<Material 1> Measuring Items of Variables.
Variable | Statement | Studies |
Cost Reduction(COS) | My cost of dealing with customer enquiries has been reduced using eCRM | (Kaplan and Haenlein, 2010) (Dwivedi et al., 2015) (Zhang et al., 2019) (Cui, 2016) (Kim and Shin, 2015)(Chung et al., 2017) |
Cost of identifying new customers has been reduced through the use of eCRM | ||
The use of eCRM has diminished customer awareness and training costs | ||
eCRM is more effective than the alternative. | (Chong and Chan,2012) (Martins et al., 2016) | |
COVID-19 Awareness(COVID) | The COVID-19 lockdown made me find it more challenging to access basic needs. | (Kumar and Ayedee, 2021) (Bhardwaj et al., 2021) (Masood and Sonntag, 2020) (Zhao et al.,2020) |
I am worried about COVID-19 occurring at my work. | ||
There is considerable uncertainty when predicting how well the business will do because of COVID-19. | ||
eCRM will be of great help in handling urgent requests from customers during the COVID-19 outbreak. | ||
Digital Transformation(DX) | My company emphasizes the use of digital technology in its business activities. | (Warner and W?ger, 2018) (Fachrunnisa et al.,2020) |
My company summarizes some of its business processes because it is switching to digital technology. | ||
The company increases its mastery of digital technology in its business processes. | ||
I am working from home because of COVID-19. | (Nagel, 2020) (Socio-Economic Panel, 2020) | |
Compatibility(COM) | eCRM is compatible with our company’s IT infrastructure | (Wang et al., 201) (Derham et al., 2011) (Yoon and Cho, 2020) |
I use eCRM regularly for business purposes | ||
My organization provides me support for getting training on eCRM | ||
It is easy to integrate eCRM with our other existing systems. | ||
Perceived Ease of Use(PEOU) | Overall, it is easy to learn eCRM | (Chatterjee and Kar, 2020) (Davis, 1989) (Venkatesh et al.,2012) |
It is easy to identify customer demand using eCRM | ||
Information retrieval about a customer is easy using eCRM | ||
Advertising products and services on eCRM is easy | ||
Perceived Usefulness(PU) | eCRM is useful for business | |
eCRM is a valuable tool for marketing | ||
eCRM enhances the productivity of the business | ||
eCRM helps better query management | ||
Intention to use eCRM(INTENTION) | To the extent possible, I would use eCRM functions (registration of customers, contact customers, promotions, customer analytics, etc.) to do different things. | (Wu and Wu, 2007) (Venkatesh and Bala, 2008) |
I intended to use eCRM in my job as often as needed. | ||
I intended to use eCRM in my job routinely. | ||
I predict I would use eCRM on a tablet PC or smartphone. | (Karjaluoto et al.,2014) (Venkatesh and Bala, 2008) |
<Material 2> Demographic characteristics of the respondents.
Category | Frequency | Percentage (%) | |
Gender | Female | 59 | 50,9 |
Male | 57 | 49.1 | |
Age Group | 20’s | 21 | 18.1 |
30’s | 57 | 49.1 | |
40’s | 13 | 11.2 | |
Above the ’50s | 25 | 21.6 | |
Education | High School Graduate | 13 | 11.2 |
Bachelor | 65 | 56.0 | |
Master | 28 | 24.1 | |
PhD. | 7 | 6.0 | |
Other | 2 | 1.8 | |
Occupation | CEO, CIO, Presidents, Directors | 17 | 2.7 |
CRM managers, CRM technical | 8 | 6.9 | |
Employee in CRM department | 18 | 15.5 | |
IT/IS managers | 7 | 6.0 | |
Sales and Marketing managers or employees | 34 | 29.3 | |
Other | 32 | 39.6 | |
Industry | IT | 25 | 21.6 |
Financial and Banking | 26 | 22.4 | |
Manufacturing | 20 | 17.2 | |
Services | 6 | 5.2 | |
wholesale and retail business | 12 | 10.3 | |
Others | 27 | 23.3 | |
Software Adoption | Microsoft Dynamics CRM | 37 | 31.9 |
Hubspot | 2 | 1.7 | |
Finger Sales | 1 | 0.9 | |
Own Software | 30 | 25.9 | |
Monday.com | 3 | 2.5 | |
Salesforce Social Studio | 23 | 19.8 | |
Oracle | 13 | 11.2 | |
None | 1 | 0.9 | |
Others | 6 | 5.2 | |
Number of Employees | Less than 10 | 27 | 23.3 |
Less than 50 | 31 | 26.7 | |
Less than 100 | 13 | 11.2 | |
Less than 300 | 26 | 22.4 | |
CRM System Usage Period | Less than one year | 49 | 42.2 |
Less than five years | 33 | 28.4 | |
Less than ten years | 8 | 6.9 | |
More than ten years | 14 | 12.1 | |
Others | 12 | 10.4 | |
Total | 116 | 100 |
<Material 3> Descriptive Statistics.
Variable | Item | Mean | Standard Deviation | Variable | Item | Mean | Standard Deviation |
Compatibility | COM1 | 3.71 | 1.237 | Perceived Ease Of Use | PEOU1 | 3.86 | 1.126 |
COM2 | 3.41 | 1.332 | PEOU2 | 3.92 | 1.040 | ||
COM3 | 3.32 | 1.381 | PEOU3 | 3.87 | 1.084 | ||
COM4 | 3.55 | 1.274 | PEOU4 | 4.02 | 1.047 | ||
Perceived Usefulness | PU1 | 3.33 | 1.061 | Cost Reduction | COS1 | 3.59 | 1.150 |
PU2 | 3.78 | 1.102 | COS2 | 3.64 | 1.204 | ||
PU3 | 3.82 | 1.018 | COS3 | 3.66 | 1.095 | ||
PU4 | 3.97 | 1.012 | COS4 | 3.85 | 1.024 | ||
Digital Transformation | DX1 | 3.90 | 1.098 | Intention to use eCRM | INTENTION1 | 3.97 | 1.051 |
DX2 | 3.70 | 1.105 | INTENTION2 | 3.98 | 1.071 | ||
DX3 | 3.67 | 1.094 | INTENTION3 | 4.03 | .964 | ||
DX4 | 3.39 | 1.419 | INTENTION4 | 3.85 | 1.189 | ||
COVID-19 Awareness | COVID1 | 4.03 | 1.118 |
| |||
COVID2 | 3.81 | 1.351 | |||||
COVID3 | 3.41 | 1.384 | |||||
COVID4 | 3.89 | 1.028 |
<Material 4> Rotated Component Matrix.
Variable | Component | |||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | Communality |
COM1 | .229 | .286 | -.013 | .717 | .293 | .075 | .142 | .760 |
COM2 | .162 | .190 | .032 | .734 | .093 | .304 | .043 | .705 |
COM3 | .156 | .175 | .190 | .790 | -.019 | .045 | .146 | .739 |
COM4 | .130 | .226 | .156 | .594 | .255 | .370 | .043 | .649 |
PU1 | .066 | -.049 | .316 | .278 | .077 | .658 | .005 | .623 |
PU2 | .364 | .229 | .162 | .139 | .114 | .698 | -.012 | .731 |
PU3 | .378 | .202 | .189 | .149 | .128 | .666 | .008 | .702 |
PU4 | .419 | .416 | .106 | .094 | .233 | .586 | .010 | .767 |
PEOU1 | .191 | .478 | .151 | .366 | .536 | .119 | .025 | .723 |
PEOU2 | .402 | .199 | .277 | .085 | .695 | .028 | .049 | .772 |
PEOU3 | .431 | .296 | .127 | .153 | .626 | .133 | .006 | .723 |
PEOU4 | .261 | .214 | .279 | .139 | .658 | .250 | .110 | .719 |
COS1 | .190 | .111 | .769 | .210 | .161 | .153 | .143 | .754 |
COS2 | .363 | .056 | .800 | -.012 | .177 | .155 | .096 | .821 |
COS3 | .104 | .192 | .806 | .054 | .227 | .251 | .075 | .821 |
COS4 | .077 | .315 | .595 | .207 | .387 | .163 | -.100 | .688 |
DX1 | .174 | .755 | .170 | .305 | .174 | .149 | .003 | .775 |
DX2 | .059 | .804 | .150 | .163 | .235 | .236 | .092 | .819 |
DX3 | .190 | .846 | .090 | .189 | .154 | .081 | .100 | .836 |
DX4 | .219 | .449 | .348 | .384 | -.206 | -.121 | .183 | .609 |
INTENTION1 | .793 | .141 | .199 | .268 | .099 | .237 | .087 | .834 |
INTENTION2 | .793 | .125 | .206 | .141 | .198 | .155 | .051 | .773 |
INTENTION3 | .729 | .199 | .155 | .135 | .162 | .257 | .056 | .709 |
INTENTION4 | .502 | .047 | .141 | .356 | .319 | .193 | .014 | .541 |
COVID1 | .155 | .080 | .043 | .037 | .151 | .209 | .718 | .616 |
COVID2 | .022 | .154 | .091 | .020 | -.040 | -.146 | .834 | .752 |
COVID3 | .013 | -.042 | .005 | .195 | -.002 | -.059 | .830 | .732 |
COVID4 | -.132 | -.015 | .283 | .049 | .532 | .146 | .509 | .664 |
Each number represents the partial correlation coefficient between the variable and the rotational component in the rotational component matrix. Through the Korean sample, each measurement item converges to the corresponding construct. Moreover, the factor loadings were all very high, above 0.5, and the cross-loadings were all below 0.3, so the validity of the research tool was secured.
<Material 5> KMO and Bartlett’s Test.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy | .875 | |
Bartlett's Test of Sphericity | Approx. Chi-Square | 2163.873 |
df | 378 | |
Sig | .000
|