In this section, the hypothesis related to the reasons not to adopt DM technologies were analysed. There were three issues identified which were technological, organisational, and human resources.
Hypothesis Three:
Technological, organisational and human resource issues are significant reasons in the decision not to adopt data mining.
Respondents who indicated that their departments were not adopting DM technology (64 respondents) indicated reasons that could be classified as technological, organisational, or human resources issues. The responses are shown in Table 7.7. In terms of technological reasons many respondents indicated that they were satisfied with the current system in place (73.5%), difficult to find the appropriate software (57.9%) and the adoption of technology was too complex and time consuming (42.2%).
Organisational reasons identified for not adopting DM technology included the cost to implement new technology (73.5%), a lack of top management support (76.5%), a lack of management policies (59.4%) and issues that were more important to resolve (56.3%).
Human recourses identified for not adopting DM technology included lack of expertise to implement DM (71.9%) and a lack of awareness about DM (79.7%).
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Table 7.7: Reasons for not adopting data mining
Reasons
Agreement (By Number of Responses and %) Strongly
Agree
Agree % of Agreement
Technological Reasons
Satisfied with current analysis method 6 41 73.5
Difficult to select appropriate software 9 28 57.9
Too complex and time consuming 6 21 42.2
Organisational Reasons
Costly to implement new technology 9 38 73.5
Lack of top management support 26 23 76.5
Lack of management policies 11 27 59.4
Having more pressing problems 17 19 56.3
Human Resources Reasons
Lack of expertise to implement data mining
17 29 71.9
Lack of awareness about data mining 20 31 79.7
There would appear to be major challenges in technological, organisational and human resource issues for non-adopters to move forward to adopt DM technology. From Table 7.7, lack of top management support and lack of awareness about DM technology seems to be the most influencing factor in the decision to adopt this technology with 76.5% and 79.7% agreement; these results are constant with previous results about the factors influencing company’s decision to employ DM where the support from top management and effective and adequate training for staff are the major influencing factors in the decision to adopt DM technology, it seems that top management support and lack of awareness about DM, hence, no adequate training for staff are the two major challenges facing publicly listed companies in Jordan when it comes to adopt DM technology. Among the three statements which represent technological reasons for not adopting DM technology (Satisfied with current analysis method, difficult to select appropriate
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software and too complex and time consuming), the first two statements produced positive and significant results, for the first statement (Satisfied with current analysis method), t(63) = 6.454, p <.001 and for the second statement (Difficult to select appropriate software), t(63) = 3.969, p <.001, for the third and last statement in technological reasons (Too complex and time consuming) however, the t-test shows an insignificant, t(63)=1.276, p=.206) result. The majority of respondents took a neutral stand with only 42.2% respondents agreeing. This has contributed to the insignificant result (Table 7.8).
Table 7.8: Individual T-test: Technological reasons
Reasons
Descriptive Statistics t-tests
(two-tailed/test value=3)
Mode Median Mean
T value Sig
Satisfied with current analysis method
Difficult to select appropriate software
Too complex and time consuming
4 4 4 4 4 3 3.69 3.50 3.17 6.454 3.969 1.276 .000 .000 .206
Statements representing technological issue were found to be reasons for not utilising such technology. Combining those statements a transformed technological reason variable resulted a positive and significant t-test result, t(63) = 4.850, , p <.001) (Table 7.9).
Table 7.9: Transformed Technological reasons for not utilise data mining
Descriptive Statistics t-tests
(two-tailed/test value=3)
Mode Median Mean
T value Sig
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The statements (Costly to implement new technology, lack of top management support, lack of management policies and having more pressing problems) which represents organisational reasons for not adopting DM were also produce a positive and significant results (Table 7.10), For the first statement (Costly to implement new technology), t(63) = 7.571, p <.001. For the second statement (Lack of top management support), t(63) = 9.328, p <.001. For the third statement (Lack of management policies), t(63) = 5.351, p <.001 and for the final statement (Having more pressing problems), t(63) = 5.169, p <.001. These results indicate that the organisational issue contributes to the decision not to adopt DM within the Jordanian publicly listed companies.
Table 7.10: Individual T-test: organisational reasons
Reasons
Descriptive Statistics t-tests
(two-tailed/test value=3)
Mode Median Mean
T value Sig
Costly to implement new technology Lack of top management support Lack of management policies Having more pressing problems
4 5 4 4 4 4 4 4 3.78 4.09 3.63 3.67 7.571 9.328 5.351 5.169 .000 .000 .000 .000
In the case of human resource reasons, both statements: lack of expertise to implement DM and lack of awareness about DM have also shown a positive and significant result, t(63) = 6.177, p<.000) and t(63) = 9.458, p<.000) respectively (Table 7.11).
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Table 7.11: Individual T-test: Human Resource reasons
Reasons
Descriptive Statistics t-tests
(two-tailed/test value=3)
Mode Median Mean
T value Sig
Lack of expertise to implement data mining
Lack of awareness about data mining 4 4 4 4 3.81 4.03 6.177 9.458 .000 .000
The lack of expertise is identified as a possible reason that would hinder the Jordanian publicly listed companies along with a lack of staff awareness in the decision to adopt DM technology.
The descriptive statistics and series of t-test above indicate that these three issues did contribute to the reasons in the decision not to adopt DM in the Jordanian publicly listed companies. Hypothesis three is supported
Interview data supported these results and supports hypothesis three that technological, organisational and human resource issues are an important challenge faced by the publicly listed companies in adopting DM technology. All six interviewees with the six interviewees who said that the DM tools are not implemented in their companies showed that the most important reason for not adopting DM in publicly listed companies is lack of top management support and lack of training program of how to use DM technology. One interviewee indicated that "One of the most important factor to adopt data mining technology is the top management support, without their support it is impossible to use
such technology"[interviewee 3]. Another interviewee said that "I think data mining
technology will cost our company a lot of money and I do not feel it will be easy to use, we have to pay money to purchase the data mining software, pay money to train our staff how to use it and we need to make sure that we choose the appropriate software to our needs, I feel that we have more urgent problems to look at. We do not need such
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technology in our work, we are happy of what we have, such as Excel software. Furthermore, the most important point to adopt data mining technology is having your top manager support, without it you will not be able to implement it even if you need it" [interviewee1].