An integrated-empirical logistics perspective on supply chain innovation and firm performance.
Mandal, Santanu ; Korasiga, Venkateswar Rao
Introduction
Supply chains are more complex (Gunasekaran et al. 2008) and are
becoming more prone to disruptions with increasing environmental
uncertainties (Wagner, Bode 2008). In this context, firms are forced to
contemplate on strategies and capabilities that can address these
growing uncertainties. Thus today's supply chain has to respond
proactively to these environmental conditions. Hence innovation in
supply chains becomes a dire necessity not only to respond proactively
to disruptions and uncertainties; but also to gain a competitive
advantage in the market. Possibly, this may be the reason for
identifying the most innovative organization by ACSCMP (American Council
of Supply Chain Management Professionals) and rewarding the same with
their "Supply Chain innovation Award". Arlbjorn, Haas and
Munksgaard (2011) noted in this regard "... among the nominees have
been prestigious organizations such as the U.S. Air Force, Motorola,
Kellogg's, and Blockbuster Inc. The list of award winners includes
companies like Intel, Cisco Systems Inc., and Hewlett-Packard. The
winner is selected out of 45-50 submissions each year, based upon
criteria related to the degree of innovativeness, impact on overall
supply chain, and sustainability in results (revenue, cost savings,
etc.)".
However, supply chain innovation is a must therefore for the
following reasons: (a) for gaining competitive edge in the market (b)
for managing the different types of risks prevailing in the supply chain
(Wagner, Bode 2006) and (c) for meeting proactively the different forms
of uncertainties in the adjoining environment. But for developing
innovative supply chains, firms must ascertain its various logistics
capabilities and align them in an appropriate manner. As logistics are
an essential part of supply chain (Mentzer et al. 2004); firms cannot
develop an innovative supply chain without integrating the dominant
logistics capabilities viz. demand management interface capability,
supply management interface capability, information management
capability and coordination capability (Mentzer et al. 2004; Esper et
al. 2007; Gligor, Holcomb 2012). Hence the current investigation
attempts to address the growing influence of each of the above logistics
capabilities on supply chain innovation in an empirical framework.
Accordingly, the objectives of the current investigation are as follows:
(a) To investigate the influence of different logistics
capabilities on logistics integration.
(b) To investigate the influence of logistics integration on supply
chain innovation.
(c) To investigate the influence of supply chain innovation on
supply chain performance?
The paper is arranged in the following manner. The next section
discusses the theoretical backdrop and the research model. The
subsequent section discusses the hypotheses followed by data collection
and empirical testing. Finally, the study discusses the findings and
concludes with managerial implications and scope for future research.
Limitations of the study have also been addressed.
1. Theoretical background
1.1. Supply chain innovation
Supply chain innovation and logistics innovation have been dealt
interchangeably. However the literature on supply chain innovation is
highly fragmented (Grawe 2009) and multidisciplinary investigation has
taken place (Flint et al. 2005). Supply chain innovation draws mainly
from the definition of Innovation given by Rogers (1995: 11):
"Innovation is an idea, practice, or object that is perceived as
new by an individual or other unit of adoption". Innovation in
logistics need not be evolutionary but the same may result in providing
a new service to its customers. For e.g. Flint et al. (2005) focused on
innovation that is more helpful to customers for e.g. a better and
enhanced service that is new. Though innovation emphasizes idea
generation, but it's not beneficial or deemed important in a supply
chain perspective unless it results in something valuable to the
customers. For innovation to happen, only idea generation may not be
enough (Chesbrough 2003); allied processes and technology must be
emphasized for successful innovations (Christiansen 2000a, 2000b; Kahn
2001). Literature also cites how the innovation takes place in
organizations and markets (Rogers 1995; Chesbrough 2003). Firms are
constantly thriving to develop and test new ideas, products and
services. Mainly for service industries, supply chain innovation is a
compulsory for ensuring effective service delivery (Chapman et al.
2003). Drucker (1985) indicated innovation as a tool directed
specifically for entrepreneurs. Afuah (1998) defined innovation as:
"a process of turning opportunity into new ideas and putting these
into widely used practice. Innovation facilitates create new technical
skills and knowledge that can help develop new products and/or services
for customers". The literature on supply chain innovation has just
started evolving. Lin (2008) described supply chain innovation as
certain set of tools that can improve firm processes directed for
efficient supply chain management through seamless integration with
suppliers, manufacturers, distributors and customers. A host of benefits
are present with supply chain innovation like cost and lead-time
reduction, generation of new operational strategies and flexibility
development (Stundza 2009). Logistics innovation can be increased by
using appropriate incentives like increased competition and capital
shortage (Zinn 1996). Flint et al. (2005) interviewed several logistic
executives and found a host of activities as indications of being
innovative viz. setting the stage activities; customer clue gathering
activities; negotiating, clarifying and reflecting activities; and
inter-organizational learning. Later studies found that extent of
innovation management and supply chain learning as having positive
impact on supply chain innovation (Flint et al. 2008). Resources when
combined, can lead to increased level of specialization and innovation
(Hakansson, Persson 2004). Chapman et al. (2003) explored in a similar
context relating to factors leading to innovation in logistics services
and found that knowledge, technology and relationship networks as the
relevant factors. Panayides and So (2005) empirically found
organizational learning to mediate the relationship between relationship
orientation and logistics innovation. Several studies have investigated
performance under innovation. Gellman (1986) examined innovative
performance of railroads under deregulation and found regulation, labor
influence and lack of channel member innovation as barriers to
innovation in the allied industry. Autry and Griffis (2008) using social
network theory propounded structural capital, relational capital and
supply chain knowledge development to be positively associated with
innovation-oriented performance. Wagner (2008) proposed a model of
logistics innovation consisting of several related activities like
internal search and development, external search and development,
investment in infrastructure and capital goods, acquisition of knowledge
and training and education etc. that can lead to innovations in
logistics. Supply chain innovation also indicates discovering and
implementing new technologies with better efficiency and effectiveness
(Bello et al. 2004). Supply chain innovation can encompass several areas
for application for e.g. implementing new technology (Stonebraker, Afifi
2004; Tang et al. 2003), supply chain networks (Srai, Gregory 2008),
supply chain business process optimization (Hines 1998; Holmstrom 2000;
Cox 1999), new product and service introduction (Ettlie 1979; Flint et
al. 2005), building new models and scenario for optimization (Bello et
al. 2004; Calantone, Stanko 2007), etc.
1.2. Defining logistics capabilities
Mentzer et al. (2004) underscored logistics as an integral part of
supply chain management; accordingly, logistics capabilities are
required for developing supply chain capabilities. Morash et al. (1996)
defined logistics capabilities as "those attributes, abilities,
organizational processes, knowledge and skills that allow a firm to
achieve superior performance and sustained competitive advantage over
competitors". Logistic capabilities determine the extent to which a
firm can manage its operations efficiently and effectively (Gligor,
Holcomb 2012) and are a p otential source of competitive advantage for a
firm (Bowersox et al. 1999; Zhao et al. 2001).
In the logistics literature, there exists several related and yet
different classifications of logistics capabilities. Morash et al.
(1996) through an extensive review of logistics capabilities classified
the same into two broad themes or "value disciplines". While
the former value discipline, labeled "demand oriented"
emphasizes interactions and interfaces with customer, fulfillment of
allied goals and objectives, timeliness and being responsive to market
needs; the latter, known as "supply oriented" stresses more on
operational capabilities aimed at ensuring product availability,
increasing convenience and minimizing total distribution cost. In
contrast, Mentzer et al. (2004) classified logistics capabilities into:
demand management interface capability (to manage and fulfill customer
requirements; Zhao et al. 2001; Lynch et al. 2000; Bowersox et al.
1999), supply management interface capability (to efficiently manage
inflow of raw materials; Morash et al. 1996; Lowson 2003), information
management capability (to effectively manage information flow both in
and out of an organization; Zhao et al. 2001; Closs et al. 1997) and
coordination capability (to align the interests of the participating
members; Mentzer et al. 2004; Gligor, Holcomb 2012).
Esper et al. (2007) categorized logistics capabilities into five
broad labels: (a) customer focus capability(also known as demand
management interface capability and aims for providing differentiated
products and services to customers in a way exceeding their
expectations), (b) supply management capability (aimed at reducing the
cost of total manufacturing or service generating system, optimal
utilization of resources and minimizing total distribution cost), (c)
Integration capability (aims to achieve unification of effort among
different activities both inside and outside the focal firm), (d)
measurement capability (degree to which a firm monitors internal and
external operations), and (e) information exchange capabilities
(indicates the effectiveness with which a firm collects, stores and
distributes tactical and strategic information both internally and
externally).
Cho et al. (2008) empirically examined the relationship between
firm's logistics capability, logistics outsourcing and its
performance in an e-commerce market environment. The authors argued that
e-commerce firms have a higher likelihood of creating a sustainable
competitive advantage and improving performance if they have strong
logistics capability. Their empirical findings suggested logistics
capability to positively impact firm performance. However, logistics
outsourcing shared a negative impact on firm performance. Studies have
also explored the direct contribution of logistics capabilities to
competitive advantage. Sandberg and Abrahamsson (2011) explored the link
between operational and dynamic logistics capabilities and sustainable
competitive advantage. Based on case study of two Swedish retail
companies; the study concluded that logistics processes and IT systems
are valuable, rare and inimitable resources for any firm and can
contribute to competitive advantage for the same. Studies have also
explored the interface of logistics capabilities and supply chain
capabilities. As Mentzer et al. (2004) pointed logistics, as an integral
of supply chain management; accordingly logistics capabilities must
contribute for developing supply chain capabilities. Based on an
extensive literature review of logistics capabilities and supply chain
agility; Gligor and Holcomb (2012) argued that logistics capabilities of
individual firms must be integrated at the supply chain level for
developing supply chain agility.
Now in the current investigation, we adopt Mentzer's et al.
(2004) classification of logistics capabilities as it is the most
popular and acceptable classification in supply chain management studies
and it covers the dominant logistics capabilities (Esper et al. 2007;
Gligor, Holcomb 2012).
1.3. Logistics integration
Specific logistics process and practices need to be unified to
ensure undisrupted flow of materials from suppliers to customers (Stock
et al. 2000). These also ensures the availability of the right quantity
of good at the required place at the appropriate hour; thereby enhancing
the value proposition across each stage in the value stream (Caputo,
Mininno 1998). Industrial firms often have time and space utilities made
being available through efficient logistics integration (La Londe 1983;
Flynn et al. 2010). The growing competition in the market place have
urged firms to increase and improve their operational activities and
processes. In addition, firms have felt the need to integrate their
operations and dominant activities with those of their key suppliers and
distributors within the supply chain. This is because suppliers
contribute greatly in building and delivering the final value to the
customer in the value chain through improved product quality, better
inventory management and reduced delivery times. Therefore logistics
integration is characterized with well-coordinated flow of materials
from suppliers; this in turn results the focal firm to have a smooth
production process (Frohlich, Westbrook 2001). A direct consequence of
this is the elimination of the intangible boundary existing between the
focal firm and its suppliers (Stock et al. 2000; Flynn et al. 2010).
Other direct benefits of effective logistics integration are also well
recognized e.g. reduced bullwhip effect; firms adopting lean production
systems etc. (Schonberger 2007). By and large, logistics integration
allows companies and their supply chain partners to act as a single
entity which would result in improved performance throughout the chain
(Tan et al. 1998).
Logistics integration also enables the firm to have the probable
gifts of vertical integration for e.g. quality, dependability, planning
and control and lower costs. A plethora of operational benefits are
incurred to the firm such as reduction in costs, lead time and risks
(Liu et al. 2005) along with improvement in sales, distribution,
customer services, and service levels (Seidmann, Sundararajan 1997) and
customer satisfaction (Kim 2009).
1.4. Supply chain innovation: a dynamic capability perspective
The popularity of the resource based view (RBV) has been widely
acknowledged in production and supply chain management (Allred et al.
2011). The RBV argues that a firm can attain sustained competitive
advantage through suitably deploying its resources and capabilities that
are often rare, valuable, not substitutable, and difficult to imitate
(Barney 1991). Further these resources and capabilities are viewed as
bundles of tangible and intangible assets that comprises for e.g. a
firm's management skills, its organizational processes and
routines, and the information and knowledge it controls (Barney et al.
2011).
Teece et al. (1997) proposed the dynamic capabilities theory as an
extension of the resource based view. The theory aims to understand how
firms use their dynamic capabilities to create and sustain a competitive
advantage by reacting positively to environmental uncertainties (Teece
2007). Helfat et al. (2007) defined dynamic capability as "the
capacity of an organization to purposefully, create, extend, and modify
its resource base". The resource base of an organization includes
its physical, human and organizational assets (Eisenhardt, Martin 2000;
Ambrosini, Bowman 2009). For developing SC Innovation, a firm must align
and realign its resources and capabilities in a suitable manner to match
its environment. Hence SC innovation can be conceptualized as a dynamic
capability as it is used for responding to environmental contingencies
through developing other supply chain capabilities viz. agility,
resilience etc. thereby providing an optimal performance.
Based on the above argument, the current study posits demand
management interface capability (DMC), supply management interface
capability (SMC), information management capability (IMC) and
coordination capability as essential logistic capabilities that must be
integrated to develop SC innovation. This is also essential as logistics
is a part of supply chain as highlighted in the fairly accepted
definition of logistics management, as offered by the Council of
Logistics Management (2003):
[FIGURE 1 OMITTED]
"Logistics Management is that part of Supply Chain Management
that plans, implements and controls the efficient, effective forward and
reverse flow and storage of goods, services and related information
between the point of origin and the point of consumption in order to
meet customer requirements".
This suggests that the various logistics capabilities must be
integrated suitably in order to develop any supply chain capability (for
e.g. supply chain innovation in this case). Supply chain innovation (as
the name implies), as a dynamic capability, extends beyond a single firm
and includes entire supply chain as unit of analysis. Also as supply
chain innovation imparts a firm the ability to address the uncertainties
in its environment positive; it must have some positive performance
implications. Figure 1 shows the proposed the research model.
In the above figures, it is proposed therefore that logistics
capabilities influence logistics integration which in turn influences
supply chain innovation. Lastly, supply chain innovation positively
influences firm performance. In the above diagram, SC innovation
represents supply chain innovation.
2. Hypotheses development
2.1. Demand management interface capability and logistics
integration
Demand Management Interface Capability ensures that the firm and
its supply chain are able to suitably manage the demands of its
customers. Morash et al. (1996) underscored demand management interface
capability as the ability of a firm to provide its customers with
differentiated products and services. In recent times, it's the
differentiated products and services that ensure the sustenance of a
firm. Also, a firm must be able to provide value added products and
services at the right time at the right place to its customers as the
same, after integration, will ensure greater responsiveness to customer
demands (Gligor, Holcomb 2012). However, the management of demand
patterns of customers in the marketplace effectively portrays that the
logistics activities are well integrated. Based on this we hypothesize
that:
H1: Demand management interface capability is positively associated
with logistics integration.
2.2. Supply management interface capability and logistics
integration
Supply Management Interface Capability aims for efficient supply of
raw materials from supplier to the manufacturer. Its main aim is to
reduce the costs in several spheres of day to day operation for a firm.
For e.g. it aims to minimize waste in inventory, enables the firm to
respond to demand fluctuations with reduced distortion of the order
cycle process and optimally utilizes resources for enabling postponement
speculation, modularization and standardization (Esper et al. 2007).
This portrays that supply management interface capability aims for
increasing responsiveness when properly integrated. A higher level of
supply management interface capability automatically results in
integration of logistics activities through seamless connection between
suppliers and the manufacturer. Accordingly we hypothesize:
H2: Supply management interface capability is positively associated
with logistics integration.
A firm managing efficient and timely supply of its raw materials
from its key suppliers will be in a much better position to manage
ultimately its customer's demands in the market. Therefore, higher
the supply management capability, greater is the demand management
capability for a firm. Hence we posit that:
H3: Supply management interface capability is positively associated
with demand management interface capability.
2.3. Information management capability and logistics integration
As pointed out by Closs et al. (1997) and Mentzer et al. (2004),
this capability aims for effective collection, storage and distributing
of routine and strategic information both internally and externally.
Since managing demand effectively necessitates availability of demand
information from the customers as well as the demand trend prevailing in
the current market; hence information management capability is critical
and affects demand management interface capability positively. Also a
firm must have information about its supplier's inventory position,
tentative delivery schedules and any change or problem in allied
matters. Similarly, the supplier should also be in a position to obtain
firsthand knowledge of production requirements. Hence, information
management capability enhances the way a firm can manage its upstream
operations. This concludes that information management capability must
have a positive impact on demand management interface capability and
supply management interface capability. Accordingly we hypothesize that:
H4: Information management capability is positively associated with
demand management interface capability.
H5: Information management capability is positively associated with
supply management interface capability.
Also a firm having effective information sharing capabilities both
upstream and downstream portrays the optimal integration of several
dominant logistics activities and capabilities. This indicated that
information management capability must have a positive impact on
logistics integration. Hence we hypothesize that:
H6: Information management capability is positively associated with
logistics integration.
2.4. Moderating role of coordination capability
Coordination capability ensures that the different logistics
activities in a supply chain are well synchronized (Gligor, Holcomb
2012). Different parties in a supply chain generally don't possess
adequate knowledge of each other's skills, assets, strengths etc.
Therefore this cognitive limitation prohibits supply chain members from
effectively align their individual logistics capabilities with those of
their focal firm. Hence, in line with Gligor, Holcomb (2012), we argue
that the effectiveness of this logistics integration of individual
logistics capabilities of supply chain members with their focal firm
depends greatly on the ability of different entities to coordinate their
activities and capabilities. Accordingly, we posit that coordination
capability moderates the relationship between each logistic capability
and logistics integration. This leads us to our next segment of
hypotheses:
H7a: Coordination capability positively moderates the relationship
between demand management interface capability and logistics
integration.
H7b: Coordination capability positively moderates the relationship
between information management capability and logistics integration.
H7c: Coordination capability positively moderates the relationship
between supply management interface capability and logistics
integration.
2.5. Logistics integration and supply chain innovation
Logistics integration results in well-coordinated flow of raw
materials from a firm's key suppliers to its production site and
then distributing finished goods to the final consumer. Supply chain
innovation aims for efficient addressing of the environmental needs for
e.g. responding to customer dynamic requirements profitably or
mitigating a disruptive event (Khan et al. 2012). Therefore, a
well-planned and coordinated flow of materials along the value chain
will help the supply chain entities to prepare well for contingencies
(Cao, Zhang 2011). Hence this increases the overall ability of the value
chain to respond to threats and contingencies (Kim, Lee 2010).
Accordingly, we argue that improved logistics integration in a supply
chain will increase its ability to address environmental dynamism more
effectively. Therefore, we hypothesize that:
H8: Logistics integration is positively associated with supply
chain innovation.
2.6. Supply chain innovation and firm performance
The main tenet of dynamic capabilities theory argued in favor of
combining resources and capabilities owned by a firm in appropriate
manner for developing special capabilities that can quickly adapt to
environments (Teece 2007). Therefore within the context of dynamic
capabilities, we are positing supply chain innovation as a dynamic
capability developed through logistics integration of logistics
capabilities. Dynamic capabilities are therefore built and not acquired;
and this development is located in the efficient synchronization of
organizational processes. Hence logistics integration of capabilities of
firms within a supply chain suits the criteria of dynamic capabilities
(Teece 2007); it is a higher-level capability, it is dedicated to the
modification of operating routines, it facilitates resource
reconfiguration and helps firms respond in a timely and effective manner
to market volatility and supply uncertainties (Gligor, Holcomb 2012).
Dynamic capabilities can result in competitive advantage because their
quick adaptive ability to match their environment (Ponomarov, Holcomb
2009; Teece et al. 1997). This becomes possible through harnessing their
resources and capabilities in a suitable manner so as to derive the
optimal performance in a given environmental setting. Therefore,
resource based view's dynamic capabilities perspective, logistics
integration of capabilities can result in optimal performance for a
firm.
[FIGURE 2 OMITTED]
Supply chain studies argued in favor of creating a sustained
competitive advantage through integration of operations. For e.g. Cho et
al. (2008) in their empirical exploration found a positive effect of
logistics capability on firm performance. Flynn obtained a positive
effect of integrating internal and external operations across the supply
chain of a firm on its performance. In a similar context, Prajogo and
Olhager's (2012) findings also empirically proved that logistics
integration has a linkage with firm performance.
The current investigation explores firm performance from a service
perspective. Stank et al. (2003) argued to measure service performance
across two dimensions: operational and relational. The operational
elements are indicated to be "the activities performed by service
providers that contribute to consistent quality, productivity, and
efficiency." The relational elements are captured as
"activities that enhance the service firm's closeness to
customers, so that firms can understand customer needs and expectations
and develop processes to fulfill them" (p. 430). While operational
performance emphasizes reliability and cost dimensions of service;
relational performance reflects responsiveness, assurance and empathy.
Thus in accordance with the dynamic capabilities agenda; we hypothesize
that supply chain innovation (a dynamic capability) developed through
logistics integration will result in positive firm performance.
Therefore it is suggested that:
H9: Supply chain innovation is positively associated with
operational performance.
H10: Supply chain innovation is positively associated with
relational performance.
Figure 2 summarizes the above hypotheses in a theoretical model.
Thus the above theoretical model portrays the proposed hypotheses.
As shown in the diagram, H1 portrays a positive influence of demand
management capability on logistics integration; H2 shows a positive
influence of supply management capability on logistics integration; H3
shows a positive influence of supply management capability on demand
management capability; H4 & H5 posits a positive influence of
information management capability on demand and supply management
capabilities respectively. H6 shows the positive influence of
information management capability on logistics integration. H7a, H7b and
H7c show the moderating role of coordination capability on each of the
proposed linkages. H8 shows the positive influence of logistics
integration on supply chain innovation. Finally, H9 and H10 show the
positive influence of supply chain innovation on operational performance
and relational performance respectively. In the above diagram, SC
innovation represents supply chain innovation. Further, in each of the
logistics capabilities "mgmt" stands for
"management".
3. Methodology
3.1. Sample and data collection
The data was collected through a web based electronic survey. The
survey instrument was pretested by administering it to a small sample of
supply chain managers drawn from a contact list that was purchased from
an Indian Marketing Research Firm (the firm wanted to remain anonymous).
A few of the measurement items were modified based on the feedback
received from this sample in the pretesting phase. The final set of
respondents was chosen randomly from the aforesaid contact list. The
list comprised of logistics, supply chain and purchasing managers
working mostly in senior designations in the Indian subcontinent in
different industries. The unit of analysis was the firm and single
respondent per firm was chosen. The surveyed respondents were asked to
respond based on their expertise in their respective firms. The first
round of survey invitation was sent in the first week of March via
email. This was followed by two reminders, each within a gap of two
weeks after the preceding survey invitation. A total of 714 emails were
sent out. Out of these, 49 emails were returned as undeliverable. 182
partially complete responses were received, giving a response rate of
27.36% (182/665). However, for the final analysis we retained only
complete responses. Thus, the final sample size was 169. We tested for
the non-response bias by comparing the early and late respondents
(Armstrong, Overton 1977). There were no significant mean differences
between these two groups on key measures such as firm size and industry
affiliation.
3.2. Survey instrument
All the constructs used in the model have established scales for
measurement and hypothesis testing. The measures were suitably adapted
(wherever needed) to suit the context. A total of 29 survey items (shown
in Appendix-1) were used to measure independent, dependent and
moderating variables in the study.
3.2.1. Independent & dependent variables
The study has a total of eight factors viz. demand management
interface capability, information management capability, supply
management interface capability, coordination capability, logistics
integration, supply chain innovation, operational performance and
relational performance. Demand management interface capability was
measured using four items that enquired respondents if their firm can
efficiently satisfy their customer needs; can provide differentiated
products and services and can distribute its product as per customer
needs. The items for measuring demand management interface capability
were suitably adapted from Mentzer et al. (2004). Information management
capability were measured with four items that enquired respondents if
their firm can effectively share operational information among its
various departments; maintains an integrated data base for information
sharing; possess adequate systems and technology for detecting,
capturing and maintaining timely data. The items for measuring
information management capability were suitably adapted from Zhao et al.
(2001) and Mentzer et al. (2004). Supply management capability was
measured with four items that enquired the respondents if their firm has
its logistics operations synchronized with that of its suppliers; if the
firm pursues programs for developing its suppliers and if it has
enhanced flexibility through collaboration with its suppliers. The items
for measuring supply management interface capability were suitably
adapted from Zhao et al. (2001) and Mentzer et al. (2004). Logistics
integration was measured with four items that enquired respondents if
their firm's internal logistics activities are closely coordinated;
their logistics integration is efficiently supported with excellent
distribution, transportation and warehousing facilities; if the inbound
and outbound distribution of goods is well integrated. The items for
measuring logistics integration were suitably adapted from Prajogo and
Olhager (2012).
As supply chain innovation is relatively new, hence we thoroughly
investigated the literature and develop our measurement items for supply
chain Innovation. The measurement scale for supply chain innovation
therefore resulted from a culmination of literature search and
adaptation of innovation items from Flint et al. (2008) and Lee et al.
(2011). Supply chain innovation in line with its definition must
encompass innovation of the core processes and technology. Accordingly,
the supply chain innovation scale (thus developed) enquired executives
if their supply chain have the formal new product or service development
process. It further enquired if their supply chain monitors new idea
generation and percentage of implemented new ideas that are successful
in case of product and services. Finally, it asked if their supply chain
focuses on new technological innovation and process innovation.
Respondents were asked to indicate their choice on a Likert scale of 1-7
where "1" indicates "strongly disagree" and
"7" indicates "strongly agree". Operational
performance was measured with three items that enquired the respondents
if their firm can deliver accurate, undamaged orders every time and able
to meet its delivery deadlines successfully. The items for measuring
operational performance was suitably adapted from Gligor and Holcomb
(2014). Relational performance was measured with four items that
enquired the respondents if their firm develops formal relationships
with its suppliers; exchanges recommendations with its suppliers for
continuous improvement; knows its supplier's needs and help its
suppliers in executing important tasks. The items for measuring
relational performance was suitably adapted from Gligor and Holcomb
(2014). All the measurement items were operationalised on a 1 to 7
Likert scale (1 = Strongly Disagree; 4 = Neutral and 7 = Strongly
Agree).
3.2.2. Moderating variable
In the proposed model, coordination capability was the moderating
variable. Coordination capability was measured with three indicators
that enquired respondents if their firm can effectively coordinate their
activities and processes with that of its key suppliers. The items for
measuring coordination capability were suitably adapted from Mentzer et
al. (2004) and Gligor and Holcomb (2012). Respondents were asked to
indicate their choice on a Likert scale of 1-7 where "1"
indicates "strongly disagree" and "7" indicates
"strongly agree".
4. Results of hypotheses testing
4.1. Scale reliability
The scale reliability of the measurement items were tested using
Exploratory Factor Analysis (EFA) and Cronbach's alpha
coefficients. The EFA on our data presented us with clean factors after
we remove three problematic items SMC-2, LI3 and EU-4.The remaining
items loaded on appropriate factors. EFA showed that one component was
extracted for each variable based on Eigen values greater than one. The
results portrayed high communalities showing that the majority of the
measures variance was being explained by the constructs and indicated
item appropriateness (Pedhazur, Schmelkin 2013). The Cronbach's
alphas for the scales were as following: demand management capability
(0.794), information management capability (0.823), supply management
capability (0.866), coordination capability (0.817), and logistics
integration (0.781), SC innovation (0.834), operational performance
(0.765) and relational performance (0.819). Thus, all the
Cronbach's alpha values are higher than the cutoff value of 0.70 as
suggested by Nunnally (1978). The Cronbach's alpha values of the
above scales demonstrate significant confidence regarding the
scales' reliability. Table 1 shows the descriptive statistics and
correlations.
As seen from Table 1, none of the correlations are high enough to
signify the presence of multi-collinearity. Hence we can proceed for
hypotheses testing.
4.2. OLS estimation results
Table II presents the results of our hypotheses testing. The
hypotheses were tested using multiple regression analysis. In Table II,
Model 1 represents the result of the hypotheses H1, H2 and H6. H1
posited a positive impact of demand management interface capability on
logistics integration. The corresponding coefficient in Model-1 is
positive and significant (0.247,p < 0.01) supporting H1. H2 predicted
a positive influence of supply management interface capability on
logistics integration. The corresponding coefficient in Model-1 is
positive and significant (0.112, p < 0.05) thereby supporting H2. H6
posited a positive influence of information management capability on
logistics integration. The corresponding coefficient in Model-1 is
positive and significant (0.179, p < 0.01) providing support for H6.
Model-2 represents the result of our hypotheses H7a, H7b and H7c.
H7a predicted a positive interaction between coordination capability and
demand management interface capability in affecting logistics
integration. The corresponding coefficient in Model-2 is positive and
significant (0.137, p < 0.05) thereby supporting H7a. Again, H7b
posited a positive interaction between coordination capability and
information management capability in influencing logistic integration.
The corresponding coefficient in Model-2 is positive and significant
(0.157, p < 0.01) thereby supporting H7b. Further, H7c predicted a
positive interaction between coordination capability and supply
management interface capability in affecting logistics integration. The
corresponding coefficient in Model-2 is positive and significant (0.84,
p < 0.05) thereby supporting H7c.
Model-3 represents the results for our hypotheses H3 and H4. H3
posited a positive influence of supply management capability on demand
management capability. The corresponding coefficient in Model-3 is
positive and significant (0.317, p < 0.05) supporting H3. H4 posited
a positive influence of information management capability on demand
management capability. The corresponding coefficient in Model-3 is
positive and significant (0.249, p < 0.05) thereby providing support
H4.
Model-4 represents the result for our hypothesis H5 that predicted
a positive influence of information management capability on supply
management interface capability. The corresponding coefficient in
Model-4 is positive and significant (0.614, p < 0.01). Therefore, H5
is supported. Model-5 represents the result of our hypothesis H8 that
predicted a positive influence of logistics integration on SC
innovation. The corresponding coefficient in Model-5 is positive and
significant (0.517, p < 0.01) thereby supporting H8. Model-6
represents the result of our hypothesis H9 that posited a positive
influence of SC responsiveness on operational performance. The
corresponding coefficient in Model-6 is positive and significant (0.541,
p < 0.01) thereby supporting H9. Again, Model-7 represents the result
of our hypothesis H10 that posited a positive influence of SC
responsiveness on relational performance. The corresponding coefficient
in Model-7 is positive and significant (0.473,p < 0.01) thereby
supporting H10. Table 3 presents a summary of the hypotheses, model
reference and findings.
5. Managerial implications
Our study has several implications for managers, practitioners and
academicians. The study has investigated the importance of logistics
capabilities in developing supply chain capability (e.g. supply chain
innovation) and its impact on firm performance. Theoretically, the study
has extended the usage of dynamic capability theory in testing
logistics-supply chain relationships in terms of capabilities. Further
the study have empirically underscored the dominant logistics
capabilities and their respective importance (can be evaluated through
path coefficients in the model) in generating supply chain innovation.
Dynamic capabilities are such capabilities that can adjust themselves to
situational needs and hence is the supply chain innovation; this helps a
firm to gain new markets and wipe out competitive barriers through
launching of new products and services (Teece et al. 1997).
The study suggests managers to invest resources for enhancing
logistics capabilities as the same would develop dynamic capabilities
e.g. supply chain innovation that would help them to sustain their
position in the increasingly competitive marketplace. The study has
underscored that a firm that is able to manage its demand side
operations will be able to integrate its logistics capabilities more
effectively; thereby helping in logistics integration (Gligor, Holcomb
2012).
Secondly, the study has urged managers to invest for newer
technologies and invest simultaneously for latest hardware and software.
This will lead to real-time and efficient information sharing among the
supply chain entities leading to enhanced transparency and
buyer-supplier relationships. Further, efficient information sharing
leads to improved demand and supply management. Also managers should
understand that if they can effectively manage their supply of raw
materials; they will be more efficient and effective in meeting their
regular demand and also demand fluctuations suitably (Mentzer et al.
2004).
Third, managers must understand that each firm in the supply chain
should understand the importance of integration. This is required for
mutual benefits. Unless every entity in the supply chain is
collaborating with the other; effective integration of individual
capabilities at the supply chain will not happen. Hence managers should
organize frequent meetings and other informal sessions so as to interact
with its partners and exchange knowledge. This will lead to enhanced
idea exchange and will not only help in logistics integration; it will
also prepare the platform for supply chain innovation to take place.
Finally, using a service perspective the study has shown that
innovation in supply chains can effectively help a firm in improving its
performance both in operational and relational terms. From the
operational standpoint, supply chain innovation will lead to development
and implementation of newer technologies in the manufacturing unit or
production site. This will lead to training and up gradation of related
skills of human resources. Further it will help in optimizing production
process and smoothen out errors eliminating redundancies. This will
overall help in streamlining different processes both inside and outside
the firm. In relational term, supply chain innovation will help in
improving transparency and relationship with its different downstream
and upstream partners.
Lastly, the study has shown to both academicians and managers that
logistics is a critical part of supply chain operations and for a firm
that wants to develop essential supply chain capabilities; should
concentrate its efforts in improving its logistics operations and
capabilities. This will help ultimately to streamline the process
thereby increasing transparency and sharing of know-how and ideas
leading to supply chain innovation.
Conclusions
The empirical investigation sheds light on an important aspect:
development of supply chain innovation through integration of logistics
capabilities. Further, the influence of this supply chain innovation on
firm performance is also measured. As firms are in constant search of
newer strategies for gaining market share and winning customers over
their competitors; supply chain innovation is a dynamic capability that
helps a firm to organize its and resources and capabilities and adapt to
its dynamic environments. Customers are constantly welcoming newer
technologies and experimenting with the same. In this scenario, firms
must adapt
to these market needs through investing and developing its existing
infrastructure. This can happen only when the focal firm (i.e. the
manufacturing firm whose supply chain is being considered) coordinates
and collaborates with its value stream partners for investing and
implementing newer technologies, products and services. As shown by our
study, this can happen when the focal firm integrates its individual
logistics capabilities with those of its value chain partners at the
supply chain level (Gligor, Holcomb 2012).
But for successful integration to happen; contribution is required
from each of the dominant logistics capabilities viz. supply management
capability, demand management capability, information management
capability and coordination capability. There must be efficient and
effective mechanisms of exchanging relevant information among the value
stream partners for effective integration to take place. Further demand
and supply management must take place in a proactive space so as to
suggest different partners for effective collaboration. This will help
in unification of individual efforts and logistics capabilities. Also,
partners in a value chain must understand the importance of
coordination. As shown by our study; effective integration of other
logistics capabilities can be possible once the partners coordinate
suitably with each other. Finally, using a service perspective for
measuring firm performance; the study has empirically shown that supply
chain innovation optimizes both operational and relational performance
of the focal firm.
However, the current study suffers from few limitations like other
survey based research. Firstly, like other supply chain survey studies,
this one too gathers perception based data which may suffer from
subjectivity. Secondly, there must be other factors and theories that
can be used to explain the development of supply chain innovation in a
more effective empirical way. Since every study has its own limitations;
the contributions of this study too should not be ignored and
investigated with greater rigor in further studies in different
contexts.
http://dx.doi.org/10.3846/btp.2015.541
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APPENDIX 1
Survey Instrument
Kindly indicate your agreement or disagreement with the following
items as indicated: (1 = Strongly Disagree; 4 = Neutral and 7 = Strongly
Agree)
Constructs & Item Label Measurement Items
Source
Demand Mgmt. DMC1 Our firm efficiently satisfies the
Capability demands of our customer.
(Mentzer et
al. 2004) DMC2 Our firm has the ability to provide
unique value added services to our
customers.
DMC3 Our firm has the ability to provide
its customers with differentiated
pro ducts/services.
DMC4 Our firm has the ability to
distribute its products according
to customer requirements.
Information IMC1 Our firm effectively shares
Management operational information between
departments.
Capability IMC2 Our firm maintains an integrated
database to facilitate information
sharing.
(Zhao et al. IMC3 Our firm's logistics information
2001) systems capture and maintain timely
data.
(Mentzer et IMC4 Our firm has invested in technology
al. 2004) designed to facilitate
crossorganizational data exchange.
Supply SMC1 Our firm's logistical operations
Management can be synchronized to integrate
with supplier operations.
Capability SMC2 Our firm actively pursues business
(Zhao et al. relationships and programs targeted
2001) at maximizing supplier involvement.
(Mentzer et SMC3 Our firm has increased operational
al. 2004) flexibility through collaboration
with suppliers.
Coordination CC1 Our firm has the ability to
Capability coordinate the activities of
different departments.
(Mentzer et CC2 Our firm can coordinate the
al. 2004) different processes within the
firm.
(Gligor, CC3 Our firm has the ability to
Holcomb coordinate firm processes with that
2012) of key SC members.
Logistics LI1 Our firm's internal logistic
Integration activities are closely coordinated.
(Prajogo,
Olhager LI2 Our firm's logistics activities are
2012) well integrated with suppliers'
logistics activities.
LI3 Our logistics integration is
characterized by excellent
distribution, transportation,
and/or warehousing facilities.
LI4 The inbound and outbound
distribution of goods with our
suppliers is well integrated.
SC INNOV1 Our supply chain has formal new
Innovation product and service development
process.
(Flint et INNOV2 Our supply chain monitors and
al. 2008) documents new product and service
ideas.
(Lee et al. INNOV3 Our supply chain keeps track of
2011) successful product and service
ideas.
INNOV4 Our supply chain focuses on process
and technological innovation.
Operational OP1 Our firm delivers undamaged orders
performance each time.
(Gligor, OP2 Our firm delivers accurate orders
Holcomb at all times.
2014)
OP3 Our firm always meets deadlines as
promised to supply chain partners.
Relational RP1 Our firm develops formal
performance relationships with its supply chain
(Gligor, partners.
Holcomb
2014) RP2 Our firm exchanges recommendations
for continuous improvement with its
supply chain partners.
RP3 Our firm helps its supply chain
partners successfully perform
tasks.
RP4 Our firm knows its supply chain
partners' needs well.
Santanu MANDAL (1), Venkateswar RAO KORASIGA (2)
Department of Operations and IT, IFHE University, IFHE Campus,
Dontanapally, Shankerpalli Mandal,
RR District, Andhra Pradesh-501203, India
E-mails: (1) shaan.nitw@gmail.com (corresponding author); (2)
venkatkorasiga@ibsindia.org
Received 16 October 2014; accepted 20 May 2015
Dr. Santanu MANDAL is currently an Assistant Professor in the
Department of Operations & IT at IBS, Hyderabad. He obtained his PhD
degree from IFHE University. He was also the Visiting Research Scholar
at Spears School Business under Oklahoma State University, USA. His
research interests include but are not limited to operations management,
quantitative research and supply chain management.
Dr. Venkateswar RAO KORASIGA is currently an Associate Professor in
the Department of Operations & IT at IBS, Hyderabad. He has
extensively worked in the areas of supply chain management and project
management in the industry sectors. His research interests include but
are not limited to supply chain management, operations management and
IT.
Caption: Fig. 1. Research model
Caption: Fig. 2. Theoretical model
Table 1. Descriptive statistics and correlations
Variable * Mean Std. Dev. 1 2
1 Demand Mgmt. capability 5.14 0.34 n. a.
2 Information Mgmt. capability 4.96 0.29 0.41 ** n.a.
3 Supply Mgmt. capability 5.02 0.55 0.27 * 0.23 *
4 Coordination capability 4.88 0.82 0.33 * 0.11 **
5 Logistics integration 5.36 0.47 0.17 ** 0.27 *
6 SC Innovation 5.24 0.73 0.22 * 0.09 *
7 Operational performance 5.07 0.38 0.14 * 0.31 *
8 Relational performance 4.91 0.27 0.28 * 0.26 *
Variable * 3 4 5
1 Demand Mgmt. capability
2 Information Mgmt. capability
3 Supply Mgmt. capability n.a.
4 Coordination capability 0.19 * n.a.
5 Logistics integration 0.08 * 0.33 * n.a.
6 SC Innovation 0.13 ** 0.37 * 0.25 *
7 Operational performance 0.24 * 0.12 ** 0.14 **
8 Relational performance 0.32 * 0.10 * 0.21 *
Variable * 6 7 8
1 Demand Mgmt. capability
2 Information Mgmt. capability
3 Supply Mgmt. capability
4 Coordination capability
5 Logistics integration
6 SC Innovation n.a.
7 Operational performance 0.13 * n.a.
8 Relational performance 0.39 * 0.16 * n.a.
Notes: * p < 0.05; ** p < 0.01; *** p < 0.001
Table 2. Results of OLS estimation
Model Independent variables Dependent variable B
1 Constant 4.27 *
Demand Mgmt. capability Logistics integration 0.247 **
Information mgmt. (Main effects model 0.179 **
capability for logistics
Supply Mgmt. capability integration) 0.112 **
Coordination capability 0.376 **
2 Constant 3.031 *
Demand Mgmt. capability Logistics integration 0.219 *
Information mgmt. (Full model for 0.162 *
capability logistics
Supply Mgmt. capability integration) 0.104 *
Coordination capability 0.323 *
Coordination cap. * 0.137 *
demand Mgmt. cap.
Coordination cap. * 0.157 **
info. Mgmt. cap.
Coordination cap. * 0.84 *
supply Mgmt. cap.
3 Constant 4.226 *
Info Mgmt. capability Demand Mgmt. 0.249 *
Supply Mgmt. capability Capability 0.317 *
4 Constant 5.904 *
Info. Mgmt. capability Supply Mgmt. 0.614 **
capabiity
5 Constant 2.309 *
Logistics integration SC innovation 0.517 **
6 Constant 4.905 *
SC innovation Operational 0.541 **
performance
7 Constant 4.369 **
SC innovation Relational 0.473 **
performance
Model Independent variables t-value [R.sup2]
1 Constant 23.190 0.212
Demand Mgmt. capability 7.298
Information mgmt. 7.112
capability
Supply Mgmt. capability 5.709
Coordination capability 9.004
2 Constant 34.371 0.167
Demand Mgmt. capability 6.517
Information mgmt. 6.321
capability
Supply Mgmt. capability 8.114
Coordination capability 8.492
Coordination cap. * 6.552
demand Mgmt. cap.
Coordination cap. * 7.114
info. Mgmt. cap.
Coordination cap. * 6.204
supply Mgmt. cap.
3 Constant 24.198 0.334
Info Mgmt. capability 3.141
Supply Mgmt. capability 4.003
4 Constant 19.580 0.214
Info. Mgmt. capability 8.674
5 Constant 26.173 0.159
Logistics integration 6.142
6 Constant 24.001 0.276
SC innovation 6.016
7 Constant 6.147 0.294
SC innovation 4.018
Model Independent variables Adj. [DELTA]
[R.sup.2] [R.sup.2]
1 Constant 0.157 n. a.
Demand Mgmt. capability
Information mgmt.
capability
Supply Mgmt. capability
Coordination capability
2 Constant 0.141 0.045 *
Demand Mgmt. capability
Information mgmt.
capability
Supply Mgmt. capability
Coordination capability
Coordination cap. *
demand Mgmt. cap.
Coordination cap. *
info. Mgmt. cap.
Coordination cap. *
supply Mgmt. cap.
3 Constant 0.291
Info Mgmt. capability
Supply Mgmt. capability
4 Constant 0.187
Info. Mgmt. capability
5 Constant 0.103
Logistics integration
6 Constant 0.249
SC innovation
7 Constant 0.266
SC innovation
Note: * p < 0.05; ** p < 0.01; *** p < 0.001 coefficients
are standardized.
Table 3. Summary of hypotheses testing
Hypotheses Statement Referred Result
Model
H1 Demand management Model-1 Supported
capability
positively
influences logistics
integration
H2 Supply management Model-1 Supported
capability
positively
influences logistics
integration
H3 Supply management Model-3 Supported
capability
positively
influences demand
management
capability
H4 Information Model-3 Supported
management
capability
positively
influences demand
management
capability
H5 Information Model-1 Supported
management
capability
positively
influences supply
management
capability
H6 Information Model-1 Supported
management
capability
positively
influences logistics
integration
H7a Coordination Model-2 Supported
capability
positively moderates
relationship between
demand management
capability and
logistics
integration
H7b Coordination Model-2 Supported
capability
positively moderates
relationship between
information
management
capability and
logistics
integration
H7c Coordination Model-2 Supported
capability
positively moderates
relationship between
supply management
capability and
logistics
integration
H8 Logistics Model-5 Supported
integration
positively
influences SC
innovation
H9 SC innovation Model-6 Supported
positively
influences
operational
performance
H10 SC innovation Model-7 Supported
positively
influences
relational
performance
