No. 08-05 MGT October 2008
Impact of RFID Technology Utilization on Operational
Pamela J. Zelbst
Sam Houston State University
Kenneth W. Green, Jr.
Sam Houston State University
Victor E. Sower
Sam Houston State University
Copyright by Author 2008
The Working Papers series is published periodically by the Center for Business and Economic Development at Sam
Houston State University, Huntsville, Texas. The series includes papers by members of the faculty of the College of
Business Administration reporting on research progress. Copies are distributed to friends of the College of Business
Administration. Additional copies may be obtained by contacting the Center for Business and Economic
Impact of RFID Technology Utilization on Operational Performance
Purpose – The impact of RFID technology utilization on operational performance is
investigated. A structural model that incorporates RFID technology utilization as antecedent to
operational performance is theorized and assessed.
Design/methodology/approach - Data from a sample of 122 manufacturing sector organizations
were collected and the model was assessed following a structural equation methodology.
Findings - RFID technology utilization directly and positively impacts operational performance.
Research limitations/implications –Interpretation of the results should be tempered in light of
this early stage of adoption of RFID technology in the manufacturing sector.
Practical implications – Manufacturing managers can expect improved operational
performance to result from the implementation of RFID technology.
Originality/value – The study offers empirical support for the adoption of RFID technology for
the purpose of improving operational performance within the manufacturing sector.
Manufacturing organizations have begun implementing RFID technology in the hope of both
operational and supply chain performance improvement. The technology holds promise for both
improving the efficiency of operations and logistics processes and improving the effectiveness of
the organization in terms of satisfaction of both the immediate customers of the organization and
the ultimate customers of the supply chain.
As manufacturing managers consider the costs and benefits of adopting the technology,
they should consider its impact on operational, business, and supply chain performance. The
first and primary focus of operations managers is likely to be the benefits on operational
performance. Will RFID technology utilization lead to improvements in operational
performance metrics such as throughput, lead time, product cycle time, and due date
If RFID technology utilization does not lead to improved operational performance, it is
unlikely that business and supply chain performance improvements will be realized. We focus
on this most basic of relationships – the impact of RFID technology utilization on operational
performance. We theorize an RFID-performance model and test the model with data collected
from a sample of manufacturing organizations using a structural equation methodology.
A review of the literature and discussion of the study hypothesis follows in the next
section. A discussion of the methodology employed in the study is then presented followed by a
description of the scale assessment and the structural equation modeling results. Finally, a
conclusions section incorporating discussions of the contributions of the study, limitations of the
study, recommendations for future research, and managerial implications follows.
2. Literature review and hypothesis
According to Drake and Schlachter (2007) development of technologies over the last 25 years
has changed the operational environment of organizations. Dos Santos and Smith (2008, p. 127)
state, “it is widely believed that the use of radio frequency identification (RFID) technology will
enable substantive supply chain transformations.” These authors also state that through the use
of RFID deployment firms can gain competitive advantage.
Large organizations, such as Walmart (Lee and Park, 2008) and Volvo (Holmqvist and
Stefansson, 2006), are forcing the use of the technology onto their upstream supply chain
members. This results in some of the organizations that are supply chain members focusing on
RFID technology simply as a cost of doing business (Zelbst et al., 2008). Vijayaraman and Osyk
(2006) state that many organizations in the supply chain of Walmart have no choice but to adopt
RFID technology. This focus could result in an organization not using information available to
them to increase operational performance. For the transformation identified by Dos Santos and
Smith 2008) to take place at the supply chain level, the performance outcomes at the operational
level need to be assessed.
According to Peng et al. (2008), an organization’s operational performance and strengths
need to be assessed using varied measures of operational performance such as lead time, cycle
time, operating expense, throughput, and inventory expense (Mabin and Balderstone, 2003).
This research will evaluate the impact of the utilization of RFID technology on the operational
performance of manufacturing organizations. We develop and assess an RFID performance
model that incorporates RFID technology utilization as antecedent to operational performance
with the link between the constructs being positive and significant. The model is depicted in
Insert Figure 1 about here
2.1 RFID technology utilization
Much of the research on RFID technology has focused on its facilitation of organizations
becoming more efficient (Uckun et al., 2008). A major barrier to the utilization of RFID has
been the cost/benefit justification (Prater et al., 2005). RFID technology can enhance operational
efficiencies within organizations (Murphy-Hoye et al., 2005) and therefore promises to improve
operational performance (Angeles, 2005; Asif, 2005; Srivastava, 2004). Extrapolating from the
work of these authors, it could be that there is too much focus on initial efficiencies in relation to
the cost of implementation. There should be more focus on effectiveness and the capabilities
that accompany the technology’s utilization. For example, RFID utilization enhances the
timeliness of production information (Brandyberry et al., 1999), creates tracking ability allowing
for traceability of inventories (Green et al., 2008; Lee and Park, 2008) and increases service level
capabilities (Kincade, Vass, and Cassill, 2001) resulting in organizational growth and
profitability (Kotha and Swamidass, 2000; Byrd and Davidson, 2003). Extrapolating from these
researchers’ findings, it stands to reason that RFID technology should enhance operational
performance by disseminating the information in real-time throughout the organization.
2.2 Operational Performance
Operational performance is defined by Feng et al. (2006, p. 26) as, “the performance related to
organizations’ internal operations, such as productivity, product quality and customer
satisfactions.” Technologies such as RFID can lead to improvement in internal operations.
Mabin and Balderstone (2003) identified some measures of operational performance as
throughput, inventory, and operating expense.
Management is involved in a constant balancing between strategic changes and
operational performance (Naranjo-Gil et al., 2008). According to Yeung et al. (2008)
technology that provides information can help to improve not only efficiency but also
effectiveness in operational performance. Extrapolating from these authors’ work and Mabin
and Balderstone’s (2003) work, throughput is related to effectiveness and inventory and
operating expense are related to efficiency. Operational performance is also dependent upon an
organization’s capabilities and technologies (Hatch, 2008). Organizations focusing on
underlying technologies find an improvement in throughput, inventory expense, and operating
expense resulting in a positive impact on operational performance (Huckman and Zinner, 2008).
H1: RFID technology utilization positively impacts operational performance.
3.1 Data collection process
Data were collected via an on-line data service during the summer of 2008. Of the 300
individuals who accessed the survey, 122 completed the RFID technology utilization and
operational performance scales. All respondents represent the manufacturing sector. Of the
sample population 67% are in managerial or supervisory positions and 33% are in operational
positions. Respondents have been in their current positions for 6.93 years and represent
organizations from 18 different manufacturing categories.
3.2 Measurement scales
The theorized model (Figure 1) incorporates RFID technology utilization and operational
performance constructs. The RFID technology utilization scale was originally developed and
assessed for reliability and validity by Green et al. (2008). The items are designed to assess the
degree to which manufacturing organizations have implemented and utilize RFID technology.
The eight-item operational performance scale was developed and assessed for reliability and
validity by Inman et al. (2008). Inman et al. (2008) note that the items in the scale are based on
operational performance metrics originally identified by Mabin and Balderstone (2003).
Respondents were asked to rate their organization's performance in each of eight operational
performance metrics as compared to the industry average. The study scales are presented in
Insert Table 1 about here
Non-response bias was assessed by comparing the responses of early and late respondents
using a common approach described by Lambert and Harrington (1990). Seventy-seven of the
study respondents were categorized as early respondents and 45 were categorized as late
respondents based on whether they responded to the initial or follow-up request to participate. A
comparison of the means of the demographic variables (years in current position and total
number of employees in organization) and for the individual item means was conducted using
one-way ANOVA. The comparisons resulted in non-significant differences indicating that the
concern related to non-response bias is minimized.
Common method bias may lead to inflated estimates of the relationships among variables
when data are collected from single respondents (Podsakoff and Organ, 1986). Taking direction
from Mossholder et al. (1998), common method bias was assessed through single factor
confirmatory factor analysis. This analysis with all items loading on one factor does not fit the
data well with a relative chi-square value of 13.25, an NNFI of .881, and a CFI of .887. This
lack of fit indicates that the concern related to common method bias is minimized.
4.1 Measurement scale assessment
Garver and Mentzer (1999) recommend computing Cronbach's coefficient alpha to assess scale
reliability, with alpha values greater than or equal to 0.70 indicating sufficient reliability. Alpha
scores for both the RFID technology utilization (alpha = .986) and operational performance
(alpha = .970) scales exceed the .70 level. Both scales exhibit sufficient reliability with
coefficient alpha values greater than the .80 criterion recommended by Nunnally and Bernstein
(1994) for basic research.
Garver and Mentzer (1999) recommend reviewing the magnitude of the parameter
estimates for the individual measurement items to assess convergent validity, with a strong
condition of validity indicated when the estimates are statistically significant and greater than or
equal to .70. All nine estimates for the RFID technology utilization scale are statistically
significant and exceed the recommended .70 level. All eight estimates for the operational
performance scale are statistically significant and exceed the recommended .70 level. Figure 2
incorporates the parameter estimates and accompanying t-values.
Insert Figure 2 about here
Discriminant validity was assessed using a chi-square difference test as recommended by
Garver and Mentzer (1999). A statistically significant difference in chi-squares indicates
sufficient discriminant validity (Garver and Mentzer, 1999; Ahire, Golhar, and Waller, 1996;
Gerbing and Anderson, 1988). The computed chi-square difference is 1,361.12 and is significant
at the .01 level.
Koufteros (1999) recommends that the individual scales be incorporated together in a
measurement model and that this model be subjected to an additional confirmatory factor
analysis and that relative chi-square, non-normed fit index (NNFI), and comparative fit index
(CFI) values be used to assess fit when the sample size is relatively small. Relative chi-square
values of less than 2.00 and NNFI and CFI values greater than .90 indicate reasonable fit
(Koufteros, 1999). Results of the analysis indicate that the measurement model fits the data
relatively well with a relative chi-square value of 1.830, an NNFI of .986, and a CFI of .988.
The measurement model is illustrated in Figure 2.
The individual measurement scales are sufficiently valid and reliable to support further
analysis. Additionally, the measurement model fits the data sufficiently well to support further
4.2 Descriptive statistics and correlations
Scale item values were averaged to obtain summary variables for RFID technology utilization
and operational performance. Descriptive statistics and correlations for the summary variables
are presented in Table 2. Summary variable means for RFID technology utilization and
operational performance are 3.04 and 4.07, respectively. The relatively low mean for RFID
technology utilization reflects the relatively early stage of adoption of the technology in the
manufacturing sector. RFID technology utilization is positively related to operational
performance with a correlation coefficient of .48 significant at the .01 level.
Insert Table 2 about here
4.3 Structural equation modeling results
The structural model is displayed in Figure 3. The model fits the data relatively well with a
relative chi-square of 1.83, RMSEA of 0.08, NNFI of 0.99, and CFI of .99. The path from RFID
technology utilization to operational performance (hypotheses 1) is significant at the .01 level
with a standardized coefficient of .56 and an associated t-value of 6.09. Hypothesis one is
supported. RFID technology utilization directly impacts operational performance.
Insert Figure 3 about here
The results support the general proposition that implementation of RFID technology in
the manufacturing sector will yield improved operational performance. Even at this early stage
of adoption, manufacturers can expect improvements in terms of efficiency metrics such as
inventory levels, operating expense, and inventory expense and effectiveness metrics such as
throughput and due date performance.
We theorize a model in which an organization’s degree of RFID technology utilization directly
enhances operational performance. Findings indicate that RFID technology utilization does
directly impact operational performance as hypothesized. The adoption of RFID technology
leads to improvements in an organization’s operational performance.
5.1 Limitations of the study
Data for the study were collected during the summer of 2008. At this time, RFID technology
utilization is in the relatively early stages of the technology utilization life cycle. Interpretation
of the results should be tempered in light of this early of adoption. The scope of this study is
limited only to the operational level benefits of RFID technology utilization. We do not assess
the impact of the technology on business and supply chain level performance. Our limited focus
is designed to investigate the impact of the technology at the most basic level.
5.2 Future research
Because RFID technology utilization is in the early stages of adoption, continued investigation
into the impact of the technology on firm and supply chain performance is necessary as the RFID
story unfolds. As RFID technology utilization becomes more pervasive, it will be important to
investigate its impact on both large and small businesses and throughout multiple sectors. The
primary focus of the technology has been on improving efficiencies related to the production and
tracking of goods. It is important also to assess the impact of the technology within the services
and governmental sectors. RFID technology has the potential not only to improve the “bottom
line” for adopters based on its ability to reduce costs but to enhance firm and supply chain
performance from a marketing perspective. Additional research focused on the ability of RFID
technology to generate sales is also necessary.
5.3 Managerial implications
Within the manufacturing sector, the implementation of RFID technology can lead to improved
operational performance. The technology is linked to improved throughput, lead times, product
cycle times, due date performance, and cash flow. It is also linked to reductions in operating and
inventory expenses and reduced inventory levels. While this is not the only potential for
improved performance, it is the most basic. This research indicates that RFID utilization should
not be seen by the practitioner simply as a cost of doing business but rather as a way to improve
efficiency and effectiveness which ultimately will lead to increased profits.
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RFID utilization (alpha = .986)
Please indicate the extent to which agree or disagree with each statement (1= strongly disagree,
7 = strongly agree).
1. We currently use RFID technology to manage inventory flows through our manufacturing
2. Our suppliers are required to provide products to us that facilitate RFID tracking.
3. Our customers require us to provide products to them that facilitate RFID tracking.
4. We use RFID technology to manage raw material inventory levels.
5. We use RFID technology to manage WIP inventory levels.
6. We use RFID technology to manage FG inventory levels.
7. Our current RFID technology facilitates tracking at the item level.
8. Our current RFID technology facilitates tracking at the bulk (i.e. pallet) level.
9. We plan to expand the use of RFID technology over the next several years to manage
inventory flows through our manufacturing processes.
Operational Performance (alpha = .970)
Please rate your organization's performance in each of the following areas as compared to the
industry average. (1=well below industry average; 7=well above industry average)
2. Inventory expense
3. Operating expense
4. Lead time
5. Product cycle time (throughput time)
6. Due date performance
7. Inventory levels
8. Cash flow
Table 2 Descriptive Statistics and Correlation Matrix
Panel A – Descriptive Statistics
Variable Mean Std. Dev.
RFID Utilization 3.04 1.83
Operational Performance 4.07 1.42
Panel B - Correlation Matrix
Variable UTIL OPPERF
RFID Utilization (RFID) 1
Operational Performance (OPPERF) .484** 1
Note: All coefficients significant at the 0.01 level (2-tailed).
RFID H1: (+) Operational
RFID Technology Performance Model