Assessing the Major Factors That Affect the Adoption of Information and Communications Technology on Court Service Delivery in Zambia ()
1. Introduction
ICT (information and communication technology) offers potent tools for productive and efficient corporate operations. Organizations and individuals make efforts to adopt them due to their significance (Johnston & Jali, 2015) . It is impossible to overlook the growing connection between an organization’s ability to use ICT and its capacity to accomplish strategic goals. As a result, information systems have been a crucial instrument in improving service delivery in the public sector, particularly in courts where their usage has grown in popularity ( Larsson, 2002 , quoted in Mbugua, 2012 ). The Judiciary was one of the three branches of government and was established under Article 91(1) of the Zambian Constitution. Its duties include hearing cases involving the constitution, promoting the rule of law, and defending human rights. Prior to 2009, the Judiciary relied mainly on manual processes to administer justice, with the sole courtroom records being the Judges’ handwritten notes, manual filing of case documents, and a lack of qualified court employees.
The High Court of Zambia embraced IS in 2009 as it was thought to be one of the most effective ways to enhance service delivery. This was done in an effort to reduce the growing backlog of cases, poor security and access to case files, delayed settlement of cases, and poor transparency. Furthermore, because less time and money would be spent on commercial litigation by firms, boosting service delivery was considered to improve contract enforcement. This would also free up a significant amount of capital for enterprises, which would promote investments even more (OECD, 2012: p. 51; ICF, 2016) .
13 years later, however, contract enforcement methods and procedures are still onerous, expensive, and time-consuming. Evidence suggests that there is still a backlog of cases; cases are still being settled slowly, and case files are being lost because the transition away from using paper has not been completed. There are still issues with transparency, and not all courts are equipped with the necessary technology, which is a blatant sign that digitization has not been adequately implemented (Kasama, 2020; Banda, 2019: p. 80; Mudenda, 2017) .
Further evidence demonstrates that substantial funds have been spent on the deployment of IS at the High Court of Zambia in Lusaka, primarily by non-governmental organizations (NGO), such as ICF, GIZ, and EU (ICF, 2012) , without the desired net impact. According to previous research, these problems are caused by a variety of factors that have an impact on how well information systems are used, including a lack of top-level management commitment, organizational and technological issues, and a general lack of competence among users ( Mukred et al. 2016 , cited in Masanja and Lwoga, 2020 ). As a result, systems malfunction, the initiative falls short of its goals, and efficient and effective service delivery and organizational performance.
This study, therefore, seeks to assess the major factors that affect adoption of information communications technology at the High Court of Zambia, in Lusaka, by focusing on how critical service delivery components are affected by IS implementation and sustainability. Therefore, this is the gap the study seeks to fill.
2. Literature Review
From the global perspective, the literature shows that there is no consensus on the factors that affect the adoption of ICT and the impact of ICT on court service delivery for both developed and developing economies. For instance, Moghaddam and Khatoon-Abadi (2013) established that the existence of ICT center itself, with various funding sources, reinforced the adoption regardless of the users’ economic status. At the same time, the other factors such as individual, social, the households’ informative & communicative, as well as the innovation related factors were found influential. Similarly, Dixit et al. (2021) highlighted that ICT increases project efficiency in terms of time and expense. The effect on the proper use of ICT in the Indian industry can be seen at all levels and will certainly support the scenarios and outlook for the forthcoming building. It was argued that there is a lack of knowledge in these technologies and that construction industry professionals find it difficult. ICT based technologies can only be used in the construction sector if these methods are adopted by large and mid-scale organizations around the country and set a benchmark for other organizations. Ziemba (2016) indicated that the adoption of ICTs within households was mainly influenced by the economic status of households and cost of ICTs, perceived economic benefits from the usage of ICTs, technological availability and security of ICTs, ICT competences and awareness, as well as satisfaction with the adoption of ICTs. Furthermore, gender, education, and place of residence did not reflect significant differences on the factors. In the same line, AlBar and Hoque (2019) found that relative advantages, top management support, culture, regulatory environment, owner/manager innovativeness and ICT knowledge had a significant relationship with ICT adoption among SMEs in Saudi Arabia, whereas compatibility, complexity and a competitive environment had no significant relationship with ICT adoption. In contrast, Salinas et al. (2017) show that most of the teachers rated themselves at the highest levels of technology adoption. However, the analysis reveals differences between countries associated with individual-type factors, such as the perception of ICT’s contribution to teaching and learning, and the training and knowledge teachers have in this realm. Lastly, Romdoni et al. (2022) established System quality, information quality, and system utilization all have a positive influence on user performance. However, the influence of information quality on usage was not statistically significant. Similarly, Gomes et al. (2018) identified and explained the effects of investment in information and communication technologies on productivity of courts in Brazil.
As regards to the African based studies, the literature revealed that there was also no consensus as to the factors that affect the adoption of ICT on court service delivery for both developed and developing economies. The results varied based on the models used and the factors considered in the analysis. For instance, Kagucia (2015) conducted a critical analysis of the impact of the use of ICT in the Judiciary in so far as enhanced access to justice is concerned. Similarly, Mbugua (2012) indicated that the use of ICT has greatly reduced the level of fraud/corrupt in the court station. In the same line, Chawinga (2017) that the ECMS comes with unlimited benefits and services. In addition, Chawinga et al. (2020) revealed that the implementation of an electronic case management system had impacted positively on the security of court files by easing the tracking and retrieving of case files thereby, contributing to efficiency in justice delivery. Alternatively, Agbo (2015) established study concluded that both home and school environment factors collaborate to affect the use of ICT in learning and teaching computer studies in Ohaukwu L.G Area.
In Zambia, there is lack of empirical research into the factors that affect the adoption of ICT on court service delivery. For instance, Undi-Phiri and Phiri (2022) indicated that the interaction between trust in government and trust in the Internet has a significant effect on the utilization of e-government services. The results further showed that e-services control and effort expectancy had a significant impact on the actual utilization of e-government services. This was supported by the works of Bwalya (2009) who found that lack of adequate ICT infrastructure and political will, provision of content in English other than local languages, lack of proper change management procedures, non-contextualization of e-government practices, etc., contribute much to the delay in appropriate e-government adoption in Zambia. This raises the need to empirically investigate the adoption of ICT and the impact of ICT on court service delivery. Thus, this is the gap the research intends to fill.
3. Methodology
The quantitative approach is aligned to the positivistic thought and is said to be objective in nature. According to Apuke (2017: p. 46) quantitative research is one that deals with quantifying and analyzing variables in order to get results and uses specific statistical techniques to answer questions. In the quantitative research approach, the researcher is independent of the research i.e., the researcher is not involved in actual experiences and thus does not influence the outcome of the study which depends entirely on statistical manipulation. Quantitative research is thus said to be objective in nature (Apuke, 2017: p. 46) . Quantitative findings are likely to be generalized to a whole population or a sub-population because it involves the larger sample which is randomly selected (Carr, 1994) . Besides sampling, data analysis is less time consuming as it uses the statistical software such as SPSS (Connolly, 2007) . Then, quantitative research is to be based on positivist paradigm of measuring variables (Kauber, 1986) . It is for this reason the research adopted a quantitative research approach.
This study used self-administered questionnaires as the mode for collecting information on several features of information systems at the High Court of Zambia in Lusaka. Collecting data using this method as opposed to interviews is more efficient and cost effective for the researcher as the respondents are not geographically dispersed i.e., they are all in one location, and this method is the most appropriate for collecting quantitative data (Bowling, 2009; Bowling, 2005) .
The population of this study comprised of all members of staff at the Lusaka High Court who are direct users of the information systems across four different departments i.e., Judges, Clerks of court, Court Reporters, and information technology (IT) personnel. The Lusaka high court has approximately 180 employees that use information systems and it was from this population that the sample was drawn.
This study will utilize the stratified random sampling method, an approach under probability sampling where homogeneous subgroups in the population are selected and units are randomly selected from each subgroup, usually in proportion to the size of the subgroup (Pazzaglia et al., 2016: p. 7) . As can be seen from Table 1, the total population is divided into four subgroups or strata (Judges, Clerks of session, Court Reporters and IT personnel). The proportion of each group is then established in relation to the total population and the number of participants to be gotten from each stratum is calculated as shown in Table 1.
3.1. Research Model
This study was guided by the updated Information System Success Model (ISSM) developed by DeLone and Mclean (2016) . DeLone and McLean (1992) reviewed prior research and introduced a comprehensive taxonomy of factors contributing to the success of information systems. Generally, the purpose of the model is to measure effectiveness or success of IS implementation in organization (Ojo, 2017) . The model seeks to provide a comprehensive understanding of IS success. The justification of using this model was because it has been tested and validated to assess the adoption and acceptance in MIS among public sectors by scholars such as Abugabah et al. (2009) ; Lwoga (2014) ; Ojo (2017) ; Aziz et al. (2018) ;
Ab Aziz et al. (2019) ; Nugroho & Prasetyo (2018) ; Lwoga (2020) . Furthermore, another reason for using this model is to meet the main objective of this study which is; to assess the factors that affect adoption of ICT and the impact that ICTs have on court service delivery at the High Court of Zambia in Lusaka. The ISS model offers six interrelated constructs of information systems success measure, that include the quality dimensions (information, system, and service quality) which could influence subsequent System Use and User Satisfaction. It is also suggested that performance tagged as net performance will be achieved as a result of use and/or user satisfaction. The net performance could consequently affect User satisfaction and System Use. This study adopted the following key components of the model, which include System quality, Information quality, Service quality, System use, User satisfaction and Net performance (DeLone & McLean, 2016) .
System Quality: This refers to desirable characteristics of an information system such as ease of use, system flexibility, system reliability, and ease of learning, as well as system features of intuitiveness, sophistication, flexibility, and response times (DeLone & McLean, 2016) . Senaratne (2019) , in their attempt at studying the factors affecting the intention to adopt m-Learning, found that system quality had a significant effect on perceived ease of use and usefulness of mobile learning, and concluded that when system quality is good, the efficiency of the m-Learning system is high. Furthermore, scholars such as Ojo (2017) , Lwoga (2020) , and Ho et al. (2019) revealed that system quality had significance influence on the use of hospital information systems and ultimately on user satisfaction.
Information Quality: According to DeLone and McLean (2016) , information quality refers to desirable characteristics such as relevance, understandability, accuracy, conciseness, completeness, currency, timelines, and usability that are responsible for system outputs like management reports and web pages. Information quality was also examined in detail in studies by scholars such as (Lwoga, 2014; Senaratne, 2019; Ab Aziz et al., 2019) . Lwoga (2014) revealed that information quality was a significant determinant of perceived usefulness, but had no relationship with the user satisfaction. Thus, the quality of information stored in the system may have important reason for user intension to use and has high level of satisfaction with using ERMS.
Service Quality: Refers to the quality of the support that system users receive from the information systems organization and IT support personnel such as responsiveness, accuracy, reliability, technical competence, and empathy of the IT personnel staff (DeLone & McLean, 2016) . Service quality directly impacts usage intentions and user satisfaction with the system, which in turn impact the net benefits produced by the system. Scholars such as Lwoga (2014) found that service quality had insignificant relationship with perceived usefulness and user satisfaction. Similarly, Ojo (2017) revealed that service quality significantly influenced the use of the hospital information system.
System Use: DeLone and McLean define system us as the degree and manner in which employees and customers utilize the capabilities of an information system, that is, amount of use, frequency of use, nature of use, appropriateness of use, extent of use, and purpose of use. The actual system use is a well-established construct in the information systems literature as indicated through various studies. For example, scholars such as Hasan et al. described system use as the degree and manner in which staff and customers utilize the capabilities of information systems. Additionally, a study by Ojo (2017) revealed that system use had a more significant influence on perceived net benefits rather than user satisfaction.
User Satisfaction: Refers to users’ level of satisfaction with reports, web sites, and support services (DeLone & McLean, 2016) . A study by Ojo (2017) revealed that the quality dimensions (system, information, and service quality) all significantly influenced users’ satisfaction with the hospital IS. Not only that, but user satisfaction was also not seen to predict perceived benefits. Other studies such as the one by Lwoga (2014) revealed that user satisfaction had significant effects on continual usage intention, and perceived usefulness had significant positive relationship with user satisfaction.
Net Performance: Refers to the extent to which information systems are contributing or not contributing to the success of individuals, groups, organizations, industries, and nations. According to DeLone and McLean (2016) , net benefits include things like improved decision-making, improved productivity, increased sales, cost reductions, improved profits, market efficiency, consumer welfare, creation of jobs, and economic development (DeLone & McLean, 2016) .
It should be noted that the performance of an information system is an important facet of the overall value of the system to its users, group or to the underlying organization. In the ISSM, net system benefits are affected by system use and by user satisfaction with the system. Scholars such as Ojo (2017) revealed that, use of system had a more significant influence on perceived net benefits than user satisfaction. Other scholars such as Nugroho & Prasetyo (2018) revealed that, when the user is satisfied by the information technology used, it will be useful to help the user task completion. Other wider benefits are corporate business processes, the organization’s competitive position, growth in transaction activity, and external organizations. Thus, usefulness and user satisfaction both contribute to net performance of the IS for both individual and organization.
Further, additional variables were added to the research model, which included Self Efficacy and IT Security. The reason of adding these two variables were to measure user’s confidence, skills and performance in usage of information systems. Moreover, these variables are used to measure the confidentiality, integrity and availability of information systems verses usage and satisfactions (Al-Mamary et al., 2014) .
Self-efficacy (SE): Refers to the individual’s capacity to produce important effects. People who are aware of being able to make a difference feel good and, therefore, take initiative. Also, people who perceive themselves as helpless are unhappy and are not motivated for actions (Flammer, 2001) . The system self-efficacy was studied by many scholars. Recently, a study by Senaratne (2019) revealed that mobile Self-efficacy (SE) is significantly affected by the perceived usefulness and perceived ease of use of mobile learning. This means the students will feel that level of capability to achieve expected levels of outcomes when using mobile technologies. It will enhance their feeling that the m-Learning system is useful for their learning and that it is easy to use (Senaratne, 2019) . Other study findings indicate that self-efficacy positively influenced health workers to use eHMIS (Lwoga, 2020) . Moreover, Aldholay et al. (2018) revealed that Self-efficacy has positive impact on both user satisfaction and actual usage in online learning system.
IT Security (ITS): Refers to the practice of defending information from unauthorized access, use, disclosure, disruption, modification, perusal, inspection, recording or destruction and is therefore used to safeguard information of value to the organization (Alhassan & Adjei-Quaye, 2017) . A study by Tu & Yuan (2014) found that IT security controls can be effectively developed, resulting in success of information security management. Another study by Jeong & Kim (2012) revealed that security quality affects intention to use and user satisfaction. On the other hand, Ngulube revealed that IT security is dependent on user compliance to policies and procedures, and it was, therefore, not always possible to ensure that records were managed as securely as they should be, and the biggest issue was that users did not comply with security policies. An earlier study by Bowen et al. revealed that IT security provided by the system had a significant positive relationship with the successful adoption of ERMS.
3.2. Research Hypotheses
The model guiding this study presented in Figure 1, has the following hypotheses that were tested and postulated:
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Figure 1. Proposed model of the study modified from ISSM 2016.
H1. Self-efficacy has positive significance on the use of ICT.
H2. Self-efficacy has positive influence user satisfaction in ICT.
H3. Information quality has positive influence with the use of ICT.
H4. Information quality has significant positive relationship with user satisfaction of ICT.
H5. IT Security has positive influence with the use of ICT.
H6. IT Security has significant positive relationship with user satisfaction of ICT.
H7. System quality has a significant positive relationship with use of ICT.
H8. System quality has positive influence on the user satisfaction of ICT.
H9. Service quality has significant positive relationship on the use of ICT.
H10. Service quality has positive influence on user satisfaction of ICT.
H11. The use of the ICT has positive significant effects on the net performance.
H12. The use of the ICT has positive significance on user satisfaction.
H13. User satisfaction in ICT has positive influence on net performance.
3.3. Model Testing
The correlation analysis performed by Pearson was utilized to test the hypothesis. The dependent and independent variables were examined using SPSS to determine whether there is a linear relationship between them. When the difference between the dependent and independent variables is less than 0.05, there is a significant relationship between them; when the difference is greater than 0.05, there is no relationship.
4. Results
Analysis of Demographics
Figure 2 shows that the majority (60.19%) of the respondents were female while the 38.81% were male. Figure 3 shows that the majority (44.66%) of the
respondents are between the ages of 36 - 35 years, 32.0% are 26 - 35 years, 21.36 % were over 46 years and 1.94% were 19 - 25 years. Figure 4 shows that the majority 33.96% of the respondents stated that they were Clerk of Court and also 33.96% were Judges, 23.30% were Court reporters and 8.74% were Information Technology. Figure 5 shows that the majority 50.96% of the respondents stated that their length of service was 0 - 10 years, 26.47% stated 11 - 20 years, 18.63% stated 21 - 30 years and 3.92% stated 31 - 40 years. Figure 6 shows that the majority 44.66% of the respondents stated that the First Degree was their highest level of education, 30.10% stated Masters and above, 17.48% stated Diploma and 7.77% stated Certificate.
The Factors affecting the Adoption of ICT on Court Service delivery in Zambia.
Pearson Correlation analysis was conducted using SPSS in order to check if there is a linear relationship between the dependent and independent variables.
Table 2 shows that the correction coefficient between the Self efficacy and System Use is 0.383. In line with Self efficacy, the results indicate that there is actually a positive relationship between Self efficacy and System Use as the Pearson correlation indicates 0.383. As seen from Table 2, the P-value for the Self efficacy and System Use using 1 tailed test is 0.000, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Self efficacy and System Use at 0.05 (5 percent) level of significance. Therefore, we can deduce that Self efficacy does have a significant positive relationship with System Use.
Table 2 shows that the correction coefficient between the Self efficacy and User satisfaction in ICT is 0.351. In line with Self efficacy, the results indicate that there is actually a positive relationship between Self efficacy and user satisfaction in ICT as the Pearson correlation indicates 0.351. As seen from Table 2, the P-value for the Self efficacy and user satisfaction in ICT using 1 tailed test is 0.000, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Self efficacy and user satisfaction in ICT at 0.05 (5 percent) level of significance.
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Table 2. SPSS coefficients results summary.
Table 2 shows that the correction coefficient between the Information Quality and use of ICT is 0.223. In line with Information Quality, the results indicate that there is actually a positive relationship between Information Quality and use of ICT as the Pearson correlation indicates 0.223. As seen from Table 2, the P-value for the Information Quality and use of ICT using 1 tailed test is 0.013, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Information Quality and use of ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the Information Quality and User satisfaction in ICT is 0.463. In line with Information Quality, the results indicate that there is actually a positive relationship between Information Quality and user satisfaction in ICT as the Pearson correlation indicates 0.463. As seen from Table 2, the P-value for the Information Quality and User satisfaction in ICT using 1 tailed test is 0.000, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Information Quality and user satisfaction in ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the IT Security and the use of ICT is 0.257. In line with IT Security, the results indicate that there is actually a positive relationship between IT Security and the use of ICT as the Pearson correlation indicates 0.257. As seen from Table 2, the P-value for the IT Security and the use of ICT using 1 tailed test is 0.005, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the IT Security and the use of ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the IT Security and User satisfaction in ICT is 0.272. In line with IT Security, the results indicate that there is actually a positive relationship between IT Security and user satisfaction in ICT as the Pearson correlation indicates 0.272. As seen from Table 2, the P-value for the IT Security and User satisfaction in ICT using 1 tailed test is 0.003, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the IT Security and User satisfaction in ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the System quality and the use of ICT is 0.301. In line with System quality, the results indicate that there is actually a positive relationship between System quality and the use of ICT as the Pearson correlation indicates 0.301. As seen from Table 2, the P-value for the System quality and the use of ICT using 1 tailed test is 0.001, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the System quality and the use of ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the System quality and User satisfaction in ICT is 0.281. In line with System quality, the results indicate that there is actually a positive relationship between System quality and user satisfaction in ICT as the Pearson correlation indicates 0.281. As seen from Table 2, the P-value for the System quality and User satisfaction in ICT using 1 tailed test is 0.002, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the System quality and User satisfaction in ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the Service quality and the use of ICT is 0.304. In line with Service quality, the results indicate that there is actually a positive relationship between Service quality and the use of ICT as the Pearson correlation indicates 0.304. As seen from Table 2, the P-value for the Service quality and the use of ICT using 1 tailed test is 0.001, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Service quality and the use of ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the Service quality and User satisfaction in ICT is 0.591. In line with Service quality, the results indicate that there is actually a positive relationship between Service quality and user satisfaction in ICT as the Pearson correlation indicates 0.591. As seen from Table 2, the P-value for the Service quality and User satisfaction in ICT using 1 tailed test is 0.000, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the Service quality and User satisfaction in ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the use of the ICT and the net performance is 0.565. In line with use of the ICT, the results indicate that there is actually a positive relationship between use of the ICT and the net performance as the Pearson correlation indicates 0.565. As seen from Table 2, the P-value for use of the ICT and the net performance using 1 tailed test is 0.000, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between use of the ICT and the net performance at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between the use of the ICT and User satisfaction in ICT is 0.295. In line with the use of the ICT, the results indicate that there is actually a positive relationship between the use of the ICT and user satisfaction in ICT as the Pearson correlation indicates 0.295. As seen from Table 2, the P-value for the use of the ICT and User satisfaction in ICT using 1 tailed test is 0.001, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. This means that there is a statistical relationship between the use of the ICT and User satisfaction in ICT at 0.05 (5 percent) level of significance.
Table 2 shows that the correction coefficient between User satisfaction in ICT
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Table 3. Summary of hypotheses results.
and the net performance is 0.174. In line with User satisfaction in ICT, the results indicate that there is actually a positive relationship between User satisfaction in ICT and the net performance as the Pearson correlation indicates 0.174. As seen from Table 2, the P-value for User satisfaction in ICT and the net performance using 1 tailed test is 0.041, this figure is less than the 0.05 (5 percent) level of significance thus we reject the null hypothesis. A summary of the hypotheses results as can be seen in Table 3.
5. Conclusion
The main purpose of this study was to access the factors that affected the adoption ICTs on court service delivery in Lusaka. The findings revealed that there was a strong positive statistical relationship between the use of ICT and self-efficacy, Information Quality, IT Security, System quality, service quality, net performance and User Satisfaction in ICT. Furthermore, the findings revealed that there was a strong positive statistical relationship between the user satisfaction in ICT and self-efficacy, Information Quality, IT Security, System quality, service quality, net performance and the use of ICT. Thus, the study concludes that an increase in Self-efficacy, Information Quality, IT Security, System quality, service quality, net performance, and User Satisfaction in ICT can enhance the use of ICT, and an increase in self-efficacy, Information Quality, IT Security, System quality, service quality, net performance and the use of ICT can also enhance user satisfaction in ICT.
6. Limitations of the Study
This study focused on investigating the major factors that affect the adoption of Information and Communications Technology on Court Service delivery in Zambia. It is imperative that another study be conducted to the adoption of ICT on court service delivery in Zambia by using other models like the UTAUT model.
7. Recommendations
1) Although the current study is based on a moderate sample of participants, IT Security in the use of information and communications technology as regards to court delivery in Zambia guarantees confidentiality, integrity, and availability of information. The Judiciary of Zambia is required to consider the use of security policy in order to protect public information from legitimate users and ensure security;
2) Although the Service Quality was statistically significant to both System use and User satisfaction in the adoption of ICT, ICT provides reliable services as well as technical support provided by authorities that satisfy users. The government is required to build technical capability of users to make them help each other when they are facing difficulties in using ICT system in their daily activities. Also, the Judiciary of Zambia has to facilitate the technical support team or helpdesk to work 24 hours per week in order to support users for the effective use of the system;
3) Although the Information quality was a significant factor in influencing the use of ICT, it is important for the organization to improve the overall court reporting process, and case record management systems to enhance the quality of proceedings as well as reducing human errors in ICT;
4) Though System quality was a statistically significant factor in both System use and User Satisfactions in ICTs, the Judiciary of Zambia is required to consider System quality by ensuring these four items which include: usefulness, ease of use, easy to learn and retrieve information easily. Thus, these four items help users to accomplish tasks quickly and improve job performance as well as get the sense of satisfaction while providing quality service delivery;
5) The Judiciary of Zambia is required to continue building capacity of users on the use of ICTs, since the system has positive effects on public information management. It, is, therefore, important to provide regular training at least twice annually on how to fully utilize the available ICT systems. Also, the Judiciary of Zambia should improve education, seminars, and training policies regularly; as well as promote leaders and improve the ICT facilities under the organization dynamics for the future uses to increase the management of electronic records;
6) The findings of the study seem to indicate that electronic records tools and guidelines were implemented, although ICT users at the Judiciary of Zambia were aware, however, they were not widely used in their responsibilities. Thus, the study recommends that the Judiciary of Zambia department that oversees the management of all public records required to ensure the administration of court service delivery and management of records and archives are updating and implementing these tools and guidelines.
Acknowledgements
I would like to acknowledge and thank management of Judiciary of Zambia, the High Court and all the other Higher Courts for enabling me to conduct this study. I would like to also thank all those who took part and time to respond to the questionnaires in the study. This research would not have been possible without considerable information and facts gotten from other researchers and sources that have researched extensively on court service delivery and ICTs, the researcher duly acknowledges their input to the study.
I wish to extend a heartfelt thank you to all the lecturers at the University of Zambia, Graduate School of Business, for all the support I received throughout this study.