logistics performance: a theoretical conceptual model for small
TRANSCRIPT
CEFAGE-UE, Universidade de Évora, Palácio do Vimioso, Lg. Marquês de Marialva, 8, 7000-809 Évora, Portugal Telf: +351 266 706 581 - E-mail: [email protected] - Web: www.cefage.uevora.pt
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Rui Mansidão 1, Luís A. G. Coelho2
1 School of Technology of Setúbal/IPS
2 CEFAGE-UE and Management Department, Évora University
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Logistics Performance: a theoretical conceptual model for
small and medium enterprises
Rui M. Mansidão*, Luís A.G. Coelho**
ABSTRACT
This paper presents a theoretical conceptual model for evaluation of logistics performance for small and
medium enterprises (SMEs). Based on recent theoretical developments, grounded in a survey of the most
important literature in the field, it analyzes the impact of the logistics function on organizational
performance. The three main models of logistics performance applied to SMEs inspire the model
presented: Fugate et al (2010), Aramyan et al (2007) and Töyli et al (2008). The conceptual model
developed in this work is built on three basic elements: organizational performance, competitive
advantage and logistics performance, which are grounded in the dimensions of efficiency, effectiveness
and service level.
Keywords: Logistics Performance, Organizational Performance, Competitive
Advantage, Efficiency, effectiveness and SMEs.
JEL Classification: D21, D24, M10
*School of Technology of Setúbal/IPS
Email: [email protected]
**CEFAGE-UE and Management Department, Évora University
Email: [email protected]
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1. Introduction
In the present context of great business competition and an increasingly dynamic
and globalized economy, companies need to find processes and management methods
that enable the development of a more efficient organization with better results. This
paradigm has been the subject of many studies, which focused their analysis on
determination of the different effects and the importance of each for companies’
competitive success (Stock et al., 2000; Bañón and Sanchez, 2002 and Norek et al.,
2007).
Logistics is increasingly playing an important role in everyday business, and
becoming a major factor of differentiation in the market, as referred to by Bowersox et
al. (2002) and Gunaseakaran and Ngail (2003). In the current competitive climate there
is strong pressure, on one hand, to operate in product and service differentiation, and on
other hand, operate on the price factor allowing its reduction. As Melnyk et al. (2009)
mention, logistics can manage these aspects, constituting a strategic or value-creation
tool.
Thus, logistics in intra-organizational and inter-organizational functions is a
prominent activity in companies, since this plays an important role in supply
management, both internally and externally.
In the literature, various empirical studies, such as Ellinger et al. (2000), show that
logistics is a strategic vector in companies’ organization and influences their
performance, namely in terms of service quality and overall profitability. In parallel
with its internal importance, logistics also has an impact on effectiveness and
profitability, as mentioned by Mentzer et al. (2001) and Fugate et al. (2010). The
management of logistics activities has become a valuable way of securing competitive
advantage and improving organizational performance (Li et al., 2006).
Thus, based on this research field, this paper intends to take a theoretical approach
to logistical and organizational performance in small and medium enterprises (SMEs).
Given the multidimensional nature of the performance component, it aims to identify
the key elements which, in terms of the logistic function, can contribute to improving
the performance and competitiveness, as well the efficiency and effectiveness, of
SMEs’ internal processes. For this purpose, the paper defines a research framework and
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presents a conceptual model to analyze the influence of logistics performance on
organizational performance.
The paper is organized as follows: the next section approaches the performance
analysis with special emphasis on logistics performance, the third section reviews the
conceptual models for assessment of the logistics performance of small and medium
enterprises, the fourth section presents the performance logistics evaluation model and
finally, the conclusions, limitations and suggestions for future research are in the fifth
section.
2. Performance Evaluation
The theme of performance evaluation is not likely to be exhausted in the scientific
community, and is a field of research that has received increasing attention from
scholars in various fields of knowledge (Neely, 2002). In the search for higher levels of
competitiveness, at the macro-economic level, the relationship between economic
competitiveness and companies’ performance is studied, since the new paradigms of a
country’s competitiveness are derived directly from the performance achieved by its
business structure.
If at a macro level competitiveness is reflected in the performance of a given
economy, at a micro level competitiveness is likely to be observed by the company’s
market share. Thus, assessing company performance constitutes a very fruitful tool for
the measurement and management of organizational objectives (Kuo and Chen, 2008;).
Systems performance measurement must include orientation of the organization’s
progress in order to achieve its objectives. Providing critical feedback on business
strategies’ success allows not only shaping the behavior of managers with responsibility
for developing competitive strategies, but also of those who implement them
(employees), as mentioned by Fawcett and Cooper (1998).
An exact interpretation and the existence of measures for evaluating performance
are key factors in businesses’ success. In the current competitive environment, it is
essential that organizational leaders, at a given time, know what happened, why it
happened and what can be improved in the future.
Some studies in this area reported that the objectives of company performance
evaluation can be of various kinds. In this connection, Thomas (2006) states that some
of the main objectives of performance evaluation at the organizational level are helping
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to clarify objectives, communicating priorities, monitoring organizational functioning
and evaluating whether the organization is meeting the objectives outlined.
Organizational performance is the result of performance at the sectorial level and, thus,
the evaluation of logistics performance represents a component of organizational or
business performance evaluation.
2.1. Logistic Performance
At the logistical level, the importance of analyzing performance was first shown in
the work of Bowersox and Closs (1996), who reported that measurement of logistics
performance consisted of a methodology for analyzing resources of the logistic
function, and its main objectives were monitoring and control of the logistics
operations.
After this initial step, analysis of logistics performance has become an important
issue in the area of management science research, but despite this attention from
researchers, there is little convergence both in terms of methods and in terms of results
for its validity. As Robb et al. (2008) mention, since logistics deal with physical,
informational and cash flow management, it is generally recognized as a major
determinant of business performance, but practices particularly in terms of performance
analysis, are still at the stage of being studied by professionals and academics.
In the literature, it is possible to identify a significant amount of work on the
relationship between logistic performance and organizational performance, such as the
work of Larson et al. (2007) who demonstrated that the performance of logistics
activities can have an impact on organizational performance.Those authors, in a study
conducted among business leaders on the impact of the perception of logistics
performance on business results, found that a significant number of managers said that
the perceived impact of logistics performance consisted of better performance in
customer service, better inventory levels and optimization costs.
As logistics are increasingly expected to contribute to organizational performance,
several studies have examined the influence of logistics performance operations and
logistics management practices on overall company performance. Some authors, such as
Zhou and Benton (2007) investigated the link between logistics management practices
and distribution performance regarding reliability of service, and concluded that
practices related to the distribution and sharing of information have a direct impact on
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performance. Also Green et al. (2008), addressing the relationship between logistics
practices and organizational performance in a large number of companies in the United
States, concluded that logistic practices have a positive impact on business performance,
namely in speed of delivery, the responsiveness and flexibility of delivery, and also
influence marketing performance, which has a leverage effect on the average sales
growth and business profitability.
Roth et al. (2008) investigated the antecedents and performance results of a set of
leading global companies, concluding that information technology and logistics
management contribute to increased sales and profitability. More precisely, information
and communication technology increased sales and logistics management increased
organizational profitability. Chow et al. (1994), who focus on analyzing the relationship
between objectives, practices, skills and management performance in the supply chain,
concluded that logistics practices influence logistics capabilities positively in terms of
quality and service, operation distribution and efficiency.
2.2 . Logistic Performance in SMEs
As described in the literature review, performance analysis is a relevant factor in
everyday business, in which there is great complexity of business processes. The
shorter life cycles of products and services, market globalization and the growing
pressure to improve profitability are elements of increased complexity. Thus, the area of
logistics performance and its contribution to organizational performance have been
onthe research agenda. According to Bhagwat and Sharma (2009), analysis of logistics
performance is among the main challenges faced by today's companies. Other
challenges include, for example, customer service, strategic partnerships, inventory
management and logistics flow management, reducing cycle times and geographical
coverage along with flexibility (Li et al., 2006).These challenges arise mostly from the
decentralization of production systems, leading companies to move towards the
development of basic skills and the need to implement efficient and effective
management of logistic activities.
As referred to by Schramm-Klein and Morschett (2006), analysis of logistics
performance is a strong current trend, which involves monitoring and planning in order
to establish connections between the results of indicators and the firm, determining how
well companies achieve strategic objectives as part of their definition and competitive
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orientation (Gunasekaran and Kobu, 2007). However, despite this importance, one of
the gaps identified in the literature on this subject is that most publications on Logistics
or Supply Chain Management are outlined for, or targeted at large enterprises, with few
publications discussing logistics in the SME context (Spillan et al., 2010).
Some authors mention that the way logistics have been implemented in SMEs
consists of application of smaller versions of successful practices in large organizations,
hoping the results will be the same in SMEs despite their more limited resources and
less willingness to invest in equipment and infrastructure (Norek et al., 2007).
Apart from this last point, another gap identified is the virtual absence of studies
that specifically address logistics performance in SMEs, as it appears there is still no
well-defined research agenda in this area of research. Despite this, the work of Halley
and Guilhon (1997), Bagchi and Virum (2000), Koh et al. (2007) and Töyli et al. (2008)
deserves special mention.
One of the first papers on this subject was the work by Halley and Guilhon (1997)
who study logistics strategies in a set of small businesses in the vegetable sector. These
authors ascertained that, due to growing awareness of organizational integration,
logistics has become an important role in enterprises with centralized control and close
management by managing partners.
The work by Bagchi and Virum (2000), conducted in a group of Norwegian SMEs,
aiming to identify logistical competencies, concluded that despite the effort to develop
these competencies and use them as a competitive lever, this is only possible according
to two principles: performance evaluation and verification of that performance’s
contribution to obtaining a competitive advantage. Another conclusion of this study is
that these authors emphasize the importance of SMEs as a strategic pillar for
development of smaller countries, where the business community is mainly composed
of this type of business organization.
Koh et al. (2007) studied the relationship between logistics management practice
and operational and business performance in a sample of SMEs producing metal
products and equipment in Turkey. Despite the limitation of the study being confined to
the city of Istanbul, the authors concluded that the practice of outsourcing and strategic
collaboration does not have a direct impact on organizational performance, but can have
a direct influence on SMEs’ operational performance.
Analyzing the importance of logistics performance in the financial performance of
Finnish SMEs, Töyli et al. (2008) concluded that a high logistics performance is
7
associated with efficient operations, involving overall cost efficiency and high
productivity of fixed assets. As the logistics performance of the group of companies
observed was at a very elementary level, a statistically significant relationship was not
found between logistics and financial performances. However, the authors emphasize
that the level of service and efficiency of logistics costs are positively related, since
firms with a high level of service had lower logistics costs.
In the work of Töyli et al. (2008), logistical and financial performance was
operationalized through the use of multiple measures. Financial performance was
measured through profitability and growth, as in the study by Delmar (1997) and
Weinzimmer et al. (1998). Thus, these investigators used as indicators of growth the
average rate of turnover growth and the average rate of asset growth, for the same
period. Profitability was measured by indicators such as average return on total assets,
average return on capital and Earnings Before Interest and Taxes (EBIT). As
conclusions of their work, the authors report that there was no large-scale observable
pattern to indicate that firms with high logistics performance are more profitable and
grow faster than the average of other companies. Overall, the results support the
possibility of logistics not yet having emerged as a driver of large-scale competitiveness
in Finnish SMEs.
3. CONCEPTUAL MODELS FOR EVALUATION OF
PERFORMANCE LOGISTICS
In this section we present three models for logistics performance evaluation that are
used to support the model presented in section 4. The first model, created by Fugate et
al. (2010), puts emphasis on the dimensions of efficiency, effectiveness and
differentiation of logistics activities as determinants of logistics performance. The
second model, created by Aramyan et al. (2007), analyzes the supply chain of agri-food
products, using efficiency, flexibility, responsiveness and food quality as determinants
of logistic performance. The latest model, developed by Töyli et al (2008), analyzes
logistics performance as dependent on the efficiency of logistics costs, quality of
logistics services and logistics performance.
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3.1. LOGISTICS PERFORMANCE: DIMENSIONS OF FUGATE
Fugate et al. (2010) analyzed the relationship between logistics performance and
organizational performance, stating that logistics performance is multidimensional and
is a function of the resources used in logistics, according to outlined objectives and
outcomes against competitors. In this context, the authors theorized that analysis of
logistics performance should be based on evaluation of a set of dimensions of the
activities carried out by the logistic function, which are namely, efficiency,
effectiveness and differentiation, as shown in the following table:
Table 1 - Logistics Performance Dimensions of Fugate
Dimensions Authors
Efficiency Mentzer and Konrad (1991), Griffis et al.(2004), Bobbitt (2004),
Seldin and Olhanger (2007).
Effectiveness Mentzer and Konrad (1991), Griffis et al. (2004), Bobbitt (2004),
Seldin and Olhanger (2007).
Differentiation Langley and Holcomb (1992), Bobbitt (2004), Flint et al. (2005),
Lambert et al.(2005) Source: Fugate et al. (2010)
According to these authors, efficiency is a dimension related to the use of resources
allocated to the logistic function, effectiviness can be defined as the extent to which
objectives are achieved and differentiation is understood as the value that can be
generated by the elements of customer service in relation to competitors.
In the opinion of Fugate et al. (2010), the better the quality of the joint work of human
resource logistics, planning and implementation of solutions to customers’ requests, the
lower the level of redundancies, conflicts and customer complaints, which increases
efficiency levels due to responsiveness (less time), allows lower levels of waste and
invested capital, and thus increases logistics efficiency and the likelihood of meeting
deadlines.
In this context, Fugate et al. (2010), in carrying out empirical research to analyse
the interrelationships between the different variables of logistic performance and their
impact on organizational dimension, outlined the following conceptual model:
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Figure 1 – Fugate Logistic Performance Model
Source: Fugate et al. (2010)
The conceptual design of the Fugate model consists of two levels of analysis. The
central level, which represents the convergence of the model for analysis of the impact
of logistics performance on organizational performance, where the authors seek to
obtain the final result of the investigation. And at a previous level, it examines variables
that form the constructs of logistic performance. This model has been tested and
validated with a number of randomly selected large companies. These authors’
conclusions point to confirmation of a significant relationship between organizational
performance and logistics performance .
The Fugate model refutes an argument at the center of controversy over the
possible trade-off between the constructs underlying performance dimensions. Some
authors have reflected on the relationship between business objectives and the concepts
of efficiency and effectiveness. According to these authors, when defining a direction or
a goal, business leaders should opt for one dimension, since it appears that performance
progress in one dimension entails a step backwards in another.
Conversely, Fugate et al. (2010) find firms that choose to combine efficiency and
effectiveness achieve better performance than their competitors who choose only one of
these dimensions, which is in line with what is stated by Seldin and Olhanger (2007).
This finding clarifies the condition that companies should not consider the dimensions
of performance as antagonistic, but instead be able to achieve both simultaneously.
These authors also emphasize the fact that in addition to efficiency and
effectiveness, the logistics function must also provide value added service to its
customers to differentiate companies in today’s market. Thus, the main task is
Logistics
Performance
Organizational
Performance
Efficiency Effectiveness Differentiation
10
conjugating the three constructs of logistics performance simultaneously and being
innovative, since, as mentioned by Fugate et al. (2010), excellence in logistics is
associated with better organizational performance.
3.2. ARAMYAN APPROACH
In order to understand performance in the agri-food supply chain, Aramyan et al.
(2007) developed a conceptual framework to analyze logistics performance. The
Aramyan model is based on a literature review of the main methodologies for analyzing
performance and contains the specific features of an agri-food supply chain. The model
structure is based on four categories of variables which, in the authors’ opinion, collect
specific information about that industry. The model structure is as follows:
Figure 2 - Aramyan Model
Source: Aramyan et al. (2007).
Based on these dimensions, Aramyan et al. (2007) theorized a conceptual
framework for evaluation of logistics performance, which suggests dividing the analysis
of logistics chain performance in four categories or clusters of indicators. The first
category is, efficiency which, according to Lai et al. (2002), seeks to measure how
resources are used. This category consists of a set of logistical process indicators, such
as distribution costs, transaction or possession of stock. The second category, flexibility,
supported in the literature by Bowersox and Closs (1996) and Beamon (1998), indicates
the ability of the Performance Measurement System to respond to changes in the
environment and exceptional customer orders. The third category, called
responsiveness, according to Pearson and Olhager (2002), helps to promote what the
customer wants in the shortest amount of time. Finally, quality, which is based on the
framework by Lunning et al. (2002), represents the particular characteristics of the food
supply chain, such as shelf life and product safety, among others.
Performance
Responsiveness
Efficiency
Flexibility
Quality
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The model proposed by Arayman et al. (2007) was applied to analysis of the
performance chain of agri-food products from the Netherlands to Germany. The authors
developed a Performance Measurement System, which consists of a set of key
performance indicators that were split according to the model variables, as shown in
Table 2:
Table 2 – Aramyan categories and performance indicators
Categories Definition Key Indicators Authors
Efficiency
Seeks to measure
how resources are
used, consisting of
financial metrics
framework.
Production costs;
Distribution costs;
Transaction cost;
Results;
Return on investment.
Bowersox & Closs (1996);
Beamon (1998, 1999);
Gunasekaran et al. (2001);
Lai et al. (2002).
Flexibility
Indicates the degree
to which the supply
chain responds to
changes in the
environment and to
customer requests.
Customer satisfaction;
Volume flexibility;
Delivery Flexibility;
Exceptional orders.
Bowersox & Closs (1996);
Beamon (1998, 1999);
Gunasekaran et al. (2001);
Lai et al.(2002).
Responsiveness
Assesses the ability
to respond to
customers and helps
to promote product
requirements in a
short time cycle.
Service level;
Delays in orders;
Response time to
customer;
Complaints and
shipping errors.
Bowersox & Closs (1996);
Beamon (1998, 1999);
Gunasekaran et al.(2001); Lai
et al.(2002).
Quality
Evaluates aspects of
sensory property,
shelf-life, safety,
production and
marketing.
Product quality;
Process quality.
Beamon(1999);
Lunnig et al. (2002);
Van der Spiegel (2006)
Source: Aramyan et al. (2007).
The empirical part of this investigation resorted to a data collection instrument
where it was possible to identify the importance of the elements of the logistics chain
attached to each of the indicators.
Based on the results obtained, a Performance Measurement System was developed
for the specific logistics of the agri-food production chain, finding that the most relevant
indicators to evaluate logistics performance were related to costs, results (profit),
customer satisfation, delivery time and product quality. Some indicators, although
perceived as important, such as delivery flexibility and marketing indicators were not
measured by the elements of the supply chain, the main reason being the difficulty in
quantifying these metrics. As a conclusion it is noted that the model presented and
performance analysis framework allow implementation in a supply chain or in a
particular organization.
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3.3. TÖYLI PERFORMANCE APPROACH
Another major approach is that of Töyli et al. (2008), who study the logistics
performance of Finnish SMEs and analyze the relationship between this performance
and company performance in financial terms. These authors concluded that high
logistics performance is associated with efficient and consistent operations, involving
overall cost efficiency and high productivity of fixed assets.
The conceptualization of Töyli et al. (2008) arises due to the fact that, despite
logistical performance and financial performance having been studied, their relationship
constitutes a research gap, because it has not been subjected to empirical studies,
especially in the field of SMEs. For these authors, this area is an exploratory field due to
the consensus that good logistics performance has an impact on a company’s results. It
allows the reduction of costs, increased income and efficient use of investments in
assets.
An interesting argument relating logistics performance with financial performance
is given when the authors mention that logistics performance will have a positive effect
on share price in the capital market, due to the direct effects related to optimizing costs
and gross operating profit, as set by Christopher and Ryals (1999).
According to Töyli et al. (2008), logistics performance is understood as a
multidimensional construct, including cost efficiency, as outlined in the conclusions of
some researchers, such as Beamon (1999) and Chow et al. (1994), service quality,
mentioned by Fawcett and Cooper (1998) and operational performance metrics
identified in the work of Gunasekaran et al. (2004) and Yusuf et al. (2004). The authors
identify the following dimensions of logistics performance:
Figure 3 – Töyli Logistic performance dimensions
Source: Töyli et al. (2008)
Logistic
Performance
Service Level
Operational
Metrics
Logistic Costs
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According to Töyli et al. (2008), logistic performance includes three components:
(1) the service level that aims to characterize the service quality for logistics clients, the
level of perfect orders and the duration of the cycle; (2) operational metrics that
characterize the logistics performance based on time, including stock rotation and
average payment and receipt; (3) the level of logistics costs that characterize the
efficiency of logistics operations.
One of the main conclusions to retain in this approach is that to analyze the
relationship between logistic and financial performance, we must first examine
separately the performance constructs, starting with analysis of financial performance,
followed by analysis of logistics performance. Töyli et al. (2008) propose a research
framework that includes the following elements:
Table3- Töyli Framework Dimensions
Constructs Theoretical Dimensions Authors
Elements of logistical
profile identified in
previous studies
Evaluation and improvement of logistics
performance
Schramm-Klein and Morschett, (2006); Shang
and Marlow,(2005).
Intra and inter organizational coordination
Support information system and information
sharing
Size and degree of outsourcing
Logistic Know-how
Logistics
Performance
Logistics Cost Efficiency
Beamon, (1999); Chow et al. (1994);
Gunasekaran et al. (2004); Schramm-Klein and
Morschett,(2006); Yusuf et al. (2004).
Logistic Service Quality
Beamon, (1999); Chow et al. (1994);); Fawcett and Cooper, (1998); Gunasekaran et al.,
(2004); Schramm-Klein and Morschett, (2006); Shang and Marlow, (2005); Stank et al. (2001).
Logistics Performance based on time
Chow et al., (1994); Fawcett and Cooper,
(1998); Gunasekaran et al, (2004); Schramm-
Klein and Morschett, (2006); Yusuf et al, (2004).
Financial
Performance
Profitability Delmar (1997); Weinzimmer et al. (1998);
Garnsey et al. (2003); Stewart (2004).
Productivity
Growth
Source: Töyli et al. (2008)
In the framework proposed by Töyli et al. (2008), analysis of SMEs’ logistics
performance consists of three dimensions: the elements of logistical profile, logistics
performance and financial performance. It should be noted that despite being an
methodological analysis that fills a gap in the SME context, it has the disadvantage of
not yet having been validated for these companies.
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4. CONCEPTUAL MODEL
According to previous models, we assume that logistics performance is influenced
by factors such as: effectiveness, efficiency, differentiation, flexibility, responsiveness,
quality, operational metrics, service level and logistics costs. As can be inferred, all
these factors can affect logistics performance and performance at the organizational
level. From the factors mentioned earlier, the most important ones must be isolated in
order to understand the relationship of each with logistics performance.
Based on the literature review, a model is proposed which integrates the following
variables as determinants of logistic analysis of Organizational Performance: Logistics
Performance, Competitivite Advantage and Organizational Performance. Despite the
relevance of other factors in explaining logistics performance, the model isolates these
variables based on the assumptions present in studies conducted on this topic, as
presented in the following table:
Tabel 4 – Dimensions of Conceptual Analysis
Dimensions Source
Logistic
Performance
Fugate et al. (2010); Green et al. (2008); Töyli et al.
(2008); Schramm-Klein and Morschett (2006); Sang
and Marlow (2005).
Competitive
Advantage
Carranza et al. (2002), Bobbitt (2004), Bhatagnar and
Teo (2009); Sandberg and Abrahamsson (2011).
Organizational
Performance
Fugate et al. (2010); Green et al., (2008), Schramm-
Klein and Morschett (2006); Aramyan et al. (2007);
Töyli et al. (2008);Kim (2006); Yang (2012).
The focal point of the development of the conceptual framework is based on the
fact that good performance of the logistic function provides a good level of
organizational performance, which can be achieved by market competitiveness. Thus,
logistics performance is assumed to be a determinant of organizational profitability
because good performance of logistics activities is associated with efficient operations
and reduced costs, and leads to high asset productivity (Yang, 2012).
In terms of competitiveness, we find there has been growing interest among
researchers in the fact that logistics can be a key factor in achieving competitive
advantage in the market (Carranza et al. 2002). The literature is consensual, regarding
logistics activities having a positive competitive impact on the company, because they
15
allow development of key determinants for market positioning with better levels of
efficiency, cost reduction and differentiation of customer service.
In general, organizational performance is defined as return or profitability, sales
growth and increased market share, which is the result of the products and services
marketed and a consequence of the processes used by companies (Akgün et al. 2009). In
this conceptual framework we point out that if logistic performance reflects the
company's performance with regard to the ability to distribute products and services in
the right quantity at the right time to its customers (Green et al., 2008), performance
organization is the reason for the performance, including its ability in terms of
profitability and investment return, when compared to their competitors (Green et al.,
2004; Green et al., 2008).
Based on these three components, an explanatory conceptual model is developed
for the analysis of logistics performance and its contribution to organizational
performance in small and medium enterprises. The basis for preparing this model is the
fact that the cumulative evidence from the literature reveals that performance is a
multidimensional construct that can be characterized by multiple perspectives
(Gunasekaran et al., 2001).
Some authors suggest that performance can be defined as the efficiency and
effectiveness of logistics activity performance (Mentzer and Konrad, 1991 and Fugate et
al, 2010). In addition to these two components, good performance is related to how the
logistics function meets customers’ requirements, namely the level of service (Töyli et
al. 2008). Based on this reasoning, logistics performance is a first order dimension,
which is defined by efficiency (how resources are used), effectiveness (degree of
compliance with the goals set) and service level attached to logistics activities. These
components represent the second order dimension in logistics performance.
The second model construct is competitive advantage, since it assumes that
logistics performance produces higher levels of competitiveness, providing key
differentiating factors in the market (Li et al., 2006). Competitiveness is the
development of core competencies, which are used to obtain competitive advantages,
meaning good performance in market share and business margins (Porter, 1996 and
Stank et al. 2001).
If the initial part of the model concerns the dimensions of logistics performance and
competitiveness, the model output will be organizational performance, which reflects
how a company achieves business objectives and goals regarding its budget and
16
financial management. Thus, based on the variables described in the previous section,
we propose a conceptual model, whose main objective is to analyze the impact of
logistics performance on the performance of small and medium enterprises.
This model is based on the assumption found in the literature, that there is a
positive correlation between logistics performance and organizational performance. The
conceptual model can be represented by the following figure:
Figure 4 – Conceptual Model
The model presented is the result of adaptation of the models by Fugate et al.
(2010) and Aramyan et al. (2007), and the framework developed for this line of research
by Töyli et al. (2008). Finally, it is pointed out that the model constructs must be
operationalized through the perception and size of each of the constructs in the specific
environment of SMEs.
5. Conclusions
In a highly competitive environment where companies are faced with intense
competition, lack of resources and unfavorable economic conditions, performance
analysis combined with a culture of competitiveness are assumed to be crucial factors
for survival and business success.
In a highly competitive market for customers and resources, logistics plays an
important role, given the availability of products or services to customers, and promotes
higher levels of efficiency and effectiveness in carrying out activities, leading to better
results (Fugate et al. 2010). Thus, in recent years a considerable number of publications
have recognized the importance of logistics and supply chain management for business
performance. However, this relationship has been studied in a scenario of large
Organizational Performance
Logistic Performance
Efficiency
Effectiveness
Service Level Competitive Advantage
17
enterprises and supply chain management, with few studies on the direct relationship
between the logistic function and organizational performance, at the SME level.
The central objective of this study is to define a conceptual theoretical framework
for analysis of performance logistics and its impact on competitiveness and business
performance. To that end, a broad bibliographical review found three approaches in the
line of this work. The Fugate et al. (2010) approach, considering a number of large
companies; the Aramyan et al. (2007) approach, developed for agro-industrial products
and the Töyli et al. (2008) approach with a set of Finnish SMEs.
These studies were found to present limitations regarding the objectives defined in
this study. The Fugate et al. (2010) study is restricted to large industrial companies,
which does not allow us to draw reliable conclusions for SMEs, where opportunities
and resources are more limited. The Aramyan et al. (2007) model is developed taking
into account the specific characteristics of the agro-food industry, with short life
periods, food safety and product quality. The Töyli et al. (2008) approach is unique,
because it was developed for the analysis of logistics performance in SMEs. However,
they point out the disadvantage of lack of validation before moving on to the empirical
application. These conclusions underscore the central importance of the investigations
carried out by the authors, but also alert us to the fact the assumptions are not
comprehensive, suggesting that performance analysis can be enhanced with the
introduction of other explanatory variables or consideration of new interactions between
existing variables.
With this backdrop, based on the literature review, a conceptual framework was
developed, with three axes of analysis: (1) logistical performance, defined as the degree
of efficiency, effectiveness and level of service associated with logistics activities; (2)
Competitive Advantage, which is perception of the logistics value compared to other
companies in the market; and, (3) business performance which, in addition to
representing the organization’s efficiency and effectiveness, represents the company’s
profitability and wealth for its stakeholders.
The major limitation of this study is not testing the theoretical model presented.
Since this work is essentialy theoretical, it makes an exhaustive bibliographic review of
the field, but lacks practical application that allows the model to be tested in real
situations with SMEs. This is a suggestion for future research, which we intend to carry
out in the near future.
18
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