An Air Force Logistics Management Index for Effective

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An Air Force Logistics Management Index for effectiveaircraft operation

Kyung Bok Yoon, Hong Sik Kim, So Young Sohn *

Department of Information and Industrial Engineering, Yonsei University, 134 Shinchon-dong, Seoul 120-749, Republic of Korea

Received 15 February 2007; received in revised form 13 June 2007; accepted 22 August 2007

Abstract

Air power plays a critical role in modern war. In order to maintain the highest possible level of aircraft readiness, logis-tics management for aircraft operation must be conducted well. In this study, we use a Structural Equation Model (SEM)to develop an Air Force Logistics Management Index (ALMI) for effective aircraft operation. An individual ALMI ratingis estimated for various combinations of characteristics. It is expected that the proposed approach for ascertaining anALMI will be used as guidance for the development of aircraft logistics management systems of the Republic of KoreaAir Force (ROKAF). 2007 Elsevier Ltd. All rights reserved.

Keywords: Air Force Logistics Management Index; Aircraft; SEM; PLS

1. Introduction

The importance of aircraft in the Air Force has increased in wartime, since warfare has been significantlychanged by aerospace technology developments (Allard, 1995). For the highest possible level of aircraft read-iness, adequate logistics management of aircraft operations is essential. Effective logistics management for air-craft operations can be performed through the continuous improvement of current logistics capabilities.Additionally, the current gradual decrease in national defense expenditures requires more efficient logistic sys-tems than ever before.

Accordingly, US Forces have reengineered their logistics systems and introduced new management para-digms to improve logistic capabilities (Chairman of the Joint Chiefs of Staff, 1998). The Chief of Staff ofROKAF (Republic of Korea Air Force) likewise introduced the Air Force vision 2025, which indicated thefollowing elements as crucial factors for improving aircraft logistics management: logistic systems, logistic net-works, and related agency policy (Chief of Staff ROK Air Force, 2003). These factors for efficient logistic man-agement can be divided into several sub-factors. There have been various studies on the sub-factors that affect

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doi:10.1016/j.tre.2007.08.001

* Corresponding author. Tel.: +82 2 2123 4014; fax: +82 2 364 7807.E-mail address:[email protected](S.Y. Sohn).

Available online at www.sciencedirect.com

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efficient logistic management: equipment and facility management (Brooks and Wallace, 1989; Fleischmannet al., 1997; Wills and Wills, 1998; Sum et al., 2001), manpower management (Graham et al., 1994; Fleisch-mann et al., 1997; Wills and Wills, 1998; Thornhill and Saunders, 1998; Sum et al., 2001; Ellinger, 2003), logis-tic information systems (Bowersox and Daugherty, 1995; Brooks and Wallace, 1989; Dawe, 1994; Daughertyet al., 1995; Closs et al., 1997; McClure, 1997; Burgess, 1998; Lau et al., 2004; Simchi-Levi and Zaho, 2002 ),

supply and maintenance management (Kang and Eaton, 1998), and logistic networks and transportation(Wills and Wills, 1998).There has been extensive research related to logistic management. However, none of the previous studies

focus on the measurement and feedback mechanism of logistic management capabilities for aircraft operation.There have been some studies on key performance indicators for Information Technology (Gunasekaran andNath, 1997), logistic capability (Shang and Marklow, 2005), and Integrated Logistics Support (ILS) (Geierand Vilsmeier, 1988; Strain and Preece, 1999). However, the studies were not developed to identify structuralrelationships among all factors considered for efficient logistic management.

In this study, we incorporate the relationships among various factors related to logistic management andpropose a Structural Equation Model (SEM) to produce an Air Force Logistics Management Index (ALMI)for both the internal user (ground men and suppliers) and external customers (pilots as end users), who areinvolved in the aircrafts logistic system in ROKAF. Here, logistics management means the managing system

which is composed of not only logistics system such as transportation, storage, packing, loading and unload-ing but also logistic facility, logistic manpower, logistic policy, and logistic networks.

The concept of the Customer Satisfaction Index (CSI) is applied to assess the ALMI for various character-istics including the airbase types, aircraft types, specialties, and classes. It is expected that this model will beused to evaluate various logistic support capabilities of the ROKAF logistic management system and contrib-ute to system modernization.

This paper is organized as follows. In Section2, the proposed SEM for an ALMI is introduced along withthe research hypotheses. In Section3, the model is discussed and the results are analyzed. Section 4 summa-rizes the results of this study and suggests further study areas.

2. Proposed model and research hypotheses

In this section, we propose an SEM to analyze the relationship among various factors for improving air-craft logistics management and to develop an Air Force Logistics Management Index (ALMI) for effectiveaircraft operation.

The SEM has become one of the most widely used multivariate statistical tools in various areas includingpsychology, education, and behavioral sciences (Bentler, 1983; Joreskog and Sorbom, 1989; Parhizgari andRonald, 2004). SEM is basically formulated by two types of equations: the measurement equation and theconstruct equation. While the measurement equations can be used to study the relationship between theobserved variables and the latent factors, the construct equations can be used to assess the hypothesized rela-tionship among the latent factors. The latent factors represent the construct of interest. Many constructs thatare of interest to researchers cannot be observed directly. Such constructs are measured indirectly by means ofobservable variables, such as questionnaire items designated to elicit responses that are related to a specificlatent factor.

Both the LISREL based on MLE (Maximum Likelihood Estimation) and the PLS are common tools usedto estimate the SEM. Although the MLE is a popular tool, it has the limitations of requiring a distributionalassumption along with a large sample size. The PLS, however, does not require a distributional assumptionand has become popular because of its use of ACSI (Fornell et al., 1996; Sohn and Moon, 2003; Sohnet al., 2007a,b; Sohn and Joo, 2007b). According toFornell and Bookstein (1982), PLS and LISREL havedifferent objectives and present systematically different results. First, LISREL attempts to account forobserved covariances, whereas PLS aim at explaining variances (of variables observed and/or unobserved).Second LISREL offers statistical precision in the context of stringent assumptions but PLS trades parameterefficiency for prediction accuracy, simplicity, and fewer assumptions.

Analogous to an ACSI, the Air Force Logistics Management Index (ALMI) is proposed, and it uses a PLS-

based SEM. Using the proposed model, the relationship among the factors is verified and the individual

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ALMI is calculated with respect to various characteristics including the airbase types, aircraft types, special-ties, and classes. Details of the ACSI and the PLS approach are explained inAppendix A.

Prior to establishing the SEM for air force logistic management index, a brief review of previous researchon various factors that could potentially affect the effectiveness of logistic management and improve the logis-tic capabilities was conducted.

The US Department of Defense emphasizes the importance of focused logistics management for the bestlogistic systems and suppliers in order to keep the leadership in warfare (Chairman of the Joint Chiefs of Staff,1998). The vision of the ROKAF requires that logistic systems, logistic networks, and the related agency pol-icy be improved for higher logistic efficiency (Chief of Staff ROK Air Force, 2003).Kang and Eaton (1998)pointed out that the highest possible level of readiness for aircraft requires an efficient logistic system thatconsists of reliable supply and maintenance management. According toQi (2005), the optimal sequence deter-mination of the logistics process is an important issue in recent logistic management. Brooks and Wallace(1989)indicated that various elements such as Maintenance Planning, Manpower and Personnel, Supply Sup-port, Support Equipment, Facilities, Training and Training Support, and Transportation must be consideredwhen formulating a logistics support system. Nam (2002)showed that material management, logistics infor-mation management, logistics organization, and human resources management must be developed for militarylogistic systems.Sum et al. (2001)pointed out that it is critical to develop manpower, establish sufficient facil-

ities and equipment, and enhance the logistic process, in order to maintain a competitive logistics system.Also,Fleischmann et al. (1997)indicated that the management of facilities and human resources are two

important decision areas of resource management. Graham et al. (1994) and Ellinger (2003) related thatcoaching had a positive impact on individual and team performance.Thornhill and Saunders (1998)showedthat employee commitment is improved when line managers are actively involved in developing a high-qualityworkforce through coaching, team building, and employee involvement. Brooks and Wallace (1989), Burgess(1998), Closs et al. (1997), McClure (1997), Simchi-Levi and Zaho (2002) indicated that information systems inlogistics management is viewed as a catalyst to avoid supply chain management failure. Additionally, infor-mation systems can simultaneously improve services and reduce costs and significantly influence the overalllogistic competency. Lau et al. (2004) investigated the impact of different levels of sharing information onthe inventory replenishment of enterprises in three-stage distribution supply chains by using a multi-agent-

based simulation model. Wills and Wills (1998) emphasized the necessity of proper logistics networks andtransportation for effective logistic management. Choi (2001) indicated that agency policy is a key factorfor the development of logistics capability in the military field.Stock et al. (1998)also emphasized the impor-tance of strategic policy and network organizations in logistics.

With this background, specific latent factors were established including the logistic systems (supply man-agement, maintenance management, manpower management, equipment/facility management, transporta-tion, and logistics information system), logistic networks and the related agency policy potentially affectingthe ALMI for aircraft operation. The ALMI can be estimated as a weighted average of the satisfaction scoresof these factors.

In summary, supply management is the factor representing how well military supplies such as repair partsand oil are managed. We consider various aspects to measure this latent factor covering preparation and stockmanagement to quality and stock level of aircraft military supplies. Maintenance management represents howsystematically maintenance of aircraft is managed for logistics. In order to represent this latent factor, we con-sider following aspects: how properly repair processes are operated upon aircraft failure, and how often air-craft is inspected to prevent failure. Manpower management is for how well human resources necessary formanagement of military supplies are operated. It can be measured in terms of the following aspects: how welltechnicians are educated, how well human resources are deployed for effective management of military sup-plies, and how timely human resources are supplied.

Equipment and facility management represents how well the equipments necessary for military supplies areprepared. This is different from the Supply management factor mentioned above, where it represents how wellmilitary suppliers are managed. For the Equipment and facility management factor, we consider the followingaspects: the level of quality of equipment and facility, and how well equipment and facilities are suitable forsupporting military supplies of aircrafts. Transportation factor is to represent how timely the military supplies

for aircraft are delivered along with proper capacity.

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Logistics information system is for how well information system is built and operated for efficient supply,maintenance and management of aircraft military supplies. Logistic networks factor is not related to how welltransportation paths for delivering military supplies are organized but how well the organizations responsiblefor management of aircraft military supplies cooperate each other to handle their tasks. The following aspectscan be considered for the logistic network factor: how well organizational logistics are managed not only

between upper and lower agencies but also among pilots, ground men and suppliers. Finally, agency policyis for how well the related policies required are managed for aircraft military supplies.Based on this concept, we develop measurement variables for latent factors in this study, since there was no

previous research done for the logistics management capability of aircraft in the Air Force. The first step indeveloping the measurement variables is to consider both the environmental factors of logistics in the ROKAFand the representative groups opinions, such as those from ground men, suppliers and pilots, all of whom areinvolved in the aircrafts logistics system. Next, minor modifications of the measurement variables are made tomake them suitable for the context of this study. A pilot test of the measurement variables is conducted bythree representative groups in the ROKAF. Finally, the measurement variables are modified once againaccording to the results of the pilot test. Details regarding the measurement variables selected for the latentfactors are given inTable 1.

The following research hypotheses were set up in relation to the latent variables in Table 1on the basis of

the vision for the improvement of logistic management (Chief of Staff ROK Air Force, 2003), previousresearch and the opinions of representative groups in the ROKAF.

H1: Maintenance management, logistic information system, and logistic network will have direct influ-ences on the ALMI for aircraft operation. Among these factors, the logistic information system will havethe highest direct effect on the ALMI.

As mentioned above, many researchers emphasized the importance of logistics management and need toimprove various logistics management factors such as maintenance management, information system andlogistic network for logistics management (Qi, 2005; Brooks and Wallace, 1989; Nam, 2002; Sum et al.,2001; Fleischmann et al., 1997; Graham et al., 1994; Ellinger, 2003; Thornhill and Saunders, 1998). Especiallyamong various factors, it was indicated that information systems in logistics management is viewed as criticalfactor and can influence the overall logistics competency (Brooks and Wallace, 1989; Burgess, 1998; Closs

et al., 1997; McClure, 1997; Simchi-Levi and Zaho, 2002).H2: Supply management, manpower management, equipment and facility management, transportation

and logistics policy will have indirect effects on the ALMI for aircraft operation. Among these, the logisticpolicy will have the highest indirect effect on the ALMI for aircraft operation.

There are many studies to support H2. Sum et al. (2001)mentioned that many factors such as manpower,sufficient facilities and equipment, logistics process are essential to maintain efficient logistic system. Ellinger(2003) and Graham et al. (1994)showed that training workers had a positive impact on performance. Fleisch-mann et al. (1997)insisted that the management of facilities and human resources are two important decisionareas of resource management. Thornhill and Saunders (1998) showed that employee commitment can beimproved when line managers are actively involved in developing a high-quality workforce through coaching,team building, and employee involvement. Choi (2001)indicated that agency policy is a key factor for thedevelopment of logistics capability in the military field. Also, Stock et al. (1998)also emphasized the impor-tance of strategic policy and network organizations in logistics. In many cases, it takes time to have tangibleoutputs and effects from policy implementation, although it is expected to have huge impact.. So we assumethat it would have the highest indirect effect.

H3: The increase of ALMI for aircraft operation will contribute to the improvement of the combatreadiness.

As mentioned above, the US Department of Defense emphasizes the importance of logistics management(Chairman of the Joint Chiefs of Staff, 1998). For the highest possible level of aircraft readiness, adequatelogistics management of aircraft operations is essential.

H4: The ALMI for aircraft operation will vary according to various characteristics such as the airbasetypes, aircraft types, specialties, and classes (Lai, 2004).

Index would vary over different groups.

To test these hypotheses, a SEM is constructed, as given inFig. 1.



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Table 1Confirmatory factor analysis (CFA) for measurement variables and factors

Latent variable(Factors)

Measurement variable Confirmatoryfactor analysis

CronbachAlpha test

R2 of endogenousvariable

Logistics systemSupply management

Preparation of military supplies of aircraft 0.698 0.84 0.368Quality of aircraft military supplies 0.521Storage management of aircraft military supplies 0.712Support of aircraft military supplies 0.719Adequacy of airplane logistics management process 0.612Effort to respond to customer (pilot, ground man)s needs 0.528

Maintenance management

Adequacy of preventive activity against failure of aircraft 0.767 0.80 0.136Maintenance management of aircraft 0.801Adequacy of maintenance process 0.820Effort to respond to customer (pilot)s needs 0.664

Manpower management

Supplement of aircraft suppliers 0.659 0.82 0.331Supplement of aircraft ground men 0.523Suitability of aircraft suppliers deployment 0.722Suitability of aircraft ground mens deployment 0.632Technical education for aircraft supplier 0.531Technical education For aircraft ground men 0.443

Equipment and facility management

Efficient equipment supply for aircraft supplier 0.696 0.88 0.501Efficient equipment supply for aircraft ground men 0.777Equipment quality for aircraft supplier 0.414Equipment quality for aircraft ground men 0.411Suitability of facilities for aircraft supplier 0.729Suitability of facilities for aircraft ground men 0.748Facilities management for aircraft supplier 0.740Facilities management for aircraft ground men 0.721

Logistics information systemSupply information system

Adequacy of interface and search design 0.663 0.88 0.425Level of acquisition of various information 0.683Level of proper operation 0.676

Maintenance information system

Adequacy of interface and search design 0.645Level of acquisition of various information 0.638Level of proper operation 0.672

Score of accurate information

Quantity of aircraft military supplies 0.507Supply progression of interesting supplies 0.449Maintenance progression of interesting supplies 0.428Plan related to supply and maintenance 0.447

TransportationLevel of proper transportation of aircraft military supplies 0.714 0.80 0.317Adequacy of transportation capacity 0.757

Logistics networkOrganization system

Between pilots and ground men 0.643 0.80 0.550Between suppliers and ground men 0.502Between pilots and suppliers 0.474



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3. Data analysis

In order to conduct confirmatory factor analysis (CFA) and to test the proposed hypotheses, a survey was

conducted to 900 related personnel in aircraft logistics in the ROKAF. The respondents consisted of pilots,

Fig. 1. The proposed Structural Equation Model (SEM).

Table 1 (continued)

Latentvariable(Factors)

Measurement variable Confirmatoryfactor analysis

CronbachAlpha test

R2 of endogenousvariable

Organizational logistics management between upper agencyand lower agency

0.319

Organizational logistics management between logistics agencyand non-logistics agency

0.401

Agency policySupply agency

Improvement of supply management 0.562 0.91Effort to respond customers needs 0.612Adequacy of supply plan 0.615

Maintenance agency

Improvement of maintenance management 0.596Effort to respond customers needs 0.641Adequacy of maintenance plan 0.627Adequacy of regulations related to supply and maintenance 0.590

ALMI for aircraft operationLogistics capacity of supply management 0.517 0.86 0.657Logistics capacity of maintenance management 0.566Logistics capacity of manpower management 0.419Logistics capacity of equipment and facility management 0.458Logistics capacity of transportation 0.438Logistics capacity of logistics information system 0.555Logistics capacity of logistics network 0.589Logistics capacity of related policy 0.461

Contribution Contribution for combat readiness 0.516 0.592



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ground men, and suppliers selected based on stratified sampling considering the proportions of specialty, air-craft type and class. Survey contents include not only the measurement variables listed in Table 1, but alsopersonal characteristics of the respondents. Each respondent was asked to score the Level of each measure-ment variable in a five point Likert scale from 1 (bad) to 5 (good). 651 valid forms out of a total of 900 surveysexecuted and were collected. Among respondents, about 64% were from the air base for fighter aircraft, 16%

were from the air base for cargo, and 20% were from the air base for training. Also, the respondents consistedof officers (46%), noncommissioned officers (30%), and civilian employees (24%). These proportions show thatthe samples represent an entire population well. The CFA, which is used to examine the convergent and dis-criminate validity of each construct, was performed before fitting the SEM. The CFA seeks to determine if thenumber of factors combined with the measurement variables conform to what is expected, on the basis of pre-established theory. The measurement variables were selected on the basis of prior theory. Factor analysis isused to see if they load as predicted on the expected number of factors. The prior assumption is that each fac-tor is associated with a specified subset of measurement variables. The reliability of the research instrument isoften tested by Chronbach Alpha (a) whereHair et al. (1998)suggested that the lowest limit fora is 0.70. Theresults presented here show thata for every factor is higher than 0.70, which confirms the consistency amongthe measurement variables within each latent variable, as shown inTable 1.

LISREL and other covariance structure analysis models estimate the parameters by reproducing as closely

as possible the observed covariance matrix. In contrast, PLS has a primary objective to minimize errors in allendogenous constructs. In addition, LISREL offers statistical precision in the context of stringent assumptionsbut PLS trades parameter efficiency for prediction accuracy, simplicity, and fewer assumptions. The degree towhich a particular PLS model accomplishes this objective can be determined by the R2 values of the dependent(endogenous) constructs. One of the differences in the objectives between LISREL and PLS is that no properoverall goodness-of-fit measure exists for estimation models that use the latter ( Hulland, 1999). According torelated literature (Birkinshaw et al., 1995; Cool et al., 1989), which dealt with the R2 values for the endogenousconstructs, there is a range from 12% to 64%. The calculated R2 for the endogenous constructs of this modelprovide results that range from 13.6% to 65.7%. The ALMI provides an R2 of 65.7%, which is relatively highcompared to the others.

3.1. Analysis of the Structural Equation Model

The PLS procedure is then applied to estimate the path coefficients in the SEM, which can be used for smallsample sizes. The significance of the path coefficient is verified by the bootstrap confidence interval that isbased on research conducted bySimchi-Levi and Zaho (2002). The research hypotheses are tested by the fittedSEM and the results are as follows.

As seen inTable 2, all of the paths are significant with a 5% confidence level. Thus,Table 2supports thegeneral relationships set in hypotheses 1, 2, and 3.

In order to identify the most influential factors, both the direct and indirect effects on ALMI for aircraftoperation are analyzed.

3.2. Analysis of the direct and indirect effects

As for hypotheses 1 and 2, the direct and indirect effects among the factors are analyzed, in order to find themost influential factors on the ALMI for aircraft operation. Direct effects are the association of one variablewith another specified in the model. Indirect effects are the association of one variable with another mediatedin the model through other variables. The total effect is represented by the sum of the direct and indirect effects(Kim and Kang, 2001).Table 3displays the relationships between the factors.

As shown inTable 3, the logistic information system has the highest direct effect on the ALMI for aircraftoperation (hypothesis 1). This implies that insufficient information in supply and maintenance managementcan cause many problems. Therefore, a systematic and integrated information system for supply and mainte-nance in the ROKAF is critical, in order to increase the ALMI for aircraft operation over a short-term period.

The agency policy factor turns out to have the highest indirect effect on the ALMI (hypothesis 2). Agency

policy reflects the agencys willingness to boost the field of supply and maintenance. Also, this kind of policy



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can instigate long term effects. Additionally, due to its huge indirect effect, the agency policy factor has thehighest total effect on the ALMI for aircraft operation. This finding implies the importance of the agency pol-icy factor in the ROKAF. Therefore, in order to improve the ALMI for aircraft operation, improving themanagement of aircraft items and their maintenance schedules cannot be overemphasized, nor can respondingto customer (pilot)s needs and regulations related to logistics.

In particular, it is worth noting that the logistics network factor has the second highest total effect on theALMI for aircraft operation. Along with the logistics network, the proper organizational system of the threemain groups (pilots, ground men and suppliers), cooperation with the supporting department (facility, com-munication), and the systematic process between the upper agency and the lower agency for logistics support

also require close attention to obtain higher ALMI for aircraft operation.

Table 2Confidence interval for path coefficients of SEM

Latent variable Lower Path coefficient Upper

Supply management ! Maintenance management 0.090 0.167a 0.243Maintenance management ! ALMI for aircraft operation 0.009 0.018a 0.065Manpower management

! Supply management 0.12 0.143a 0.271

Maintenance management 0.017 0.027a 0.101Equipment and facility management 0.357 0.409a 0.479ALMI for aircraft operation 0.072 0.125a 0.160

Equipment and facility management ! ALMI for aircraft operation 0.022 0.053a 0.118Transportation ! Supply management 0.069 0.135a 0.244

ALMI for aircraft operation 0.030 0.092a 0.148Logistics information system ! Supply management 0.029 0.036a 0.158

Maintenance management 0.027 0.047a 0.150Logistics network 0.159 0.237a 0.304ALMI for aircraft operation 0.196 0.261a 0.380

Logistics network ! Supply management 0.108 0.186a 0.330Maintenance management 0.072 0.193a 0.288Manpower management 0.138 0.223a 0.305

Transportation 0.260 0.353

a

0.441ALMI for aircraft operation 0.073 0.239a 0.284Agency policy ! Supply management 0.028 0.093a 0.229

Maintenance management 0.003 0.012a 0.131Manpower management 0.300 0.394a 0.491Equipment and facility management 0.331 0.394a 0.456Transportation 0.172 0.252a 0.349Logistics information system 0.611 0.652a 0.694Logistics network 0.503 0.565a 0.630ALMI for aircraft operation 0.244 0.253a 0.364

ALMI for aircraft operation ! Contribution 0.745 0.769a 0.803a Significant parameters with a 5% bootstrap confidence interval.

Table 3Relation between the ALMI for aircraft operation and other factors

Latent variable ! Latent variable Direct effect Indirect effect Main effectSupply management ! ALMI . 0.003 0.003Maintenance management 0.018 . 0.018Manpower management 0.125 0.022 0.147Equipment and facility management 0.053 . 0.053Transportation 0.092 0.001 0.093Logistics information system 0.261 0.034 0.295Logistics network 0.239 0.064 0.303Agency policy 0.253 0.347 0.600



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In summary, the ROKAF needs to pay attention to integrated information systems, systematic logistic net-works, and proper agency policy, in order to attain a higher ALMI for aircraft operation.

4. Analysis of ALMI

4.1. ALMI

In order to test hypothesis 4, an ALMI was calculated for aircraft operation with respect to various char-acteristics. The overall ALMI is related to eight measurement variables, as shown in Fig. 2.

The relationship between the overall ALMI (gi) for aircraft operation and eight observed variables for therespondent (i) is described as follows:

gi s1 yi1 s2 yi2 s3 yi3 s4 yi4 s5 yi5 s6 yi6 s7 yi7 1where sjis the score between the measurement variable (yij) and latent factor (gi).

In order to find a scaled ALMI for aircraft operation that varies from 0 to 100 for a specific group, thefollowing formula is used:

ALMI P8

j1sj

yj P8

j1sjr 1 P8j1sj2

where yjis the mean of the measured variable jfor a group and ris the range of the Likert scale. In this case ris5.Tables 47display the calculated ALMIs by their respective groups.

Fig. 2. Relationship between the overall ALMI and the measurement variables.

Table 4ALMI for aircraft operation by air bases

Items Frequency ALMI

Overall 651 59.2Air bases for fighter aircraft 419 73Air bases for trainer 101 56.3

Air bases for cargo 131 48.4



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As shown inTable 4, the ALMI for aircraft operation varies according to the air base type. The ALMI foraircraft operation at air bases used for fighter aircraft is highest, due to its important role in airpower. TheALMI for aircraft operation of air bases used for cargo is the lowest, which implies that institutional policiesare required to improve their index.

In order to find potential differences among groups with respect to other latent factors, the index at the levelof each latent variable was obtained by applying the same method used in the ALMI. The spider maps arebased on the latent variable indices that are displayed in Fig. 3. As shown in Fig. 3, similar spider shapesare found with respect to each air base type. While an air base for a fighter aircraft has relatively high valuesin every aspect, an air base for cargo and training have low values. It is also observed that the maintenancemanagement index is higher than the other indices. This implies that all air bases carry out the failure preven-tion activity, maintenance procedure, and effort to respond to pilots needs in a satisfactory manner.

Air bases used for cargo and training appear to have poor conditions in most aspects. In particular, themanpower management index for these bases is lower than other indices. This may be due to the fact thatthe deployment and supplementary and technical education of suppliers and ground men is insufficient. Effec-tive manpower management is required to improve the ALMI for aircraft operation in the short-term, sincelogistics management is based on it.

Table 5 shows the difference of the ALMI for aircraft operation organized by aircraft type. Among thefighter aircraft, the ALMI for aircraft operation of the latest fighter aircraft is higher than that of other air-craft. As for training and cargo, KT-## and C-## have lower ALMI than the others, which is likely to causepotential delays of aircraft readiness. Thus, it is necessary to find a way to improve their ALMI for aircraft

operation.

Table 5ALMI for aircraft operation by aircraft type


Overall 651 59.2F-a(The latest age type) 131 77.5F-a(The middle age type) 154 73.4

F-a(The oldest age type) 132 69.8T-a 52 59.7KT-a 56 54.2CN-a 67 50.6C-a 59 47.2

a Omitted due to military security.

Table 6ALMI for aircraft operation by specialties


Overall 651 59.2

Pilot 192 49.9Groundman 254 60.1Supplier 205 69

Table 7ALMI for aircraft operation organized by class


Overall 651 59.2Officers 301 43.3Noncommissioned officers 198 70.5

Civilian employees 152 63.8



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Table 6shows the differences among the ALMIs for aircraft operation organized by specialty. The ALMIfor aircraft operation of internal customers (ground men and suppliers) is higher than that of external custom-ers (pilots). This represents the gap between the two groups. Since the end user of the aircraft is the pilot, thegeneral ALMI for aircraft operation has to be improved.

Table 7shows the difference between the ALMI for aircraft operation organized by class. The ALMI foraircraft operation of managers (officer) is lower than that of workers (noncommissioned officer and civilianemployees). This implies that the current logistics capability of aircraft operation is lacking in terms of plan-ning, implementation, and evaluation in its logistics system. These shortcomings are related to the managersroles and can make the greatest total impact on the ALMI when they are sufficiently reflected in the logisticspolicy.

On the basis of the fitted SEM, the causal relationships, impacts, and the ALMI for aircraft operation orga-

nized by specific groups are shown. However, this may not be sufficient to provide the airbase unit of the

Fig. 3. Spider maps of the latent variables organized by air base type.



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Table 8Check-list for improvement by air base types

Latent variable(Factors)

Measurement variable Airbase for fighteraircraft

Airbase forcargo

Airbase fortrainer

Logistics systemSupply management

preparation of military supplies of aircraft pQuality of aircraft military supplies

p pStorage management of aircraft military supplies

pSupport of aircraft military supplies

pAdequacy of airplane logistics management process

p pEffort to respond to customer (pilot, ground man)s needs

p p

Maintenance management

Efficient equipment supply for aircraft supplier p

Efficient equipment supply for aircraft ground men p

Equipment quality for aircraft supplier p

Equipment quality for aircraft ground men p p

Manpower management

Suitability of facilities for aircraft supplier pSuitability of facilities for aircraft ground men pFacilities management for aircraft supplier

p pFacilities management for aircraft ground men

p pEfficient equipment supply for aircraft supplier

p pEfficient equipment supply for aircraft ground men

p p

Equipment and facility management

Equipment quality for aircraft supplier p p

Equipment quality for aircraft ground men p p

Suitability of facilities for aircraft supplier p

Suitability of facilities for aircraft ground men p p

Facilities management for aircraft supplier p p

Facilities management for aircraft ground men p p

Efficient equipment supply for aircraft supplier p p

Efficient equipment supply for aircraft ground men p pLogistics information systemSupply information system

Adequacy of interface and search design p p

Acquisition of various information p p

Proper operation p p

Maintenance information system

Adequacy of interface and search design p p

Acquisition of various information p p

Proper operation p p

Score of accurate information

Quantity of aircraft military supplies p p

Supply progression of interesting supplies p pMaintenance progression of interesting supplies

p pPlan related to supply and maintenance

p p

Transportation Proper transportation of aircraft military supplies p p

Adequacy of transportation capacity p

Logistics networkLevel of organization system

Between pilots and ground men p

Between suppliers and ground men p

Between pilots and suppliers p

Organizational logistics management between upper agencyand lower agency

p p

(continued on next page)



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ROKAF with the feedback information necessary for the required improvements. Accordingly, a check-list

was made that is based on the measurement variables. Ticked units have a lower value than the overall averageof the three types of airbases for each category of the measurement variables.

Table 8shows the measurement variables that need to be improved for each airbase unit. According to thisresult, most aspects were required to be improved in the air bases except for the training and cargo aspects.This reflects the low ALMI for aircraft operation at the air base used for training and cargo. The air base fortraining requires improvement in supply management, equipment and facility management, and the logisticinformation system.

5. Conclusion

In order to maintain the highest possible level of aircraft readiness, it is essential to improve logistic capac-ities for aircraft operation effectively. Additionally, the current trend toward a gradual decrease in nationaldefense expenditures requires more efficient logistic systems for aircraft than ever before. However, no previ-ous research has focused on the measurement tools and feedback mechanism of logistic capabilities for aircraftoperation. In this paper, a SEM was applied to develop the ALMI for effective aircraft operation by consid-ering the relationships among various factors.

The results of our study verify that logistic information systems have the highest direct effect on the ALMIfor aircraft operation. Therefore, the systematic and integrated information system of supply and mainte-nance in the ROKAF is important to increase the ALMI for aircraft operation over a short-term period.Aircraft logistic capacity cannot be improved by controlling a single factor. The structural relationshipsamong many factors must be considered; for instance, the agency policy factor has the highest indirect effecton the ALMI. Additionally, due to its huge indirect effect, the agency policy factor has the highest total effecton the ALMI for aircraft operation. This result implies the importance of the agency policy factor in the

ROKAF.

Table 8 (continued)

Latentvariable(Factors)

Measurement variable Airbase for fighteraircraft

Airbase forcargo

Airbase fortrainer

Organizational logistics management between logisticsagency and non-logistics agency

p p

Agency policySupply agency

Improvement of supply management p

Effort to respond customers needs p p

Adequacy of supply plan p

Maintenance agency

Improvement of maintenance management p p

Effort to respond customers needs p p

Adequacy of maintenance plan p p

Adequacy of regulations related to supply andmaintenance

p

ALMI for aircraft operationLogistics capacity of supply management p pLogistics capacity of maintenance management

p pLogistics capacity of manpower management

p pLogistics capacity of equipment and facilitymanagement

p

Logistics capacity of transportation p

Logistics capacity of logistics information system p

Logistics capacity of logistics network p

Logistics capacity of related policy p p



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In addition to comparing the ALMIs for aircraft operation by airbase type, aircraft type, specialty, andclass, a check-list was also made that is based on the measurement variables to provide practical feedbackinformation for improvements.

The results of this study are expected to be used as guidance for the development of logistics managementsystems for aircraft operation in the ROKAF. In addition, the proposed model can be extended to provide the

management index for logistics company which cover various products and materials. Finding more applica-tion areas of this model remain for further study.

Appendix A. ACSI and Partial Least Square

The formal expression of the ACSI model depicted inFig. 1may be spelled out as a series of equations thatuses the systematic part of the predictor relationship in the conditional expectation of the dependent variablesfor given values of predictors (Fornell et al., 1996). The general equation is thus specified as stochastic:

Egjg; n Bg Cn A:1whereg 0= (g1,g2, . . . ,gm) andn 0= (n1,n2, . . . ,nn) are vectors of unobserved (latent) endogenous and exogenousvariables, respectively. B(m m) is a matrix of coefficient parameters for g, and C(m n) is a matrix of coef-

ficient parameters forn. This implies thatE[gf0] = E[gf0] = E[f] = 0, wheref=g E[gjg,n]. The general equa-tions relating the latent variables to the measurement variables are

y Kyg e A:2x Kxn d A:3

where y 0= (y1,y2, . . . ,yp) and x 0= (x1,x2, . . . , xq) are the measured endogenous and exogenous variables,respectively. Ky(p m) and Kx(q n) are the corresponding factor loading matrices. By implication fromthe PLS estimation (Fornell and Bookstein, 1982),

Ee Ed Ege0 End0 0The ACSI is estimated by the PLS (Partial Least Square) estimation to determine the relationship between

the unobserved (latent) variable and observed (measurement) variable. The PLS are used to minimize theresiduals (P

d2,P

e2 andP

f2) in the structural relationship (Rodgers, 1999). For example, consider the spec-

ification of structural relation between n and g1of the ACSI model, as inFig. 4. In the PLS, the unobservedvariables are estimated as exact linear combinations of their empirical indicators

g pgy A:4n pnx A:5g cn f A:6

where pg(p m) and pf(q n) are regression matrices (Fornell and Bookstein, 1982).Fig. 4is estimated by giv-ing arbitrary initial values to the weights pg1 , pg2 and pg3 , normalizinggto unit variance and regressing it on x1,x2and x3. Let nbe the predicted value ofg in this regression. gis estimated by a corresponding procedure as

the predicted value ofn. That is, pn1, pn2, and pn3are given arbitrary starting values and nis normalized to unitvariance and regressed ony1,y2, andy3.gandnare replaced by gand n, each normalized to unit variance, andthe procedure is repeated ktimes until gk equals gk1 and nkequals nk1. At this point, the estimated gk is re-gressed on the estimated nkto obtain the structural relationship (c) between the two.

Fig. 4. PLS model.



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The general form of the ACSI index is as follows:

ACSI Eg MingMaxg Ming 100 A:7

where g is the latent variable for customer satisfaction, and E[], Min[], and Max[] denote the expected, theminimum, and maximum value of the variable, respectively. The corresponding measurement variables deter-mine the minimum and the maximum values

Ming Xn

i1piMinyi A:8

Maxg Xn

i1piMaxyi A:9

wherey0i s are the measurement variables of the latent customer satisfaction, p0i s are the weights, and g is the

number of measurement variables. In calculating the ACSI index, unstandardized weights must be used ifunstandardized measurement variables are used. The main advantage of PLS is that it uses a rapid least

squares based estimation technique (Lohmoller, 1984). However, the PLS estimation has shortcomings: (1)Neither an assumption nor an assessment of an one-dimensional measurement is made and, therefore, the the-oretical meaning input to the latent variables can be problematic ( Rodgers, 1999); (2) Since it is a limited-information estimation method, its parameter estimates are not as efficient as full-information estimations(Fornell and Bookstein, 1982); (3) Jackknife, Bootstrap, or other procedures are required to obtain estimatesof the standard errors of the parameter estimates (Dijkstra, 1983).

Appendix B. An example: a part of survey

The Questions for supply management of aircraft military supplies

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How well aircraft military supplies such as oil, repair parts, equipment aremanaged?

Bad Average ! Goodr s t u v

What do you think about the quality of aircraft military supplies? Bad Average ! Goodr s t u v

What do you think about the level of storage management of aircraft militarysupplies?


How well the supplement of aircraft military supplies is managed when thoseare used up?


How well the processes for the support of aircraft military supplies gosmoothly?


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Bad

Average !

Goodr s t u v



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