
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
|
Valid |
Male |
161 |
62.4 |
62.4 |
62.4 |
|
Female |
97 |
37.6 |
37.6 |
100.0 |
|
|
Total |
258 |
100.0 |
100.0 |
|
|
The data for this research study was collected from 3rd party logistics companies. Out of 258 respondents, 161 were male and 97 were female. The ratio of male is 62.4% and ratio of female have 37.6%. But this part of demographics is not much focused as it is not relevant to the result of the research.
Income
|
Income |
|||||
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
|
Valid |
10,000 - 20,000 |
34 |
13.2 |
13.2 |
13.2 |
|
21,000 - 30,000 |
58 |
22.5 |
22.5 |
35.7 |
|
|
31,000 - 40,000 |
25 |
9.7 |
9.7 |
45.3 |
|
|
41,000 - 50,000 |
67 |
26.0 |
26.0 |
71.3 |
|
|
51,000 - 60,000 |
8 |
3.1 |
3.1 |
74.4 |
|
|
Other |
66 |
25.6 |
25.6 |
100.0 |
|
|
Total |
258 |
100.0 |
100.0 |
|
|
The respondents we collected data from, were the employees of 3rd party logistics companies. The income level of 67 i.e. 26%respondents was from 40,000 to 50,000 but yet again this part of demographic is not focused as it is not relevant to the result of the research.
Qualification
|
Qualification |
|||||
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
|
Valid |
Intermediate |
17 |
6.6 |
6.6 |
6.6 |
|
Bachelors |
135 |
52.3 |
52.3 |
58.9 |
|
|
Masters |
59 |
22.9 |
22.9 |
81.8 |
|
|
Diploma Certificate |
35 |
13.6 |
13.6 |
95.3 |
|
|
Other |
12 |
4.7 |
4.7 |
100.0 |
|
|
Total |
258 |
100.0 |
100.0 |
|
|
Out of 258 people, 135 i.e. 52.3%, respondents had bachelor’s degree, 59 respondents i.e. 22.9% had master’s degree and 35 respondents i.e. 13.6% employees have done diploma in the relevant field which means the data has been collected from qualified respondents and the chances of biasness were less.
Work Experience
|
Work Experience |
|||||
|
|
Frequency |
Percent |
Valid Percent |
Cumulative Percent |
|
|
Valid |
More than 6 months |
40 |
15.5 |
15.5 |
15.5 |
|
1-2 years |
54 |
20.9 |
20.9 |
36.4 |
|
|
3-4 years |
54 |
20.9 |
20.9 |
57.4 |
|
|
5-6 years |
102 |
39.5 |
39.5 |
96.9 |
|
|
Above 7 years |
8 |
3.1 |
3.1 |
100.0 |
|
|
Total |
258 |
100.0 |
100.0 |
|
|
The experience of 102 respondents i.e. 39.5% was of 5 to 6 years’ working in 3rd party logistics companies which seems sufficient considering an employee needs to have at least 6 months or above experience to understand how to approach competitor and customer orientation to increase relation quality in order to achieve operational performance.
Confirmatory Factor Analysis (CFA)
The results shown in the table below states that factor loading values are above 0.6 which is a sign that the questions of this research study were accurate. Cronbach’s Alpha values appears to be more than 0.7 which shows that the questionnaires’ internal consistency to predict the results is better. Whereas, CR (Composite Reliability) values are also above 0.7 which shows accurateness of the data. AVE (Average Variance Extracted) values are above 0.50.
|
Construct/Indicators
|
Standardized Factor Loading (CFA-AMOS) |
Construct Reliably |
Construct Validity |
|
|
Cronbach’s alpha |
Composite Reliability (CR) |
Convergent Validity |
||
|
Average Variance Extracted (AVE) |
||||
|
COMPETITOR ORIENTATION (C) |
.926 |
0.927 |
0.681 |
|
|
CO1 |
.90 |
|||
|
CO2 |
.91 |
|||
|
CO3 |
.86 |
|||
|
CO4 |
.82 |
|||
|
CO5 |
.72 |
|||
|
CO6 |
.72 |
|||
|
CUSTOMER ORIENTATION (CUO) |
.887 |
0.887 |
0.568 |
|
|
CU1 |
.74 |
|||
|
CU2 |
.79 |
|||
|
CU3 |
.79 |
|||
|
CU4 |
.74 |
|||
|
CU5 |
.73 |
|||
|
CU6 |
.73 |
|||
|
RELATIONSHIP (RE) |
.856
|
0.858 |
0.548 |
|
|
R1 |
.72 |
|||
|
R2 |
.71 |
|||
|
R3 |
.66 |
|||
|
R4 |
.80 |
|||
|
R5 |
.80 |
|||
|
OPERATIONAL PERFORMANCE (OPP) |
.880 |
0.881 |
0.553 |
|
|
OP1 |
.67 |
|||
|
OP2 |
.71 |
|||
|
OP3 |
.72 |
|||
|
OP4 |
.81 |
|||
|
OP5 |
.80 |
|||
|
OP6 |
.74 |
|||
|
Reliability and Construct Validity Thresholds: [Suggested by Fornell and Larcker (1981)] |
α > 0.70 (Nunnaly,1967) |
CR > 0.70 |
i) AVE > 0.50 ii) CR > AVE |
|
Model fit
In order to measure the model there are some standards or mark set. This study has taken seven indices which are Chi-square/df, P. Value, Goodness-of-Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index, Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA). The value of all the indices except for P-Value did not match the threshold. After modification, values almost reached the threshold but the value of GFI and AGFI has improved but is still lower than the threshold.
|
Chi- square/df |
P-Value |
GFI |
AGFI |
CFI |
TLI |
RMSEA |
|
3.040 |
.000 |
.796 |
.751 |
.881 |
.866 |
.091 |
Modification Indices
Model fitness after modification
|
Chi- square/df |
P-Value |
GFI |
AGFI |
CFI |
TLI |
RMSEA |
|
2.377 |
.000 |
.849 |
.803 |
.929 |
.916 |
0.75 |
Hypothesis Significant
|
DESCRIPTION |
R2 |
β |
P-Value |
|
|
.875 |
.372 |
.003 |
|
|
.505 |
.001 |
|
|
|
.459 |
.002 |
|
|
|
.376 |
.040 |
|
|
|
.265 |
.048 |
|
|
|
.1406 |
.028 |
|
|
|
.0988 |
.024 |
(C= Competitor Orientation, CUO= Customer Orientation, RE= Relation Quality, OPP= Operational Performance).
The above table shows a direct and positive relationship between competitor orientation and operational performance as its (beta= .372 and P-Value = .003) which means its hypothesis is significant. Another direct relationship is found between competitor orientation and relationship quality with (beta = .505 and P- Value = .001). Direct relationship between customer orientation and relationship quality is found to be (beta = .459 and P-Value = .002) which is again indicating significant hypothesis. Direct relationship between relationship quality and operational performance is found to be (beta = .376 and P- Value = .040). Direct relationship between customer orientation and operational performance is found to be (beta = .265 and P-Value = .048). the indirect relationship found between competitor orientation and operational performance which mediates through relationship quality has (beta = .1406 and P- Value = .028) which indicates significant hypothesis. Additionally, another indirect relationship between customer orientation and operational performance which mediates through relationship quality is found to be (beta= .0988 and P-Value = .024) which indicates significant hypothesis.
Hypothesis testing using mediation analysis
Two Tailed Tests: Indirect Effect
For testing mediation, the Independent variables are Competitor Orientation and Customer Orientation. The mediator is Relation Quality and the dependent variable is Operational Performance.
The indirect effect of two relations i.e. OPP – RE – C and OPP – RE – CUO is .028 and .024 respectively which is less than 0.05 which means this hypothesis is significant, therefore the test is accepted.
Two Tailed Tests: Direct Effect
Whereas for direct relations, i.e. OPP – RE, OPP – CUO, OPP – C, RE – C, RE – CUO also has significant relationship as their P values are .040, .048, .003, .001 and .002 respectively which are less than 0.05. Thus, this model shows that there is partial mediation present as both direct and indirect relations are significant. And as both effects are significant, all the hypothesis are accepted.
Hypothesis Assessments.
|
Hypothesis |
Accepted/Rejected |
|
H1: There is a significant positive correlation between competitor orientation and operational performance. |
Accepted |
|
H2: There is a significant positive correlation between competitor orientation and relationship quality. |
Accepted |
|
H3: There is a significant positive correlation between customer orientation and relationship quality. |
Accepted |
|
H4: There is a significant positive correlation between relationship quality and operational performance. ` |
Accepted |
|
H5: There is a significant positive correlation between customer orientation and operational performance. |
Accepted |
|
H6: Relationship quality mediates the link among competitor orientation and operational performance |
Accepted |
|
H7: Relationship quality mediated the link among customer orientation and operational performance |
Accepted |
Conclusion and Discussion
This research study determines the impact of competitor and customer orientation on operational performance having relationship quality as a mediator. A conceptual framework was developed to acquire knowledge that whether using competitor and customer orientation approach has a positive effect on operational performance of 3rd party logistics companies or not. And after using the survey data from 3rd party logistics companies’ employees, it has been found that there is positive connection between competitor/customer orientation and operational performance of 3PL companies. thus, positive direct and indirect effect of competitor and customer orientation on operational performance. The findings prove that when a 3rd party logistics company is competitor oriented and customer oriented, by having better relations with both the parties, operational performance of the company is enhanced.
Limitation and Recommendation
There were few limitations for this research study that the researchers had to face. First limitation was lack of time resource and financial resources. If we would have more time and financial resources, the sample size would be greater than 258. Another limitation is that this study was conducted in Karachi, Pakistan so the future researchers can explore other cities of Pakistan to expand the course of this study. This study examines the if there is positive impact of competitor orientation and customer orientation on operational performance of 3rd party logistics companies. The future researchers can add variables such as cross-functional integration or on the policies of corporate social responsibilities of logistics service providers.
Anderson, R. (1996, Fall). Personal selling ans sales management in the new millennium. Journal of Personal Sellings and Sales Management, 16, 17-32.
Athanasopoulou, P. (2009). Relationship quality: a critical literature review and research agenda. European Journal of Marketing, 43, 583-610.
Bendle, N., & Vandenbosch, M. (2014). Competitor orientation and the evolution of business markets. Marketing Science.
Blanco, E., & Cotrill, K. (2013). Delivering on the promise of green logistics. MIT Sloan Management Review, 1-6.
Boles, J., Babin , B., Brasher, T., & Brooks, C. (2001). An examination of the relationships between retail work environments, salesperson selling orientation-customer orientation and job performance. Journal of Marketing Theory and Practice, 9, 1-13.
Bowersox, D., Closs, D., Cooper, M., & Bowersox, J. (2013). Supply Chain Logistics Management 4th ed. McGraw-Hill Higher Education, New York, NY.
Cantor, D., Macdonald, J., & Crum, M. (2011). The influence of workplace Justice perceptions on commercial driver turnover intensions. Journal of Business Logistics, 32(3), 274-86.
Chang, T., & Chen , S. (1998). Market orientation, service quality and business profitability: a conceptual model and empirical evidence. Journal of service marketing, 12, 246-264.
Chopra, S., & Meindl, P. (2009). Supply Chain Managment. Prentice Hall International .
Christopher, M. (2011). Logistics and supply chain management . FT press.
Chu, Z., & Wang, Q. (2012). Drivers of relationship quality in logistics outsourcing in China. Journal of Supply Chain Management, 48, 78-96.
Chung, H. (2011). Market orientation, guanxi and business performance. Industrial marekting management, 40, 522-533.
Coelli, T. J., Rao, D. S., O'Donnell, C. J., & Battese, G. E. (n.d.). An introduction to efficiency and productivity. Springer, US.
Crosby, L. A., Evans, K. R., & Cowles, D. (1990). "Relationship quality in services selling: an interpersonal influence perspective". Journal of Marketing, 54(3), 68-82.
Day, G. S., & Wensley, R. (1988). Assessing advantage: a framewrok for diagnosing competitive superiority. Journal of Marketing, 16(1), 1-20.
De Marco, A., Cagliano, A., Mangano, G., & Perfetti, F. (2014). Factor infuencing logistics service providers efficiency in urban distribution systems. Transportation Research Procedia, 3, 499-507.
Debruyne, M., Frambach, R. T., & Moenaert, R. (2010). Using the weapons you have: the role of resources and competitor orientation as enablers and inhibitors of competitive reaction to new products. Journal of product innovation management, 27, 161-178.
Deepen, J. M., Goldsby, T. J., & Knemever, A. M. (2008). Beyond expectations: an examination of logistics outsourcing goal achievement and goal exceedance. Journal of business logistics, 29(2), 75-105.
Deepen, J., Goldsby, T., & Knemeyer, A. (2008). Beyond expectations: an examination of logistics outsourcing goal achievement and goal exceedance. Journal of Business Logistics, 29(2), 75-105.
Deshpande, R., Farley, J. U., & Webster, F. E. (1993). Corporate culture, customer orienation and innovativeness in Japanese firms: A quadrad analysis. Journal of Marketing, 57(1), 23-27.
Dey, A., LaGuardia, P., & Srinivasan, M. (2011). Building sustainability in logistics operations: A research agenda. Management of research review, 34(11), 1237-1259.
Ellram, L., & Cooper , M. (1990). Supply chain management, partnership and the shipper- third party relationship. The International Journal of Logistics Management, 1(2), 1-10.
Fawcett, S., Fawcett, A., Watson, B., & Magnan, G. (2012). Peeking inside the black box: toward and understanding of supply chain coolabration dynamics. Journal of Supply Chain, 48, 44-72.
Fugate, B., Mentzer, J., & Flint, D. (2008). The role of logistics in market orientation. Journal of Business Logistics, 29, 1-26.
Humphries, A., & Wilding, R. (2004). Long term collaborative relationships: the impact of trust and C3 Behaviour. Journal of Marketing Management, 20(9-10), 1107-1122.
Huo, B. (2012). The impact of supply chain integration on company performance: An organizational capability perspective. Supply Chain Management: An International Journal, 17(6), 596-610.
Jaworski, B., & Kohli, A. (1993). Market Orienattion antecedents and consequences. Journal of Marketing, 57, 53-70.
Lambert, D., Emmelhainz, M., Gardner, J., & Gardner, E. (1999). Building successful logistics partnerships. Journal of Business Logistics, 20(1), 165-181.
Langley Jr, C. J., Albright, D., Wilcox, S., Hadhazy, M., Zieciak, M., Sanger, S., . . . O'Reilly, K. (2014). 2014 third-party logistics study- The state of logistics outsourcing report. Capgemini Consulting.
Lukas, B., & Ferrell, O. (2000). The effect of market orientaion on product innovation. Journal of the Academy of Marketing Science, 28(2), 239-47.
Lun, Y. (208). Adoption of EC by logistics service providers: Adoption of EC by logistics service providers in Hong Kong. VDM, Saarbruken.
Macintosh, G. (2007). Customer orientation, relationship quality and relational benefits to the firm. Journal of Service Marketing, 21(3), 150-159.
Marchet, G., Melacini, M., Perotti, S., Sassi, C., & Tappia, E. (2017). Value creation models in the 3PL industry: what 3PL providers do to cope with shippers requirement. International Journal of Physical Distribution and Logistics Management, 47(6).
Min, S., Roath, A. S., Daugherty, P. J., Genchev, S. E., Chen, H., Arndt, A. D., & Richey, G. R. (2005). Supply chain collaboration: what is happening? International Journal of Logistics Management, 16(2), 237-256.
Moslemi, A., Hilmola, O., & Vilko, J. (2016). Risks in emerging markets: logistics services in the mediterranean region. Martime Business Review, 1(3), 253-272.
Murphy, P., & Daley, J. (2001). Profiling international freight forwarders: an update. International Journal of Physical Distribution and Logistics Management, 31(3), 152-168.
Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of marketing, 54, 20-35.
O'Marah, K., & Afghan , F. (2011). Value chain ecosystems of the future the role of outsourcing in supply chain strategy.
Palmatier, R. W., Dant, R. P., Grewal, D., & Evans, K. (2006). Factors influencing the effectiveness of relationship marketing: a meta analysis. Journal of Marketing, 70(4), 136-53.
Rabinovich, E., Windle, R., Dresner, M., & Corsi, T. (1999). Outsourcing of intergrated logistics functions: an examination of industry practices. International Journal of Physical Distribution and Logistics Management, 29(6), 353-373.
Raue, J. S., & Wieland, A. (2015). The interplay of different types of governance in horizontal cooperations: A view on logistics service providers. International Journal of Logistics Managemenr, 26, 401-423.
Richey, R., Adams, F., & Dalela, V. (2012). Technology and Flexibility: Enablers of collobration and time based logistics quality. Journal of Business Logistics, 33(1), 34-49.
Roberts, K., Varki, S., & Brodie, R. (2003). Measuring the quality of relationships in consumer services: an empirical study. European Journal of Marketing, 37(1/2), 160-96.
Saxe, R., & Weitz, B. (1982, August). The SOCO Scale: a measure of the customer orientation of sales people. Journal of Marketing Research, 19, 343-51.
Schoenherr, T., Modi, S., Talluri, S., & Hult, G. (2014). Antecedents and performance outcomes of strategic environmental sourcing: An investigation of resource-vased process and contigency effects. Journal of Business Logistics, 35(3), 172-90.
Shah, R., & Ward, P. T. (2003). Lean manufacturing: context, practice bundles, and performance. Journal of operational management, 21, 129-149.
Shang, K., & Lu, C. (2012). Customer relationship management and firm performance: an empirical study of freight forwader service. Journal of Marine science and technology, 20, 64-72.
SØrensen, H. E. (2009). Why competitors matter for market orientation. European Journal of Marketing, 43(5/6), 735-761.
Stank, T., Davis, B., & Fugate, B. (2005). A strategic framework fro supply chain oriented logistics. Journal of Business Logistics, 26(2), 27-46.
Stenberg, H., Germann, T., & Klass-Wissing, T. (2013). Who controls the fleet? Initisal insights into the efficiency of road freight transport planning and control from an industrial network perspective. International journal of logistics: research and applications, 16(6), 493-305.
Subramanian, R., & Gopalakrishna, P. (2001). The market orientation-performance relationship in the context of a developing economy: an empirical analysis. Journal of Business Research, 53(1), 1-13.
Tian, Y., Ellinger, A. E., & Chen, H. (2010). Third-party logistics provider customer orientation and customer firm logistics improvement in China. International Journal of Physical Distribution and logistics management, 40, 356-376.
Uhrin, A., Bruque-Camara, S., & Moyano-Fuentes, J. (2017). Lean production, workforce development and operation performance. Management Decision, 55(1).
Wagner, S. M., & Sutter, R. (2012). A qualitative investigation of innovation between third-party logistics providers and customers. International Journl of Production Economics, 140, 944-958.
Wu, H., J., & Dunn, S. C. (1994). Environmentally responisble logistics system. International Journal of Physical Distribution and Logistics Management, 25(2), 20-38.
Yongtao, S., Qin, S., Qiang , L., & Tieshan, W. (2012). Impact of business relationship functions on relationship quality and buyer's performance. Journal of Business and Industrial Marketing, 27(4), 286-298.
Yu, K., Luo, N., Feng, X., & Liu, J. (2018). Supply chain information integration, flexibility, and operational performance: an archival search and content analysis. International Journal of Logistics Management, 29(1), 340-364.
Zhang, M., & Huo, B. (2013). The impact of dependence and trust on supply chain integration. International Journal of Physical Distribution and Logistics Management, 43(7), 544-563.
Zhaofang, C., Qiang, W., & Augustine , A. L. (2016). Customer orientation, relationship quality and performance: the third party logistics provider's perspective. The international journal of logistics management, 27(3), 738-754.
Zhaofang, C., Qiang, W., & Augustine, A. L. (2016). Customer orientation, relationship quality, and performances: third party logistics provider's perspective. The international journal of logistics management, 27(3), 738-754.
Zhaofang, C., Qiang, W., & Augustine, A. L. (2016). Customer orientation, relationship qulity and performance: the third party logistics provider's perspective. The international journal of logistics management, 27(3), 738-754.
Zhu, Q., Sarkis, J., & Lai, K. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International journal of production economics, 111(2), 261-273.
