Exploring the Items for Measuring the Marketing Information System Construct: An Exploratory Factor Analysis

One of the most important factors that affect the decision-making process is the Information system (IS) in any given institution. Accordingly, IS in any institution is closely matching the heart role in a human body. The aim of this research is to perform instrument validation through exploratory factor analysis (EFA). The questionnaire used in this study is adapted from two different studies: Bahloul (2011) and Al-Adamat (2015). It consists of of seven sub-constructs; after the questionnaire was distributed, 100 responses were collected to do the EFA. EFA was done for each construct separately. The results show that all of the seven constructs have one component or dimension, The factor loading for every item in each construct is >0.6, Bartlett’s Test of Sphericity was <0.05 for all the constructs, which is Significant (P-value < 0.05). Kaiser-Meyer-Olkin Measure of Sampling Adequacy was higher than 0.6 for all the constructs, and this means that the sample size is adequate. Cronbach’s Alpha test was higher than 0.7 for the entire constructs’ items, which means that these items are all reliable. This study found a valid and reliable instrument for measuring the effectiveness of marketing IS components in the decision-making process.


INTRODUCTION
When an excess of possible actions are available, a decision must be taken. A decision is a conscious choice from among at least two options (Brest et al., 2018). Actually, there is no institution or business organization that can work and competes without information system (IS). Marketing IS (MIS) can be defined as computer-based systems that work in combination with other functional IS in order to support the firm's management in solving all problems that correlate to marketing actions, analyses and provide them to the marketing manager for making effective decisions (Keller and Kotler, 2016). Basically, all parts of MIS should run concomitantly in order to achieve the overall efficiency of the whole system (Harker et al., 2015). Thus there is a need to measure the effectiveness for MIS in any organization, and its role in the decision-making process, which represents the aim of this study to find a validated instrument measuring MIS effectiveness in the decision-making process. System (DSS) and its' use (12 items using the scale of 10). Seventh construct: Decision-making process (7 items using the Likert scale of 10). As stated by Awang et al., (2016) that 10 points of Likert scale are more effective than 5 points of Likert scale in operating of the measurement model (Awang et al., 2016). Accordingly, this study will apply the interval scale of 10, in which a person selects a statement among several statements from 1-10 which is considered to reflect the perceived quality of the subject. Where number 1 stands for strongly disagree, while, number 10 stands for strongly agree. According to Awang et al. (2010;2012;2014; and Awang et al. (2018), the researcher should apply a Likert Scale without a label because this measure would give an interval type of data that is continuous and fit the data presumption for parametric analysis. As per Awang (2010;2012;2014; and Hoque et al. (2017;, if the analyst adjusted instruments from past studies and altered accordingly, at that point the scientist needs to direct both pre-test and pilot-test for these "changed items" so as to approve them before it tends to be utilized in the final study. Content validity, face validity, and criterion validity were done as a pre-test for this questionnaire, content validity was done through content experts, and face validity was done through English language experts, criterion validity was done through a statistical expert, after these validation tests are completed, the researcher distributed the instrument to 10 respondents, in order to gather their comments, and check the consistency in their responses. After all the required changes according to pre-test results have been done, the researcher distributed the questionnaire to gather minimum of 100 responses to be able to run the exploratory factor analysis (EFA), according to many researchers for example: Awang (2010Awang ( , 2012Awang ( , 2014Awang ( , 2015, Hoque et al. (2017Hoque et al. ( , 2018, Noor et al. (2015), Awang et al. (2018) and Yahaya et al. (2018) ensures that EFA should be done for each construct to explore for changes in dimensionality of items from past studies due to changes in the characteristics of population from the past.

RESULTS AND DISCUSSION
EFA should be done for each construct to check for the dimensionality of items has changed from past studies due to different conditions between the present and the past.

The EFA for the First Construct: The Abundance of Hardware Utilized in the Hotel
This construct was measured using 8 items listed in Table 1 as AQ1 to AQ8, and each item was measured using Likert-scale of 10, where 1 stand for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation, and item statement, for each item, are listed in Table 1. EFA using Principal Component Analysis as an extraction method performed for these 8 items to measure The Abundance of Hardware utilized in the Hotel construct. The results in Table 2 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-Olkin Measure of Sampling Adequacy higher than 0.6 which is for the first construct 0.930, and this means that the sample size is adequate (Awang, 2010;2012;2014;Hoque et al., 2017;and Noor et al., 2015). Accordingly, the current data are acceptable.
The scree plot in Figure 1 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component. Table 3 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2010;2012;Awang et al. (2018) and Yahaya et al., 2018). Thus all items will be retained.  The results in Table 4 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 77.583%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010(Awang, , 20122014;Noor et al., 2015;Hoque et al., 2017;and Yahaya et al., 2018).

The internal reliability for the instrument measuring the abundance of hardware utilized in the hotel
The last test that should be done is the internal reliability of each construct. As Table 5 shows that Cronbach's Alpha test is 0.958, higher than 0.7, which means that these items are reliable.

The EFA for the Second Construct: The Abundance of the Software Ingredients
This construct was measured using 8 items listed in Table 6 as BQ1 to BQ8, and each item was measured using Likert-scale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation and item statement, for each item, are listed in Table 6.
EFA using principal component analysis as an extraction method performed for these 8 items to measure The abundance of the software ingredients construct. The results in Table 7 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-Olkin measure of sampling Adequacy higher than 0.6 which is for the 2 nd construct 0.949, and this means that the sample size is adequate (Awang, 2010;2012;2014;Hoque et al., 2017Hoque et al., , 2018Noor et al., 2015). Accordingly, the current data are acceptable.
The scree plot in Figure 2 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 8 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2010;2012;2014;Awang et al., 2018 andYahaya et al., 2018). Thus all items will be retained.     There is a protection system for the marketing database to prevent it from nonauthorized person to access the system.

BQ3
There is the flexibility of exchanging marketing information among system's users in your hotel systems.

BQ4
The programs utilized by your hotel have the ability of storage, summarizing, retrieval and modification the marketing information 8.23 1.862

BQ5
The software product your hotel utilizes contributes to minimizing the over usage of papers among sections.

BQ6
The software utilized by your hotel is the most recent and advanced software products.

BQ7
The software package your hotel utilizes is proficient and effective.

BQ8
The abundance and efficiency of the software in the hotel affect the quality of a marketing decision.
8.65 1.808 The results in Table 9 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 76.289%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010;2012;2014;Noor et al., 2015;Hoque et al., 2017Hoque et al., , 2018and Yahaya et al., 2018).

The internal reliability for the instrument measuring: The abundance of the software ingredients
The last test that should be done is the internal reliability of each construct. As Table 10 shows that Cronbach's Alpha test is 0.955, higher than 0.7, which means that these items are reliable.

The EFA for the Third Construct: Internal Records
This construct was measured using 11 items listed in Table 1 as IVQ1 to IVQ11, and each item was measured using Likert-scale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation, and item statement, for each item, are listed in Table 11.
EFA using principal component analysis as an extraction method performed for these 11 items to measure the internal records construct. The results in Table 12 shows Bartlett's Test of sphericity which is significant since it's <0.05. Kaiser-Meyer-Olkin measure of sampling adequacy higher than 0.6 which is for the third construct 0.947, and this means that the sample size is adequate (Awang, 2010;2012;Hoque et al., 2017;and Noor et al., 2015). Accordingly, the current data are acceptable.
The scree plot in Figure 3 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 13 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2010;2012;and Yahaya et al., 2018). Thus all items will be retained.
The results in Table 14 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 77.866%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010(Awang, , 2012(Awang, , 2014(Awang, , 2015Noor et al., 2015;Hoque et al., 2017Hoque et al., , 2018and Yahaya et al., 2018).

The internal reliability for the instrument measuring: Internal records
The last test that should be done is the internal reliability of each construct. As Table 15 shows that Cronbach's Alpha test is 0.971, higher than 0.7, which means that these items are reliable.

The EFA for the Fourth Construct: Marketing Intelligence
This construct was measured using 12 items listed in Table 16 as VQ1 to VQ12, and each item was measured using Likert-scale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation and item statement, for each item, are listed in Table 16.
EFA using Principal Component Analysis as an extraction method performed for these 12 items to measure the Marketing Intelligence construct. The results in Table 17 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-Olkin Measure of Sampling Adequacy higher than 0.6 which is for the 4 th construct 0.968, and this means that the sample size is adequate (Awang, 2010;2012;Hoque et al., 2017;Yahaya et al., 2018 andNoor et al., 2015). Accordingly, the current data are acceptable.
The scree plot in Figure 4 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 18 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2012;2014;and Yahaya et al., 2018). Thus all items will be retained.
The results in Table 19 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 81.888%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010; 2012; Noor

The internal reliability for the instrument measuring: Marketing intelligence
The last test that should be done is the internal reliability of each construct. As Table 20 shows that Cronbach's alpha test is 0.980, higher than 0.7, which means that these items are reliable.

The EFA for the Fifth Construct: Marketing Research
This construct was measured using 14 items listed in Table 21 as VIQ1 to VIQ14, and each item was measured using Likert-scale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation and item statement, for each item, are listed in Table 21.
EFA using Principal Component Analysis as an extraction method performed for these 14 items to measure the Marketing Research construct. The results in Table 22 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-

VQ11
Marketing intelligence efficiency in the hotel is positively reflected in the marketing performance of the employee in the organization.

VQ12
The subsequent data of the marketing intelligence at the Hotel adds to the decision-making process.       Olkin Measure of Sampling Adequacy higher than 0.6 which is for the 5 th construct 0.963, and this means that the sample size is adequate (Awang, 2010;2012;Hoque et al., 2017;Noor et al., 2015). Accordingly, the current data are acceptable.
The scree plot in Figure 5 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 23 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2012;and Yahaya et al., 2018). Thus all items will be retained.
The results in Table 24 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 81.087%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010;2012;Noor et al., 2015;Hoque et al., 2017;and Yahaya et al., 2018).

The internal reliability for the instrument measuring: Marketing research
The last test that should be done is the internal reliability of each construct. As Table 25 shows that Cronbach's alpha test is 0.982, higher than 0.7, which means that these items are reliable.

The EFA for the Sixth Construct: Marketing DSS
This construct was measured using 12 items listed in Table 26 as VIIQ1 to VIIQ12, and each item was measured using Likertscale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation and item statement, for each item, are listed in Table 26.
EFA using Principal Component Analysis as an extraction method performed for these 12 items to measure the Marketing DSS construct. The results in Table 27 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-Olkin Measure of Sampling Adequacy higher than 0.6 which is for the 6 th construct 0.960, and this means that the sample size is adequate (Awang, 2010;2012;2014;Hoque et al., 2017;218 and Noor et al., 2015). Accordingly, the current data are acceptable.   The scree plot in Figure 6 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 28 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2010;2012;and Yahaya et al., 2018). Thus all items will be retained.
The results in Table 29 show that there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 80.619%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010;2012;Noor et al., 2015;Hoque et al., 2016;Hoque et al., 2017;and Yahaya et al., 2018).

The internal reliability for the instrument measuring: Marketing DSS
The last test that should be done is the internal reliability of each construct. As Table 30 shows that Cronbach's Alpha test is 0.978, higher than 0.7, which means that these items are reliable.

The EFA for the Seventh Construct: The Decision-Making Process
This construct was measured using 7 items listed in Table 31 as VIIIQ1 to VIIIQ7, and each item was measured using Likert-scale of 10, where 1 stands for strongly disagree and 10 stands for strongly agree, the mean response, standard deviation and item statement, for each item, are listed in Table 31.
EFA using Principal Component Analysis as an extraction method performed for these 7 items to measure: The decision-making process construct.   The results in Table 32 shows Bartlett's Test of Sphericity which is Significant since it's <0.05. Kaiser-Meyer-Olkin Measure of Sampling Adequacy higher than 0.6 which is for the 7 th construct 0.941, and this means that the sample size is adequate (Awang, 2010;2012;Hoque et al., 2017;and Noor et al., 2015). Accordingly, the current data are acceptable.     The scree plot in Figure 7 shows that only one component is emerged from the EFA, accordingly all items in this construct will belong to one component.
The results in Table 33 the components or dimension for each item is shown in this table, as it's clear all items are belonging to one component, The factor loading for every item should be >0.6 in order to be retained (Awang, 2010;2012;and Yahaya et al., 2018). Thus all items will be retained.
The results in Table 34 show there are one dimension or component emerged from the EFA procedure based on the computed Eigenvalue >1.0. The total variance explained for measuring this construct is 85.593%. The total variance explained is acceptable since it exceeds the minimum 60% (Awang, 2010;012;Noor et al., 2015;Hoque et al., 2017;and Yahaya et al., 2018). Hotel's staff understand the goals and objectives of the computerized marketing information system in the hotel.

VIIIQ2
Tangible benefit from computerized information system in the hotel is found in the decisions you make in your field.

The internal reliability for the instrument measuring: The decision-making process
The last test that should be done is the internal reliability of each construct. As Table 35 shows that Cronbach's Alpha test is 0.972 higher than 0.7, which means that these items are reliable.

CONCLUSION
This study has proven the validity and reliability of the new instrument for measuring the effectiveness of MIS components in the decision-making process, accordingly, this instrument can be used to measure the effectiveness of MIS in the targeted organizations in this study. This study found a valid and reliable instrument for measuring the effectiveness of MIS components in the decision-making process.