Perceived importance of success factors of firms practicing e-logistics in supply chain

By

Wing S. Chow

Hong Kong Baptist University

Hong Kong

Outlines

1. Introduction

2. Objective of the study

3. Design of the study

4. Result Findings

5. Further Discussion

and Conclusion

1. Introduction

Supply chain :

– traditionally, emphasizes on the connection, transaction, and delivery of services

– nowadays, the focus shifts to meet market demands rapidly, correctly, and profitably

– How to achieve this new goal?

• Through the help of

– 1. Technology, and– 2. Quality-driven capabilities

• e-logistics is a system which enhances such an objective

• e-fulfillment – is an e-ERP system, or Extranet– also refers as an web-based B-B e-logistic

system

2. Objective of the study

• To determine the success factors of web-based e-logistics

3. Design of study

a. Data collection procedure

b. Data analysis

b. Data analysis

• Four main tests were adopted:

i) construct validity

ii) reliability test

iii) exploratory factor analysis

iv) SERVQUAL measure

(refer to the paper for these clear definitions)

This paper adopted the following methods for data analysis:1) Construct validity. This paper adopted KMO (Kaiser-Meyer-Olkin) values to measure

the adequacy of the samples (Black & Porter, 1996). KMO values are typically usedto judge if a group of decision variables is suitable for analyzing as the successfactors when the exploration factor analysis method is used. The KMO value of 0.5 isconsidered to be acceptable condition (Kim & Mueller, 1978).

2) Reliability test. This paper adopted internal consistency method to test if a set ofdecision variables in a cluster is homogeneous. A reliability coefficient

³ 0.6 in a

cluster is considered as sufficient condition to conclude a high consistency of decisionvariables (Nunnally, 1978).

3) Exploratory factor analysis. This paper followed xxx(decision science) to performfactor analysis of decision variables with each factor. A general guideline is that avalue of factor loading

³

± 0.5 for a decision variable is considered as practically and

significantly contribution to that factor (Hair, 1987).4) SERVQUAL measure. This paper adopted the SERVQUAL measure as shown in

Kettinger and Choong (1997). The service quality of Intranet can be measured bycomputing firstly Intranet Perceptual scores by subtracting values of IntranetPerformance scores from Intranet Expectation scores. Gap correlation is thenobtained by studying the correlation of Intranet Perceptual scores with the OverallIntranet User Satisfaction scores.

a. Data collection procedure

3 main steps:

1. Conduct a literature survey to collect decision variables

2. Construct a questionnaire

3. Samples selection

Steps:1. Conduct a literature survey to collect decision

variables that relating to e-fulfillment• here, the examination of a B-B system, such as

Intranet is highly depended upon• A total of decision variables is identified

Steps:2. Construct a questionnaire based on part (1)

• two measurements are collected for each decision variable

– a) their expected performance in a scale of 5

– b) their actual performance in a scale of 5

Fill out by e-logistics/MIS manager

Fill out by their trading partners a value 5 representsmost important/ highlyagree; where as 1 appliesto the vice versa case

Steps:

3. Samples were selected from the web of http:www.tdctrade.com

• 380 samples were randomly selected

• 105 returned with two missing data

• 103 replies used for data analysis– response rate is 27.6%

Table 1: Decision variables for e-fulfillment system

X1 = The system maintains consistently and regularly,X2= The system provides user-menu/instructions,X3= The system enhances the collaboration among group members,X4= The systems produces accurate search results/information,X5= The system gives a standardized display format (screen layout),X6= The system adopts Data security/privacy,X7= The system improves personal productivity,X8= The organization provides technical support competently,X9= The system improves the business communication,X10= The system enhances fast response time,X11= The system provides standardized retrieval procedure,X12= The organization provides training,X13= The system provides most up-to-date information,X14= The system provides standardized search procedure,X15= The system eases to use,X16= The system improves the quality of decision-making,X17= The system helps to make decision faster,X18= The system allows faster exchange of information.

4. Result Findings

Results– Demographic data– results:

• mean scores, factor analysis, SerQual scores

Summary of background information of respondents.

Total NumbersIndustry Type Trading 25

Telecommunication 16Wholesaling 15Computer software 21Computer/IT 15Others 11

Department Administration 6Marketing 10Human Resources 5Accounting 5EDP/IT 45Sales 5Others 27

Position Top Management 25Operational Management 78

Table 1: Result findings

D.V. FactorLoadings

ExpectedPerformance

ActualPerformance

PerceptualScore

GapCorrelation

X X X X6 0.771 4.08 1.09 3.30 0.89 -0.78 1.12 0.133X11 0.754 3.72 1.02 3.17 0.97 -0.54 1.17 0.287*

X14 0.716 3.93 0.94 3.18 1.06 -0.75 1.27 0.482*

X10 0.642 4.33 0.83 3.24 1.02 -1.09 1.25 0.305*

X15 0.642 4.19 0.88 3.57 1.02 -0.62 1.00 0.259*

SystemQuality

=0.7601KMO=0.76

X2 0.590 3.60 1.30 2.50 1.24 -1.10 1.55 0.097

X13 0.904 4.33 0.94 3.41 0.94 -0.92 1.22 0.063X4 0.880 4.19 0.99 3.30 1.04 -0.89 1.07 0.194**

InformationQuality=0.7125KMO=0.72

X5 0.607 3.48 1.06 3.09 1.03 -0.39 1.21 0.267*

X1 0.835 4.03 1.09 3.11 0.88 -0.92 1.28 0.092X8 0.771 4.21 0.85 3.21 0.96 -1.00 1.26 0.219**

ServiceQuality=0.6622KMO=0.63

X12 0.729 3.77 1.05 2.56 0.97 -1.20 1.40 0.117

X9 0.813 4.10 0.94 3.35 1.08 -0.75 1.25 0.201**

X17 0.791 3.74 0.96 2.86 1.08 -0.87 1.27 0.267*

X16 0.776 3.60 1.10 2.81 0.94 -0.80 1.29 0.173X3 0.758 3.90 0.94 2.95 0.99 -0.95 1.21 0.138X7 0.708 3.95 0.97 2.95 0.86 -1.00 1.16 0.142

Workperformancequality

=0.8504KMO=0.76 X18 0.696 4.11 0.96 3.46 1.06 -0.65 1.09 0.371*

Where *

£ 0.05 and **

£ 0.01

5. Further Discussion and Conclusion

Four critical success factors are identified:

1. System quality (6 decision variales)

2. Information quality(3 decision variables)

3. Service quality(3 decision variables)

4. Work performance quality(6 decision variables)

We further to examine if these four CSF can be used to discriminate the good and poor performance of their e-fulfillment systems, it is shown that the the good performers would do a better job on the following two CSF:– a. System quality– b. Work performance quality

In this paper, we identified:– 18 decision variables– 4 critical success factors– 10 decision variables significant to overall

performance– 2 critical success factors, exercise more by the

good performers

Discriminant of 4 critical success factors

Name of Intranet success factor Discriminant loadingsSystem Quality 0.853*Work Performance Quality 0.650*Information Quality 0.427Services Quality 0.397

Centroid for good performers 0.927Centroid for poor performers -2.1

Wilks’ lambda0.330

P-value 0.000Canonical squared correlation 0.818Hit ratio 86.7

* Factor entered into the stepwise model