SCM 502_ASU_ASSIGNMENT WEEK 1_THE EFFECT OF SUPPLY CHAIN LEARNING ON DYNAMIC CAPABILITY AND ITS IMPACT ON OPERATIONAL CAPABILITY

THE EFFECT OF SUPPLY CHAIN LEARNING ON DYNAMIC

CAPABILITY AND ITS IMPACT ON OPERATIONAL CAPABILITY

AND SUPPLY CHAIN PERFORMANCE

ARIZONA STATE UNIVERSITY

SCM 502 - OPERATIONS AND SUPPLY CHAIN MANAGEMENT

SPRING 2024

Introduction:

Recent developments in globalization, technological change, and rapidly changing

markets have made it difficult for companies to maintain their superior competitive position.

Competing successfully in a competitive market environment requires companies to

demonstrate responsiveness and product innovation while making optimal use of their

internal and external competencies. One of the ways that companies demonstrate is dynamic

capabilities (Aslam & Azhar, 2018).

Dynamic capability is an extension of the resource-based view theory and explains

how companies achieve sustainable competitive advantage (D. J. Teece, 2007). Dynamic

capability is the ability to constantly integrate and reconfigure resources to gain competitive

advantage under a changing environment. The term dynamic refers to the ability to cultivate

competencies that match the changing environment; the term capability emphasizes the

adaptation, integration, and reconfiguration of both internal and external organizational

resources in response to environmental changes (Chien & Tsai, 2012).

Dynamic capabilities have become one of the most important views in the strategic

management literature in recent times (Schilke, 2014). Dynamic capabilities help companies

detect changes in the market and recognize market opportunities. Dynamic capabilities also

help capitalize on these market opportunities through the deployment and redeployment of

company resources (Aslam & Azhar, 2018). Dynamic capabilities create differences in a

company's competitive position in the same industry and usually cannot be imitated by other

companies because these are formed by organizational processes based on the history and

management of the organization (D. J. Teece, 2014).

Companies need internal and external dynamic capabilities to achieve more

environmentally friendly products, they work together with the company's supply chain

activities (Kιrcι & Seifert, 2015). Supply chains tend to have more dynamic changes due to

reasons such as constant changes in customer behavior, or significant influence from

competing companies (Masteika & Čepinskis, 2015). Supply chain strategy can provide a

competitive advantage when it aims to achieve long-term development in technology,

machinery, and process management.

In accordance with the concept of dynamic capability, supply chain management

examines management strategies to adapt to sudden changes, risks and opportunities in the

market and how to influence and control their environment to achieve competitive

advantage. Studies show that the characteristics of supply chain management practices

include long-term relationships, top management support, cooperation along the supply

chain, supplier development, and enhanced communication (Beske, 2012).

Competition is driving managers to devote considerable attention to supply chain

management (SCM). SCM is a key strategic factor to improve the effectiveness of the

company and better realization of the company's goals. Companies are required to choose

supply chain and logistics in their operations. Most companies seek to improve the

efficiency and effectiveness of the supply chain. Improving the company's business

performance can be done by supplier cooperation, delivery performance, customer service

and reducing logistics costs (Purnomo & Santosa, 2016).

A framework combining supply chain management and dynamic capabilities was

proposed for the first time by Beske (2012). In the framework, dynamic capabilities consist

of five characteristics in supply chain development: knowledge assessment involving access,

supply chain partner development, new capability development, supply chain control and

supply chain re-conceptualization focusing on new partnerships (Kιrcι & Seifert, 2015). The

dynamic capabilities perspective in the resources based theory (RBV) view, where the firm

is understood as a collection of resources, builds on the idea that the organization must

develop a learning process to adapt to environmental changes. Dynamic capabilities are

based on different organizational processes derived from the firm's specific asset position

and shaped by its path. Dynamic capabilities allow companies to renew and better utilize

their resources and have the potential to improve organizational performance outcomes

(Hernández-Linares et al., 2018).

This research is a development of Aslam & Azhar's research (2018). The difference

between this research and Aslam & Azhar's research (2018) is the use of different research

objects. Aslam & Azhar's research (2018)

This study uses the object of SME research in Malaysia while this study uses manufacturing

SMEs in Yogyakarta. Aslam & Azhar's research (2018) examines the relationship between

dynamic capabilities and performance from a supply chain management perspective. The

results of this study are supply chain learning has a significant positive effect on supply

chain dynamic capabilities, supply chain dynamic capabilities have a significant positive

effect on supply chain learning, operational performance has a significant positive effect on

supply chain performance, and supply chain dynamic capabilities have a significant positive

effect on supply chain performance.

2.1

Previous Research

Aslam & Azhar's research (2018) examines the relationship between dynamic

capabilities and performance from a supply chain management perspective. The results of

this study are supply chain learning has a significant positive effect on dynamic supply

chain capabilities, dynamic supply chain capabilities have a significant positive effect on

supply chain learning, supply chain capabilities have a significant positive effect on supply

chain performance, and dynamic supply chain capabilities have a significant positive effect

on supply chain performance.

Research by Ju et al. (2016) tested and empirically analyzed the impact of supply

chain dynamic capabilities on operational performance, and the mediating effect of

technological innovation between dynamic capabilities and operational performance. This

study is based on empirical data collected from a survey of 206 small and medium-sized

enterprises in Korea. Structural equation modeling was used to test the research questions.

Results show that supply chain dynamic capabilities positively influence technological

innovation and operational performance of a firm. In addition, structural equation analysis

revealed that technological innovation acts as a partial mediator of the relationship between

supply chain dynamic capabilities and operational performance. In a dynamic and ever-

changing environment, the enforcement of dynamic capabilities in a sustainable supply

chain is important for technological innovation and o p e r a t i o n a l performance

improvement. Further investigation It is necessary to understand differences by industry,

company characteristics, and position in the supply chain.

Song & Choi's (2018) research examined dynamic capabilities as an antecedent of

GSCM, with the aim of proposing a causal relationship between dynamic capabilities and

GSCM. The results of this study indicate that implementing GSCM with dynamic

capabilities enables companies to achieve successful GSCM practices, and this in turn leads

to improved organizational performance.

Beske (2012) researched to discuss the relationship between dynamic capability and

supply chain and secondly, to develop a framework that integrates dynamic capability in

supply chain practice. This paper is conceptual in nature and is based on the theories of

supply chain management and dynamic capability. The results show that when dynamic

capability and supply chain are linked through similar environmental and organizational

conditions, it makes the application of dynamic capability concepts in the field of supply

chain a logical choice.

2.2

Foundation Theory

2.2.1

Management Theory Operations

These are some of the definitions of operational management, based on experts:

According to Heizer & Render (2016), operations management is a series of activities

that create value in the form of goods and services by converting inputs into outputs.

According to Evans & Coullier (2007), operations management is the science and art of

ensuring that goods and services are made and delivered successfully to customers.

According to Russell & Taylor (2011), operations management is the design, operation,

and improvement of productive systems.

According to Krajewski et al. (2007), operations management refers to the systematic

design, direction, and control of processes that transform inputs into services and

products for internal, as well as external customers.

According to Stevenson (2009), operations management is the management of systems

or processes that create goods and/or provide services.

Heizer & Render (2016) state that differentiation, low cost, and response can be achieved

when managers make effective decisions in 10 areas of operations managers. These are

collectively known as operations decisions. Operations management decisions that support

the mission and implement the strategy follow:

Design of goods and services. Designing goods and services determines much of the

transformation process. Cost, quality, and human resource decisions are often

determined by design decisions. Design usually determines the lower limit of cost and

the upper limit of quality.

Quality. Customer quality expectations must be defined and policies and procedures

established to identify and achieve that quality.

Process design and capacity. Process options available for products and services.

Process decisions commit management to technology specific, quality, human

resources, and maintenance. These capital expenditures and commitments will

determine much of the company's basic cost structure.

Location selection. Facility location decisions for manufacturing and service

organizations can determine the ultimate success of the company. Mistakes made at this

point can overwhelm other efficiencies.

Layout design. Material flow, capacity requirements, personnel levels, technology

decisions, and inventory requirements affect the layout.

Human resources and job design. People are an integral and costly part of the total

system design. Therefore, the quality of work life provided, the talents and skills

required, and the cost must be determined.

Supply chain management. These decisions determine what to do and what to buy.

Consideration is also given to quality, delivery and innovation, all at a satisfactory price.

Mutual trust between buyer and supplier or required for effective purchasing.

Inventory. Inventory decisions can be optimized only when customer satisfaction,

supplier, production, schedule, and human resource planning are considered.

Scheduling. A feasible and efficient production schedule must be developed; demands

on human resources and facilities must be determined and controlled.

10.

Maintainability. Decisions must be made regarding the desired level of reliability and

stability, and the system must be set up to maintain that reliability and stability.

11.

2.2.2

Resourced Based View Theory

Resource Based View Theory is a prominent theory in the field of strategic

management since the early 1990s. Mainly due to the superiority of this theory that

prioritizes the role of internal resources which when certain conditions are met will lead the

company to gain a competitive advantage and even a sustainable competitive advantage that

will lead to superior performance. Resources in general consist of tangible and intangible

resources. Intangible resources according to many researchers are strategic resources

because the resources that will bring the company is able to achieve competitive advantage

and sustainable competitive advantage (Mulyono, 2013).

RBV states that, whenever a firm's resources are valuable, rare, inimitable, and

irreplaceable, they establish a source of sustainable competitive advantage through the

implementation of value creation strategies that do not prove vulnerable to duplication by

competitors. RBV means that firms can capitalize on competitive advantage through

differentiated capabilities and appropriate resources, and these factors play a central role in

crafting business strategy (Ferreira & Fernandes, 2017).

2.2.3

Dynamic Capabilities

Companies face increasing legal and extra-legal demands to incorporate

environmental sustainability aspects in their business practices and supply chains (Reuter et

al., 2010). These demands change dynamically, requiring companies to adapt their

capabilities o v e r time, one of which is dynamic capabilities (Kιrcι & Seifert, 2015).

Dynamic capabilities were introduced by D. Teece & Pisano (1994) as a paradigm

that explains how firms gain and maintain competitive advantage. They state that resource-

based strategies that focus on the exploitation of firm-specific assets are insufficient in

supporting significant competitive advantage. They argue that timely responses and product

innovation are possible through the renewal of internal and external competencies, and

effective coordination. Furthermore, they state that dynamic capabilities are high-performing

internal routines found in the firm's processes, and conditioned by the firm's history.

D. J. Teece et al. (1997) further developed the framework by introducing the

concepts of internal and external replicability of competencies that support a firm's services

or products with a changing business environment. Eisenhardt & Martin (2000) argue that

dynamic capabilities as defined by Teece et al. (1997) are a source of competitive advantage,

but not necessarily a sustainable one. They distinguish the nature of dynamic capabilities

and learning mechanisms between moderately dynamic and high-speed markets.

Synthesizing existing literature, D. J. Teece (2007) provides a more general

framework of dynamic capabilities. He divides dynamic capabilities into three foundations:

sensing, seizing opportunities, and transforming them. Sensing is the ability to recognize

new opportunities. Sensing involves scanning and interpreting the internal and external

environment, and creating opportunities. Seizing opportunities is the ability t o address

opportunities. Opportunity seizing involves maintaining and improving complementary

competencies and assets such as corporate structure, procedures, design, and incentives.

Transformation is the ability to recombine and reconfigure assets and organizational

structures as the firm grows, and as the external environment changes. Transformation

involves continuous alignment and realignment of specific tangible and intangible assets.

2.2.4

Supply Chain Management

2.2.4.1

Definition

Daft (2002) defines supply chain management as a term for managing the chain of

suppliers and buyers, which includes all stages of processing from the purchase of raw

materials to the distribution of finished goods to end consumers. Supply chain management

is the integration of the activities of procuring materials and services, converting them into

semi-finished goods and final products, and delivering them to customers (Heizer & Render,

2016).

Levi et al. (2000) state supply chain management as an approach that is applied to

bring together suppliers, entrepreneurs, warehouses, and other storage places (distributors,

retailers, and retailers) efficiently, so that products can be produced and distributed in the

right amount, right location, and right time to reduce costs and meet customer needs.

2.2.4.2

Supply Chain Learning

There are two important components involved in learning; the first involves the

accumulation and development of a core knowledge base and core competencies that

differentiate the firm from others and offer the potential for competitive advantage. The

second is the long-term development of the ability to learn and continuous improvement

throughout the organization (Bessant et al., 2003). Organizational learning is one of the most

important subjects to understand because of how critical it is to performance (Bessant et al.,

2003). Flint et al. (2008) extended this concept of organizational learning to inter-

organizational learning, where two or more companies in a supply chain interact as they

solve logistics and supply chain problems.

One form of corporate learning is supply chain learning. In the context of supply

chain learning this has interesting implications. Where the learning content is relatively

straightforward e.g. the adoption of well proven practices or the uptake and use of new

regulatory standards learning. Conversely where there are significant challenges then the

whole approach taken to the operation or management of the inter-firm relationship itself

challenges are likely to involve elements of multiple or generative learning and are much

more difficult to achieve (Bessant et al., 2003).

However, it is important to note that the requirements for the learning process of

supply chain management relationships indicate that the parties must basically have mutual

trust, commitment to long-term cooperation and willingness to integrate key business

processes. The next stage model for supply chain learning is leading to innovation. The set-

up stage should provide shared focus and motivation between supply chain partners. The

operations stage involves agreement on shared goals and targets that are developed into new

operating processes and new ways of working. To maintain momentum for the process, the

sustainability stage should deal with management processes that emphasize the need for

continuous learning such as measurement and benchmarking. Supply chain structures such

as supplier associations may have a role to play at this stage. Comparing this model with our

study, the driving force for further development is the voice of the customer, or more

specifically customer value insights, rather than measurement and benchmarking. (Flint et

al., 2008)

2.2.5

Dynamic Capability of the Supply Chain

The application of the dynamic capability view to strategic decisions in supply chain

management is becoming increasingly common. Dynamic capabilities in the supply chain

emerge when companies engage their employees in understanding customer requirements

and translating these requirements so that they are effectively communicated throughout the

supply chain (Aslam et al., 2018).

Aslam et al. (2018) divides supply chain dynamic capabilities into two parts, namely:

Supply Chain Agility

Swafford et al. (2006) argue that supply chain agility is the ability that enables the

supply chain to seize opportunities once they are sensed. Supply chain agility as a

fundamental capability needed to survive and thrive in a volatile environment, as it enables

flexible supply chain responses (Aslam et al., 2018). Building on this argument, Blome et al.

(2013) put forward the idea that supply chain agility is a dynamic capability capable of

positively influencing a firm's operational performance. Supply chain agility can also be

considered as an extension of agile manufacturing that focuses primarily on the firm.

Furthermore, supply chain agility is usually considered to expand the narrower concept of

supply chain flexibility ((Gligor & Holcomb, 2012; M. Stevenson & Spring, 2007).

Supply chain Adaptability

Supply chain adaptability refers to the ability of enterprises to reconfigure and

change the supply chain design according to expected market changes. Supply chain

adaptability is the willingness to reshape the supply chain when necessary, with no strings

attached with legacy issues or the way the chain has operated previously. Supply chain

adaptability is a property of the supply chain that enables members to cope with the

dynamics associated with the supply chain. Supply chain adaptability can be considered as a

dynamic capability resulting from a firm's ability to reconfigure resources at the firm level

and the supply chain level (Aslam et al., 2018).

2.2.6

Operational Capabilities

Operational capability has long been studied from an outcome perspective. Previous

researchers have operationalized capabilities in terms of performance outcomes, including

cost, quality, dependability, speed, and flexibility (Wu et al., 2012). This approach

highlights the relationship between operational capabilities and business objectives;

however, it does not provide much guidance on how to achieve optimal operational

capabilities (Wu et al., 2012).

This study encompasses this broader process perspective and views operational

capabilities as part of the organizational capabilities developed within the operations

management system (Wu et al., 2012). Therefore, Wu et al. (2012) used organizational

capability attributes to determine operational capability. Organizational capabilities stem

from complex social routines that determine the efficiency with which firms physically

transform inputs into outputs. This definition provides a starting point for understanding

operational capability and ultimately for developing our own definition of this construct. It

emphasizes two basic elements. First, organizational capabilities reside in corporate

structures and processes, corporate culture, and networks of employee and inter-

organizational relationships. Capabilities originate from different patterns of behavior that

are complex in nature and that involve both internal and external processes.

2.2.6 Supply Chain Performance

Performance measurement is one of the important factors for business

organizations. In the management control system in a business organization, performance

measurement is an effort made by management to evaluate the results of activities that have

been carried out by the accountability center. For this reason, performance measurement is

needed in order to build a plan and control to achieve the vision and mission of an

organization. Of course, the measurement of supply chain management performance must be

very concerned about how important the influence of the supply chain is on the company

(Tanaka & Nurcaya, 2018).

Performance appraisal is one way that management can fulfill its obligations to

funders and also to achieve the goals set by the company. Performance is a general term

used for part or all of the actions or activities of an organization in a period with reference to

a standard amount such as past or projected costs, on the basis of efficiency, responsibility

or management accountability and the like (Srimindarti, 2004).

2.3

Hypothesis Research

2.3.1

Supply Chain Learning and Dynamic Capability of Supply Chains .

Learning is an ever-present element of individual and organizational behavior.

Learning occurs mainly when displaying continuous change due to changes in the external

(technological) or internal (behavioral) environment through innovation (Dosi & Marengo,

2007). Learning sources include experience, interpretation of experience, and learning from

the experiences of others (Aslam & Azhar, 2018). Simon (1989) argues that the concept of

organizational learning is metaphorical because learning in organizations can only occur in

two ways; (1) by learning from its members, or (2) by new members joining who bring

knowledge from their previous organizations. However, there is also a collective view of

organizational learning. According to the collective view, organizational learning occurs

socially and cannot be reduced to individual members of the organization (Aslam & Azhar,

2018). Furthermore, knowledge gained through the process of learning is integrated into not

only individual members, but also into the routines that shape individual and organizational

behavior (Dosi & Marengo, 2007).

Learning contributes to the development of signature processes that lead to a

company's competitive advantage. These processes emerge through frequent communication

between supply chain members (D. J. Teece, 2014). Supply chain members form a value

stream whose competitiveness depends on the learning and development of the entire system

instead of one or a few links in the chain. Supply chain learning (SCL) refers to the extent to

which companies enjoy the process of learning together with supply chain partners (Flint et

al., 2008). Learning contributes to improved performance at the firm level as well as the

supply chain level (Aslam & Azhar, 2018). Previous research has shown that learning

contributes to the development of dynamic capability. Supply chain learning helps in

shaping and modifying capabilities to generate appropriate responses to market changes. We

therefore hypothesize that SCL will have an impact on the successful development and

deployment of dynamic capability.

2.3.2

Supply Chain Dynamic Capability and Operational Capability

Dynamic capabilities are understood as a company's ability to integrate, build, and

reconfigure internal skills and externally in a turbulent environment (D. J. Teece et al.,

1997). In this way, dynamic capabilities refer to the standardized and systematic state of the

collective activities of an enterprise. These capabilities can generate and modify company

routines and practices, seeking to improve organizational effectiveness (Bitencourt et al.,

2019).

According to Heizer and Render (2005), companies need to consider supply chain

issues to ensure that the supply chain supports the company's strategy. If the operations

management function supports the overall corporate strategy, then the supply chain is

designed to support the operations management strategy. Facilities and costs required to

meet consumer needs, with the aim of achieving minimum costs and maximum service

levels are all considered in supply chain management. Research by Li et al. (2006) states

that effective supply chain management has the potential to become a strategy to maintain

competitive advantage and improve organizational performance because current competition

is in competition between supply chain management used by companies.

2.3.3

Operational Capability and Supply Chain Performance

A company's operational capability is its ability to deliberately combine its resource

base in a way that enables the organization to perform ongoing tasks to transform inputs into

outputs (Coltman & Devinney, 2013). Operational capability is necessary for problem

solving as well as performing daily activities (Zahra & Das, 1993). OC consists of both

explicit elements such as company resources and routines and tacit elements such as skills,

leadership systems, and know-how. Operational capability is fundamental to a company's

existence and can be a source of competitive advantage for a long time especially from the

perspective of developing countries (Aslam & Azhar, 2018).

Companies with good operational performance in the sense of being able to implement

flexibility in various ways, reduction of production lead time, production forecasting,

resource planning and cost savings and reduction of inventory levels will be able to improve

their company's SCM performance. A competitive supply chain in the market may be

characterized by efficient use of resources that will lead to lower product costs, better

product quality, faster response and lead to higher market share. Through SCM practices, it

will provide an opportunity for companies to increase their sales.

The results of research (Aslam & Azhar, 2018) prove that operational performance

has a positive effect on supply chain performance. Based on the description above, the

hypotheses of this study are

H3 : Operational Capability has a positive effect on Supply Chain Performance.

2.3.4

Supply Chain Dynamic Capability and Chain Performance Supply Chain

Process optimization currently has very little influence on the success of modern

companies. Much of it is influenced by a company's ability to sense market opportunities

and capitalize on these opportunities. Companies that focus on market learning about their

competitors, channel members, and customers aim to understand current and future events.

The stronger the market focus, the stronger the ability to collect, interpret and use market

information. After identifying new, potentially profitable opportunities, companies need to

capitalize on them through the design of new products, services or processes. This requires

companies to reconfigure their technological assets and capabilities and then invest in design

and technology when the time is right (Teece, 2007).

From a supply chain perspective, this requires the ability to not only handle

variations coming from the customer side but also variations caused by suppliers. This can

be achieved by sharing continuous information with supply chain partners about demand

and supply, establishing collaborative relationships with supply chain partners, delays,

maintaining inventories of small items that can cause bottlenecks, building up logistics

systems that can respond quickly to unforeseen events, and building teams that can create

and execute plans

contingency quickly (Lee, 2004).

3.1

Approach Research

This research approach uses quantitative methods. In this quantitative research,

researchers formulate new problems by identifying through hypotheses, namely temporary

answers to the formulation of research problems. Quantitative research methods are

approaches to empirical studies to collect, analyze, and display data in numerical rather than

narrative form.

3.2

Classification of Variables Research

Research variables are the object of research, or what is the point in a study

(Arikunto, 2010). The variables in this study are as follows:

Independent variables consisting of supply chain learning and supply chain dynamic

capabilities

Intervening variables consisting of operational capability

The dependent variable in this study is supply chain performance.

3.3

Operational Definition Variable

3.3.1

Chain Learning Supply

Organizational learning is one of the most important subjects to understand because

of how important it is for performance (Bessant et al., 2003) one of which is supply chain

learning. Supply Chain Learning is measured by six indicators namely (Flint et al., 2008):

Managers are constantly learning about ways to serve customers

Managers learn how to operate and service

Managers in our customer organizations learn to manage the business and work together.

Market and customer learning.

Employees and managers change their behaviors and processes

Employees and managers change attitudes about customers and serving customers

3.3.2

Dynamic Capability of the Supply Chain

The application of the dynamic capability view to strategic decisions in supply chain

management is becoming increasingly common. Dynamic capability in the supply chain

arises when companies engage their employees in understanding customer requirements and

translating these requirements so that they are effectively communicated throughout the

supply chain (Aslam et al., 2018). Supply chain dynamic capability is measured using two

dimensions namely (Aslam et al., 2018):

3.3.2.1

Supply Chain Agility

The supply chain agility indicators are as follows:

Quickly adapt services and/or products to new customer needs

React to new market developments quickly

React to significant increases and decreases in demand quickly

Customize product portfolio according to market needs

3.3.2.2

Supply Chain Adaptability

The indicators of supply chain adaptability are as follows:

find new supply bases and markets around the world

Evaluate end-consumer needs

Determine the company's product positioning in terms of technology cycle and product

life cycle

3.3.3

Operational Capabilities

Operational capability in terms of performance outcomes, including cost, quality,

dependability, speed, and flexibility (Wu et al., 2012). This approach highlights the

relationship between operational capability and business objectives; however, it does not

provide much guidance on how to achieve optimal operational capability (Wu et al., 2012).

Operational capability is measured using six indicators, namely (Wu et al., 2012):

operational cooperation

operational customization

operational responsiveness

operational improvement

operational innovation

operational reconfiguration

3.3.4

Supply Chain Performance

Performance measurement is one of the important factors for business organizations.

(Tanaka & Nurcaya, 2018). Supply chain performance is measured using five indicators,

namely (Sezen, 2008):

Ability to respond to and accommodate variations in demand, such as seasonality

Ability to respond to and accommodate periods of poor manufacturing performance

(machine breakdowns)

Ability to respond to and accommodate periods of poor supplier performance

Ability to respond to and accommodate periods of poor delivery performance

Ability to respond and accommodate new products, new markets, or new competitors

3.4

Instrument Test Research

3.4.1

Instrument Validity Test Research

Validity test is a measure that shows the level of validity of an instrument. In this

study, confirmatory factor analysis was used to determine the construct validity of the

survey items. This means how well the construct explains the variables under the construct

(Hair et al., 2010). In other words, whenever the correlation of items within the same

construct is relatively high said to have construct validity. Also, factor loadings or regression

weights and squared multiple correlations (SMC) of items significantly correlated with the

specified construct will also contribute to the understanding of construct validity.

Confimatory factor analysis provides a standardized loading factor of each indicator

on which the research variable is quantified from a set of statements known as manifest

variables. Standardized loading factors (regression weights) indicate the contribution of each

indicator to each research latent variable. According to Hair et al. (2010) a good

standardized loading factor of any latent measurement variable measured from manifest

variables should be above 0.5 and ideally 0.7 or higher. Data validity was also tested using

the Variance Extracted (VE) approach. The average percentage of Variance Extracted (VE)

is a specific Confirmatory Factor analysis that tests convergent validity. According to Hair et

al., (2010) a VE of 0.5 or higher as a rule of thumb is good, indicating adequate

convergence.

3.4.2

Test Reliability

Hair et al. (2010) define reliability as an assessment of the level of consistency

between multiple measurements of a variable. This study assessed the consistency of the

entire scale with Cronbach's alpha and the overall reliability of each productivity value

factor. All the resulting alpha coefficient values exceeded the 0.70 value suggested by Hair

et al. (2010). From the results of these Cronbach's alpha coefficient values, this

questionnaire is acceptable. In short, it is proven reliable. To validate the instrument, this

study also considers construct validation using analysis of moment structures software

(AMOS) with the maximum likelihood (ML) method to analyze the data.

3.5

Data Analysis Techniques

3.5.1

Analysis Descriptive

Descriptive statistical analysis techniques are statistics used to analyze data by

describing or describing the data that has been collected as it is without intending to make

general conclusions or generalizations (Sugiyono, 2011). This analysis is a description that

explains the identity of the respondent.

3.5.2

Structural Equation Model Analysis (SEM)

The research model will be analyzed using the Structural Equation Model (SEM),

using AMOS software. The reason for using SEM analysis is that the model being analyzed

is multilevel and relatively complex, so it will be very difficult to solve with the path

analysis method in linear regression and is able to test complex and multilevel hypotheses

simultaneously.

SEM is an analytical technique that allows complex and complicated relationships to

be estimated simultaneously. In simple terms, SEM provides an adequate and most efficient

estimation technique for a set of multiple and separate regression equations estimated

simultaneously. ((Ghozali, 2011).

Hair et. al. (2010) explain the seven steps of the data analysis process with SEM in

full as follows:

Step 1: Develop a theoretically based model

A model is a simplification of a complex problem for easy analysis. The model is

built based on relevant literature and the results of previous studies.

Step 2: Construct a path diagram

The model that has been built is then depicted in the form of a path diagram. At this

stage the research defines and establishes exogeneous and endogeneous constructs and then

connects them in the form of a path diagram. With this path diagram, it will be clear which

parts must be carried out conformatory tests, namely testing whether indicators can explain

latent variables and which parts must be hypothesized, namely testing the effect of all

exogenous variables on endogenous variables both directly and indirectly, and testing the

effect of endogenous on other endogenous variables.

Step 3: Convert flowchart into equation form

At this stage, researchers describe the flowchart of the research model in the form of

structural equations and measurement model specification equations.

Step 4: Selecting input matrix and model estimation

Because in this study what is tested is causality, the input used is covariance. The

steps of using inputs in SEM are as follows:

Measurement model estimation (confirmatory factor)

This measurement model is to test whether the indicators can significantly measure the

latent variables in the model.

Path analysis estimation

At this stage, we test the direct and indirect effects of exogenous variables on

endogenous variables and the effects of endogenous variables with other endogenous

variables.

Step 5: Forecasting model identification

This stage is to assess whether the structural model created is able to produce good

estimates. Signs of problems in this stage are:

The standard deviation for one or more model coefficients is very large.

The required information cannot be presented by the program.

The appearance of unnatural numbers. For example, there is a negative variance.

There is a very high correlation coefficient between the estimation coefficients.

Step 6: Evaluating the accuracy of model estimation

Model estimation can be tested if several assumptions of SEM use can be met.

Things that need to be seen are: sample size of at least 100 units; data is nomally distributed

and linearly patterned; evaluation of outliers by univariate and multivariate methods. If the

assumptions of SEM users can be met, then the next step is to conduct a goodness of fit test.

Step 7: Interpret and modify the model

The last step in the series of steps above is to interpret and modify the model if it

turns out that the resulting estimate does not have the expected level of prediction or has a

high level of residuals.

DATA ANALYSIS AND DISCUSSION

This chapter consists of descriptive analysis which contains descriptions of

respondents, as well as respondents' answers to each variable item. In addition, data quality

testing, data processing results and hypothesis testing, including analysis and interpretation

of results and discussion. Data that has been tested for validity and reliability is processed to

test the hypothesis. Furthermore, a discussion of the research results and findings is carried

out.

4.1

Analysis Descriptive

4.1.1

Description of Respondents Research

This section explains the descriptive data of respondents obtained from the survey.

Descriptive data is presented to see the profile of the research data and its relationship with

the variables used in this study. Supply Chain Learning and Supply Chain Capabilities .

The results of this study prove that the effect of supply chain learning on supply chain

capabilities is positively significant. Thus, the hypothesis stating that supply chain learning

has a positive effect on supply chain capabilities is accepted.

Learning is an ever-present element of individual and organizational behavior.

Learning occurs especially when displaying continuous change due to changes in the

external (technological) or internal environment (behavior) through innovation (Dosi &

Marengo, 2007). Learning sources include experience, interpretation of experience, and

learning from the experiences of others (Aslam & Azhar, 2018). Simon (1989) argues that

the concept of organizational learning is metaphorical because learning in organizations can

only occur in two ways; (1) by learning from its members, or (2) by new members joining

who bring knowledge from their previous organizations. However, there is also a collective

view of organizational learning. According to the collective view, organizational learning

occurs socially and cannot be reduced to individual members of the organization (Aslam &

Azhar, 2018). Furthermore, knowledge gained through the learning process is integrated into

not only individual members, but also in routines that shape individual and organizational