Muhammad Noman Shafique, Dongbei University of Finance and Economics, China. Email: shafique.nouman@gmail.com
Alireza Nasiri, Surrey International Institute (University of
Surrey DUFE Campus), China. Email: anasiri@ut.ac.ir
Dr. Haji Rahman, Preston University Islamabad Campus.Email: haji616@yahoo.com
Hussain Ahmad, Federal Urdu University of Arts Science &
Technology, Islamabad. Email: hussainahmad251977@gmail.com
Abstract. Distribution
concept was the origin of marketing. Every organization has realized that they
can enhance their performance through strengthen their network channels and
through the adaptation of new, Radio-frequency identification
(RFID), technology. In this study, the relationship between network channel and
organizational performance has been established. RFID
technology is focused to strengthen network channel to gain competitive
advantage, which will result to enhance organizational performance. The nature of this
study is correlation based on deductive approach and quantitative
nature through survey method based on the adoptive questionnaire. The
population of this study is retail industry in China. The sample size is 100 with
random sampling technique is used. The results from this
study show that network channel affect organizational performance while the competition plays the mediating effect and radio-frequency identification
technology play the
moderated effect on the relationship between network channel and organizational performance. This study will improve organizational
performance in
retail industry and will reduce the cost of network channel, which will result
to increase organizational performance.
Key words: Network
channel, Accessibility of location, Information, Competition, Radio frequency
identification (RFID), Performance
Introduction
Globalization boosted the technology in all over the world. It
revolves around organizational processes, customer’s behaviors, competition
intensity and innovation to increase the efficiency in every field. Today, the
battle of customer acquisition, retention and loyalty is the biggest issue in
every organization due to hyper competition; electronic distribution and rapid
information transformation create a tough situation for the survival of every
organization. The war wining situation is the only guarantee to sustain them in
the market (Betancourt,
Chocarro, Cortiñas, Elorz, & Mugica, 2017; Tokman
et al., 2011).
In recent years, many
manufacturers have not the capability for direct marketing. They are not able
to supply their products to their customers that is why the move towards the
brokers of distribution channel. Even if they have sufficient financial
facilities, use of these facilities in the main profession has more efficiency;
therefore, advantage of using distribution channel is obvious (Kotler
& Armstrong, 2010). On the other hand, according to
marketing experts, distribution channel plays the important role in
organizational performance. Because if organization has their own distribution
channel, then they can satisfy their customers and reduce distribution cost (Haghighinasab,
Ebrahimi, Sattari, & Roghanian, 2013).
The network channel has not
only the distribution of products from manufacturer to customers. It has many
other advantages like the interaction between customers and manufacturer, time
saving, cost reduction, and develops the relationship between manufacturer and
customers. In the literature of marketing network channels have specially
highlighted the importance of customers and manufacturer relationship because
marketing experts knows that organizations can sustain their customers only if
they have strong relationship with their customers otherwise competitors
acquire their customers (Skarmeas,
Katsikeas, Spyropoulou, & Salehi-Sangari, 2008).
Marketing
network channel in retail industry has been distributed in many categories in
marketing literature. Five most important network categories which are using in
both online and offline retailing are accessibility of location, information,
assortment, assurance of product delivery and ambiance are cited in literature (Kopalle et al., 2009).
However, in this study only three of them categories have been focused. The
focused dimensions of network channel are accessibility of location,
information and assurance of delivery of products.
Marketing network channel getting more importance because the
network channel will cause to save the cost. In retail, cost is very important.
Different studies related to network channel has analyzed the cost function (Betancourt, 2004).
Furthermore, network studies have to develop the relationship of cost and
retailer; household and consumer demands are major consideration in network
channel studies (Betancourt, 2004).
The ultimate goal of the network channel is to reduce cost and increase
customers, retailer and household demand. The accessibility of location is
equally important for sensory and non-sensory goods to enhance economic performance
in marketing channels (Betancourt, Chocarro, Cortiñas, Elorz, &
Mugica, 2016; Bucklin, 1966; Keh, 1997).
Information
is playing the most important role in product purchasing decision. The
purchasing decision of sensory and no sensory products are entirely different
from each other. Sensory products are those products that can be analyzed
through the basic human senses. These products can be smelled, touched and
taste. Customers want to physically see these products before to purchase. So,
these products require totally different information as compared to non-sensory
products. People do not too much caring to physically see these products before
to purchase. So, they require the different type of information during the
purchasing decision of online and offline products (Betancourt et al., 2017).
Organizations
should ensure their product delivery in online market channels. On-line
purchasing took long time as compared to offline purchasing because it will
require delivery time. Customers must have to be wait for a long time while in
offline purchasing, customer can get products on real time. So, organizations
must consider time, delivery and product handling factors during planning their
network channel development for online purchasing (Bansal, McDougall, Dikolli, & Sedatole, 2004; Betancourt et al., 2016). Assurance of product delivery can enhance customer
satisfaction, which will result from economic and operational performance of
organizations. So, the assurance of product delivery is considered the most
important dimension of network channel (Finn et al., 2009; Hung et al., 2014; Jaiswal, Niraj, & Venugopal, 2010; Kim et al., 2009).
Radio frequency identification
technology was evolved from electronic product code. This technology is used in
supply chain management to increase the efficiency and effectiveness of network
channel work in organizations to enhance their performance(Shister,
2005). Radio frequency identification
technology is the general in nature so this technology can be used in every
industry and sector it is not specific with any organization. This unique
feature of radio frequency identification technology gave the boost in supply
chains equally important in all sectors (Shister,
2005).
Radio frequency identification
technology minimized human interaction because this technology does not require
the direct connection for operation like the traditional bar system (Dargan,
Johnson, Panchalingam, & Stratis, 2004). Furthermore, RFID tags operated very
fast they can respond in milliseconds. These tags can be readable virtually,
and they cannot be effected through weather conditions. There are a lot of
other advantages, in this technology product can be real time traced at any
location along the supply chain channel. Through this technology, products can
communicate with each other. Furthermore, this technology enabled to handle
inventory, even products can inform to replacement of products on their shelves
(Dargan
et al., 2004).
Competition is situation when
organization feels someone other is offering the same products what they are
offering. In the same manner, the competition intensity is the presence of
numerous competitors in the same market. Every firm tries to achieve the
competitive advantage which will reduce the growth opportunities for other
organizations (Auh
& Menguc, 2005). Competition intensity increased the
social corporate responsibilities among organizations. In high competitive
environment, organizations follow more corporate social responsibilities, and
they provide more friendly services with care and hospitality to their
customers (Zahra
& Covin, 1995).
High competitive environment
will boost organizational performance. In this situation, customers have free
choice to change organization. This reality will result as highly customer’s
satisfaction and loyalty, which will lead to frequent sales and economic
performance. So, the competition intensity is good for both organizations as
well as customers, and both can enjoy high performance (Chan,
He, Chan, & Wang, 2012).
Organizational performance was
categorized into two major parts. The first is financial performance, which can
be measured through profit and sales growth. On the other hand, non-financial
factors can also be used to measure organizational performance. It is further
divided into two major categories. The first is internal non-financial
performance. It is based on the internal organizational performance factors
like growth in productivity, efficiency in internal process or technological
innovation. While the second is external non-financial performance factors it
is based on external factors like customer satisfaction, customer loyalty and
customer or supplier relationship management (Schoviah,
2012; Swanson
& Ramiller, 2004).
Unified Theory of Acceptance and Use of Technology
(UTAUT)
The
unified theory of acceptance and use of technology (UTAUT) focuses on the
acceptance, adoption and implementation of technology in organization. The main
purpose of this theory is to educate people about technology and inform them
the use of technology. Furthermore, inform them about the advantages of the use
of technology. This information will effect on the behaviors of people and
enhance their intention in the implementation of technology. This theory is
based on four major constructs. The first construct is performance expectancy.
The second construct is effort expectancy. Third is social influence and fourth
is facilitating conditions. All constructs showed that the implementation of
technology will facilitate them in their work and enhance their performance (Venkatesh,
Thong, & Xu, 2016; Venkatesh & Zhang, 2010).
In
this study radio-frequency identification, technology is focused as the
moderating variable in this study. The unified theory of acceptance and use of
technology will support this variable. This study aims at developing awareness
about RFID technology in organizations. The subject technology is environment
friendly and that’s why organizations and society will adopt this technology.
By adopting this technology organizations are expected to enhance their
performance.
Conceptual Framework
Based on in-depth literature
review and theoretical frame work, following conceptual framework for study has
been developed.
RFID Technology Competition Organizational Performance Network Channel Assurance of
Product Delivery Accessibility of
Location Information
Figure 1. Conceptual
framework
Hypotheses
Based on the conceptual
framework, following hypotheses have been developed.
H1:
Network Channel has the positive
impact on organizational performance.
H2:
Competition plays the mediating role
between network Channel and organizational performance.
H3:
Radio frequency identification
technology plays the moderating role between network Channel and organizational
performance.
Methodology
Methodology
plays a vital role to conduct the study. It will describe the whole process and
activities related to studying. The nature of current study is quantitative in
nature. Because in this study quantitative techniques will be used to analyze
data. All variables have the relationship with each other, which can be tested
through statistical analysis. Furthermore, deductive research approach is used
in this study because theories have been tested through data collection in this
study. The population of this study is retail industry in China. Sample is the
subset of population. In this study, three organizations should be taken as the
sample. Sample will be collected through random sampling technique. The sample
size will be 100 employees from Wall Marts. For data collection survey method,
will be used based on the adoptive questionnaires from previous studies. The items
regarding network channel based on accessibility of location, information and
assurance of product delivery (Betancourt
et al., 2017), items for RFID Technology (Tokman
et al., 2011), items regarding competition and organizational
performance (Chan et
al., 2012), have been adopted from previous studies. Furthermore,
data will be analyzed through different statistical tests by using SPSS
software. Then their results will be interpreted by using MS Word.
Data Analysis and Results
Data
have been analyzed through different statistical tests. First of all, the
reliability of data has been tested through Cronbach Alpha test. If data is
reliable and the values of reliability is greater than 0.6, then this data
meets the minimum reliability value for further statistical tests and analysis (Sekaran
& Bougie, 2013). After finding the
reliability, mean, standard deviation and correlation of variables have been
tested and results have been interpreted in the following table.
Table
1 Means, Standard Deviations, Correlations, and Reliabilities (N=76)
|
Mean |
S.D |
N.C |
RFID |
Comp. |
OP |
Network
Channel (N.C) |
3.12 |
1.02 |
(.94) |
|||
Radio
frequency identification |
2.86 |
1.02 |
0.76** |
(.89) |
||
Competition |
2.84 |
0.92 |
0.81** |
0.90** |
(0.88) |
|
Organizational Performance (OP)
|
2.69 |
0.93 |
0.67** |
0.71** |
0.78** |
(0.81) |
Note. **. Correlation is significant at
the 0.01 level (2-tailed).
Reliability estimates in parentheses.
The
mean values are the central tendency of respondents. In the above table mean
value of research variables have been analyzed. The values in the table showed
respondents have given the responses towards the neutral or agree behavior.
While the standard deviation value shows the deviation from the mean point. The
values of standard deviation of research variables are close to zero. It means
most of the respondents have the tendency towards central or mean value. The
correlation values show the correlation between research variables with each
other. In the above table, the values showed positive correlation with all
other research variables at the highly significant level. While the data
reliability is shown in parentheses, and the value of Cronbach Alpha is greater
than 0.6. So, data fulfill the requirements of reliability for further
analysis.
Regression
analysis shows the regressive effect of independent variable on dependent
variable. The following table shows the regression results between network
channel and organizational performance.
Table 2 Regression
between Network Channel and Organizational Performance (N= 76)
Model |
R2 |
β |
t |
Sig. |
Network Channel |
0.450 |
0.671 |
7.784 |
0.000 |
Note. Dependent Variable:
Organizational Performance |
Moderated regression shows the moderated
effect between the independent and dependent variables. In the following table
network, channel is taken as independent variable, organizational performance
is taken as dependent variable and radio frequency identification is taken as
moderated variable. The results of moderated regression have been interpreted
in the following table.
Table 3 Moderated
Regression among Network Channel, RFID and Organizational Performance (N= 76)
Model |
R2 |
β |
t |
Sig. |
Network Channel |
0.45 |
0.67 |
7.78 |
0.00 |
Interaction (NC * RFID) |
0.52 |
0.68 |
3.33 |
0.00 |
Note. Dependent Variable:
Organizational Performance |
In
the moderated regression, first the direct effect of independent variable on
dependent variable has been analyzed. Then in second model the indirect effect
through moderated variable has been analyzed. It is calculated through the
interaction term by multiplying independent variable and moderated variable.
The change in both models shows the moderated effect of on dependent variable.
In the above table, the value of R2 has changed from 0.450 to 0.523, which
shows that the effect of moderated variable enhances the effect on performance.
The values of β show standardized coefficient value. In the above table,
the β values change from 0.671 to 0.683. The value of t is also changed
from 7.784 to 3.332 at the highly significant level these values proved
moderated effect.
Mediation
effect between the independent and dependent variables can be analyzed through
two steps the first step is to calculate the regression effect (direct and
indirect through the interaction term) then Sobel test calculator is used to
find the mediation effect.
Table 3 Mediation among Network Channel, Competition
and Organizational Performance (N= 76)
Model |
R2 |
β |
t |
Sig. |
Network Channel |
0.45 |
0.67 |
7.78 |
0.00 |
Interaction (NC * Compet) |
0.59 |
1.09 |
4.91 |
0.00 |
Note. Dependent Variable: Organizational Performance
In
the regression, first the direct effect of independent variable on dependent
variable has been analyzed. Then in second model the indirect effect through
interaction variable has been analyzed. The interaction term can be calculated
by multiplying the independent variable and mediated variable. The change in
both models shows the effect of on dependent variable. In the above table, the
value of R2 has changed from 0.450 to 0.587. The values of β showed
standardized coefficient value. In the above table, the β values change
from 0.671 to 1.086. The value of t is also changed from 7.784 to 4.911 at the
highly significant level. After calculating these values, Sobel's test is
applied to find mediation effect. The value of Sobel's test is 4.15 at
significant level 0.00. The results proved the mediation of competition between
network channel and organizational performance.
Conclusion & Discussion
This
study is correlational in which the relationship among variables had been
developed. The first hypothesis of the study is that network channels have
positive impact on organizational performance. This hypothesis was tested
through regression analysis and results of the study support the
hypothesis. The second hypothesis of
this study is competition plays the mediating role between network channel and
organizational performance The results of the multiple regression analysis
using Sobel's test proved that competition has been mediating effect between
network channel and organizational performance. So, the mediation effect in the
model was proved. The third hypothesis of this study is radio frequency identification
technology plays the moderating role between network channel and organizational
performance. This hypothesis is tested through moderated regression analysis,
and the results from this test proved this hypothesis. The empirical data
supported the whole model. So, if organizations want to increase their
performance, they should be focused on their network channel. The performance
of network channel is interlinked with radio frequency identification
technology. Because this technology can trace products at real time and give a
lot of information about product delivery. Competition also encourages
organizations to strengthen their network channel through innovation,
technological improvement and new methods to enhance organizational
performance. The model of this study will also open new horizons for
organizations and researchers in new dimensions.
Limitations and Future Directions
This study has some
limitation, which can be minimized in future studies. This study is limited
only four variables network channel, organizational performance, RFID
technology and competition. All other variables have been ignored in this
study. While in the future, some other variable can be considered like channel
policies, customer satisfaction and organizational structure in future studies.
The population of this study is limited to China only. While in future studies
other geographical areas like Malaysia and Pakistan can be considered. This
study is based on quantitative methodology while in future qualitative or mixed
methodology can be focused. This study is limited only retail industry. In
future studies, other industries like health, pharmaceutical, manufacturing and
retailing industry can be considered.
References
Atkinson,
W. (2004). Tagged: the risks and rewards of RFID technology. Risk Management, 51(7), 12-18.
Auh, S., & Menguc, B. (2005). Balancing
exploration and exploitation: The moderating role of competitive intensity. Journal of Business Research, 58(12),
1652-1661.
Bansal, H. S., McDougall, G. H., Dikolli, S. S., &
Sedatole, K. L. (2004). Relating e-satisfaction to behavioral outcomes: an
empirical study. Journal of Services
Marketing, 18(4), 290-302.
Betancourt, R. R. (2004). The Economics of Retailing and Distribution. Cheltenham, UK: Edward
Elgar.
Betancourt, R. R., Chocarro, R., Cortiñas, M.,
Elorz, M., & Mugica, J. M. (2016). Channel Choice in the 21st Century: The
Hidden Role of Distribution Services. Journal
of Interactive Marketing, 33, 1-12.
Betancourt, R. R., Chocarro, R., Cortiñas, M.,
Elorz, M., & Mugica, J. M. (2017). Private Sales Clubs: A 21st Century
Distribution Channel. Journal of
Interactive Marketing, 37, 44-56.
Bose, I., & Pal, R. (2005). Auto-ID: managing
anything, anywhere, anytime in the supply chain. Communications of the ACM, 48(8), 100-106.
Bower, A. B., & Maxham III, J. G. (2012). Return
shipping policies of online retailers: normative assumptions and the long-term
consequences of fee and free returns. Journal
of Marketing, 76(5), 110-124.
Bucklin, L. P. (1966). A theory of distribution channel structure: University of
California, Institute of Business and Economic Research.
Cadogan, J. W., Cui, C. C., & Li, E. K. Y. (2003).
Export market-oriented behavior and export performance: The moderating roles of
competitive intensity and technological turbulence. International marketing review, 20(5), 493-513.
Chan, R. Y., He, H., Chan, H. K., & Wang, W. Y.
(2012). Environmental orientation and corporate performance: The mediation
mechanism of green supply chain management and moderating effect of competitive
intensity. Industrial Marketing
Management, 41(4), 621-630.
Chiu, C. M., Wang, E. T., Fang, Y. H., & Huang, H.
Y. (2014). Understanding customers' repeat purchase intentions in B2C
e‐commerce: the roles of utilitarian value, hedonic value and perceived
risk. Information Systems Journal, 24(1),
85-114.
Dargan, G., Johnson, B., Panchalingam, M., &
Stratis, C. (2004). The Use of Radio Frequency Identification as a Replacement
for Traditional Barcoding. Final Project.
Darke, P. R., Brady, M. K., Benedicktus, R. L., &
Wilson, A. E. (2016). Feeling Close From Afar: The Role of Psychological
Distance in Offsetting Distrust in Unfamiliar Online Retailers. Journal of Retailing, 92(3), 287-299.
Finn, A., Wang, L., & Frank, T. (2009). Attribute
perceptions, customer satisfaction and intention to recommend e-services. Journal of Interactive Marketing, 23(3),
209-220.
Goh, J. W. (2003). The resource advantage theory of
competition: Implications for higher educational institutions in Singapore. Educational Research for Policy and
Practice, 2(2), 93-106.
Haghighinasab, M., Ebrahimi, M., Sattari, B., &
Roghanian, P. (2013). The Effect of Channel Function Performance on
Relationship Quality with Organizational Buyers.
Hart, S. L. (1995). A natural-resource-based view of
the firm. Academy of management review,
20(4), 986-1014.
Hung, S.-Y., Chen, C. C., & Huang, N.-H. (2014).
An Integrative approach to understanding customer satisfaction with e-service
of online stores. Journal of Electronic
Commerce Research, 15(1), 40.
Hunt, S. D. (2011). Developing successful theories in
marketing: insights from resource-advantage theory. AMS review, 1(2), 72-84.
Jaiswal, A. K., Niraj, R., & Venugopal, P. (2010).
Context-general and context-specific determinants of online satisfaction and
loyalty for commerce and content sites. Journal
of Interactive Marketing, 24(3), 222-238.
Keh, H. T. (1997). The classification of distribution
channel output: a review. The
International Review of Retail, Distribution and Consumer Research, 7(2),
145-156.
Kim, J., Jin, B., & Swinney, J. L. (2009). The
role of etail quality, e-satisfaction and e-trust in online loyalty development
process. Journal of retailing and
Consumer services, 16(4), 239-247.
Kopalle, P., Biswas, D., Chintagunta, P. K., Jia Fan,
K., Pauwels, B. T. R., & Sills, J. A. (2009). Retailer Pricing and
Competitive Effects. Journal of
Retailing, 85, 56–70.
Kotler, P., & Armstrong, G. (2010). Principles of marketing: pearson
education.
Lewis, M., Singh, V., & Fay, S. (2006). An
empirical study of the impact of nonlinear shipping and handling fees on
purchase incidence and expenditure decisions. Marketing Science, 25(1), 51-64.
Luckett, D. (2004). The supply chain. BT Technology Journal, 22(3), 50-55.
Mahoney, J. T., & Pandian, J. R. (1992). The
resource‐based view within the conversation of strategic management. Strategic management journal, 13(5),
363-380.
Schoviah, A. (2012). The effect of marketing distribution channel strategies on a firm's
performance among commercial banks in Kenya. University of Nairobi,
Kenya.
Sekaran, U., & Bougie, R. (2013). Research methods
for business: A skill-building approach .[e-book]: Wiley & Sons. http://www.wiley.com/college.
Shister, N. (2005). RFID: Taking stock of the wal-mart
pilot. World Trade, 18(8), 38.
Skarmeas, D., Katsikeas, C. S., Spyropoulou, S., &
Salehi-Sangari, E. (2008). Market and supplier characteristics driving
distributor relationship quality in international marketing channels of
industrial products. Industrial Marketing
Management, 37(1), 23-36.
Swanson, E. B., & Ramiller, N. C. (2004).
Innovating mindfully with information technology. MIS quarterly, 553-583.
Tokman, M., Beitelspacher, L. S., Kros, J. F., Glenn
Richey Jr, R., Chen, H., & Nadler, S. S. (2011). Technology emergence
between mandate and acceptance: an exploratory examination of RFID. International Journal of Physical Distribution
& Logistics Management, 41(7), 697-716.
Van Loo, J., De Grip, A., & De Steur, M. (2001).
Skills obsolescence: causes and cures. International
Journal of Manpower, 22(1/2), 121-138.
Venkatesh, V., Thong, J. Y., & Xu, X. (2016).
Unified theory of acceptance and use of technology: a synthesis and the road
ahead.
Venkatesh, V., & Zhang, X. (2010). Unified theory
of acceptance and use of technology: US vs. China. Journal of Global Information Technology Management, 13(1), 5-27.
Wernerfelt, B. (1984). A resource‐based view of the
firm. Strategic management journal, 5(2),
171-180.
Zahra, S. A., & Covin, J. G. (1995). Contextual
influences on the corporate entrepreneurship-performance relationship: A
longitudinal analysis. Journal of
business venturing, 10(1), 43-58.