Journal of Systems and Information Technology

Jorfi, Saeid; Nor, Khalil Md; Najjar, Lotfi

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-10-2016-0067

PurposeThe purpose of this study is to contribute to the current discussion on strategic alignment of information technology and business (strategic alignment) by developing a model for conceptualizing how strategic alignment can be enabled through of IT flexibility and IT capability.Design/methodology/approachA questionnaire instrument was created to measure the constructs and it was assessed in a pretest and two pilot-tests. The main data set was collected from IT managers (or similar titles) of medium- and large-sized firms.FindingsStrategic alignment seems to be moving closer to firms’ core activity in today’s business environment. The findings revealed that strategic alignment was significantly affected by four dimensions of IT flexibility and IT capability. Furthermore, the significant role of two dimensions of IT flexibility in IT capability was supported.Research limitations/implicationsSingle key informants were used for data collection that could be a potential limitation.Practical implicationsIt seems likely that firms will benefit from the results to manage and control their scarce IT resources more effectively for aligning IT with business strategies, goals and needs.Originality/valueStrategic alignment has become a more complex and unstructured phenomenon and many firms are still considering how to reconcile to it. Furthermore, the lack of empirical examination of IT flexibility and IT capability in relation to strategic alignment from important perspectives, and the lack of research of the dimensions of IT flexibility for supporting IT capability, determines the purpose of this study.

King, Melanie Rose Nova; Dawson, Ray J.; Rothberg, Steve J.; Batmaz, Firat

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-04-2017-0027

PurposeThis study aims to investigate the effectiveness of a theory-driven realist evaluative research approach to better understand complex technology implementations in organizations.Design/methodology/approachAn institution wide e-learning implementation of lecture capture (LC), within a UK University, was chosen, and a realist evaluation framework was used, tailored for educational technology. The research was conducted over four, increasingly focused, evaluation cycles combining engagement analytics, user interviews and theory to refine what works (or does not work), for whom, in which contexts and why.FindingsDespite explicit demand and corresponding investment, overall student engagement is lower than expected. Increased student use appears linked to particular staff attitudes and behaviours and not to specific disciplines or course content. The main benefits of LC are providing reassurance to the majority, aiding revision and understanding for the many and enabling catch-up for the few. Recommendations for future research are based on some unexpected outcomes uncovered, including evolving detrimental student behaviours, policy development based on technological determinism and future learner-centred system development for next-generation LC technologies.Practical implicationsThe realist approach taken, and evaluation framework used, can be adopted (and adapted) for future evaluative research. Domain specific reference models, categorizing people and technology, supported analysis across multiple contexts.Originality/valueThis study responds to a call for more theory-based research in the field of educational technology. The authors demonstrate that a theory-driven approach provides real and practical recommendations for institutions and allows for greater insight into the political, economic and social complexity of technology implementation.

Mandari, Herman Eliewaha; Chong, Yee-Lee; Wye, Chung-Khain

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-01-2017-0005

PurposeGenerally, this paper aims to develop a model by identifying factors which will assist policy makers in implementing m-government in Tanzania. The paper identifies direct and indirect factors which may influence adoption of m-government among the rural farmers in Tanzania.Design/methodology/approachThe paper conducted a survey by using Drop Off/Pick Up method to collect data from rural farmers. Stratified and multi-stage sampling were used to collect 407 valid responses from rural farmers in Tanzania. Data collected were analyzed by using structural equation modeling (SEM).FindingsThe results show that government support has direct influence, while awareness has indirect influence through relative advantage, ease of use, compatibility and visibility. Furthermore, relative advantage, compatibility, ease of use, visibility and results demonstrability have direct influence on rural farmers intention to adopt m-government.Originality/valueThis study contributes to knowledge because no study in this area has been conducted in developing countries to examine factors that influence adoption of m-government. Furthermore, this study tests the mediating effects of perceived characteristics of innovation which have not yet been investigated to date.

Khodabandehlou, Samira; Zivari Rahman, Mahmoud

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-10-2016-0061

PurposeThis paper aims to provide a predictive framework of customer churn through six stages for accurate prediction and preventing customer churn in the field of business.Design/methodology/approachThe six stages are as follows: first, collection of customer behavioral data and preparation of the data; second, the formation of derived variables and selection of influential variables, using a method of discriminant analysis; third, selection of training and testing data and reviewing their proportion; fourth, the development of prediction models using simple, bagging and boosting versions of supervised machine learning; fifth, comparison of churn prediction models based on different versions of machine-learning methods and selected variables; and sixth, providing appropriate strategies based on the proposed model.FindingsAccording to the results, five variables, the number of items, reception of returned items, the discount, the distribution time and the prize beside the recency, frequency and monetary (RFM) variables (RFMITSDP), were chosen as the best predictor variables. The proposed model with accuracy of 97.92 per cent, in comparison to RFM, had much better performance in churn prediction and among the supervised machine learning methods, artificial neural network (ANN) had the highest accuracy, and decision trees (DT) was the least accurate one. The results show the substantially superiority of boosting versions in prediction compared with simple and bagging models.Research limitations/implicationsThe period of the available data was limited to two years. The research data were limited to only one grocery store whereby it may not be applicable to other industries; therefore, generalizing the results to other business centers should be used with caution.Practical implicationsBusiness owners must try to enforce a clear rule to provide a prize for a certain number of purchased items. Of course, the prize can be something other than the purchased item. Business owners must accept the items returned by the customers for any reasons, and the conditions for accepting returned items and the deadline for accepting the returned items must be clearly communicated to the customers. Store owners must consider a discount for a certain amount of purchase from the store. They have to use an exponential rule to increase the discount when the amount of purchase is increased to encourage customers for more purchase. The managers of large stores must try to quickly deliver the ordered items, and they should use equipped and new transporting vehicles and skilled and friendly workforce for delivering the items. It is recommended that the types of services, the rules for prizes, the discount, the rules for accepting the returned items and the method of distributing the items must be prepared and shown in the store for all the customers to see. The special services and reward rules of the store must be communicated to the customers using new media such as social networks. To predict the customer behaviors based on the data, the future researchers should use the boosting method because it increases efficiency and accuracy of prediction. It is recommended that for predicting the customer behaviors, particularly their churning status, the ANN method be used. To extract and select the important and effective variables influencing customer behaviors, the discriminant analysis method can be used which is a very accurate and powerful method for predicting the classes of the customers.Originality/valueThe current study tries to fill this gap by considering five basic and important variables besides RFM in stores, i.e. prize, discount, accepting returns, delay in distribution and the number of items, so that the business owners can understand the role services such as prizes, discount, distribution and accepting returns play in retraining the customers and preventing them from churning. Another innovation of the current study is the comparison of machine-learning methods with their boosting and bagging versions, especially considering the fact that previous studies do not consider the bagging method. The other reason for the study is the conflicting results regarding the superiority of machine-learning methods in a more accurate prediction of customer behaviors, including churning. For example, some studies introduce ANN (Huang et al., 2010; Hung and Wang, 2004; Keramati et al., 2014; Runge et al., 2014), some introduce support vector machine ( Guo-en and Wei-dong, 2008; Vafeiadis et al., 2015; Yu et al., 2011) and some introduce DT (Freund and Schapire, 1996; Qureshi et al., 2013; Umayaparvathi and Iyakutti, 2012) as the best predictor, confusing the users of the results of these studies regarding the best prediction method. The current study identifies the best prediction method specifically in the field of store businesses for researchers and the owners. Moreover, another innovation of the current study is using discriminant analysis for selecting and filtering variables which are important and effective in predicting churners and non-churners, which is not used in previous studies. Therefore, the current study is unique considering the used variables, the method of comparing their accuracy and the method of selecting effective variables.

Lwoga, Edda Tandi; Nagu, Tumaini; Sife, Alfred Said

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-06-2016-0038

PurposeThis paper aims to determine factors that influence people living with HIV (PLHIV) to engage in internet-based HIV information seeking behaviour in selected Tanzanian public regional hospitals.Design/methodology/approachThe authors conducted a questionnaire-based survey to 221 PLHIV in two regional public hospitals in Mwanza and Dar es Salaam, Tanzania. They assessed the validity and reliability of the measurement model by using exploratory factor analysis and also used hierarchical regressions to examine the research hypotheses by using Statistical Package for Social Science.FindingsThe study found that there is low usage of internet (24.3 per cent) to search online HIV information. Factors related to attitude and information source accessibility predicted usage intentions of internet, while facilitating conditions, information source accessibility and usage intention of internet determined actual use of internet among PLHIV. Age moderated the effects of information source quality and social influence on usage intention of internet, and the effects of the information source accessibility and social influence on actual use of internet. The findings imply that younger PLHIV were more likely to use internet to access HIV information than the older respondents due to perceived ease of accessing information and quality of the online content. Further, older PLHIV were more influenced by the views of others when making decisions to use internet.Practical implicationsHealth-care providers and libraries need to conduct regular studies on health needs of patients, and promote benefits of accessing online information; website designers need to design user-friendly databases; public libraries need to include a section on health information; hospital and public librarians need to provide catalogues of health information resources on their websites; and health-care providers need to improve technological infrastructure.Originality/valueThis is a comprehensive study that provides empirical findings to better understand the HIV information seeking behaviour from actual internet users, particularly factors that may influence PLHIV to seek online information in Tanzania.

Gupta, Kriti Priya; Bhaskar, Preeti; Singh, Swati

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-04-2017-0028

PurposeGovernment employees have various challenges of adopting e-government which include administrative problems, technological challenges, infrastructural problems, lack of trust on computer applications, security concerns and the digital divide. The purpose of this paper is to identify the most salient factors that influence the employee adoption of e-government in India as perceived by government employees involved in e-government service delivery.Design/methodology/approachThe paper first identifies different factors influencing the employee adoption of e-government on the basis of literature review and then finds their relative importance by prioritizing them using the analytic hierarchy process (AHP). The AHP is a multi-criteria decision-making (MCDM) tool which combines all the factors into a hierarchical model and quantitatively measures their importance through pair-wise comparisons (Saaty, 1980). Eleven influencing factors of employee adoption of e-government have been identified, which are categorized under four main factors, namely, “employee’s personal characteristics”, “technical factors”, “organizational factors” and “trust”. The data pertaining to pair-wise comparisons of various factors and sub-factors related to the study is collected from ten senior government employees working with different departments and bodies of the Government of National Capital Territory of Delhi.FindingsBased on the results obtained, the findings reveal that “organizational factors” and “technical factors” are the two most important factors which influence the intention of government employees to adopt e-government. Moreover, “training”, “technical infrastructure”, “access speed”, “technical support” and “trust” in infrastructure are the top five sub-factors which are considered to be important for the employee adoption of e-government.Research limitations/implicationsOne of the limitations regarding the methodology used in the study is that the rating scale used in the AHP is conceptual. There are chances of biasing while making pair-wise comparisons of different factors. Therefore, due care should be taken while deciding relative scores to different factors. Also, some factors and sub-factors selected, for the model may have interrelationships such as educational level and training; computer skills and trust; etc., and these interrelationships are not considered by the AHP, which is a limitation of the present study. In that case, the analytic network process (ANP) can be a better option. Therefore, this study can be further extended by considering some other factors responsible for e-government adoption by employees and applying the ANP in the revised model.Practical implicationsThe results of the study may help government organizations, to evaluate critical factors of employee adoption of e-government. This may help them in achieving cost-effective implementation of e-government applications by efficiently managing their resources. Briefly, the findings of the study imply that government departments should provide sufficient training and support to their employees for enhancing their technical skills so that they can use the e-government applications comfortably. Moreover, the government departments should also ensure fast access speed of the e-government applications so that the employees can carry out their tasks efficiently.Originality/valueMost of the existing literature on e-government is focused on citizens’ point of view, and very few studies have focused on employee adoption of e-government (Alshibly and Chiong, 2015). Moreover, these studies have majorly used generic technology adoption models which are generally applicable to situations where technology adoption is voluntary. As employee adoption of e-government is not voluntary, the present study proposes a hierarchy of influencing factors and sub-factors of employee adoption of e-government, which is more relevant to the situations where technology adoption is mandatory. Also, most of the previous studies have used statistical methods such as multiple regression analysis or structural equation modelling for examining the significant factors influencing the e-government adoption. The present study contributes to this area by formulating the problem as an MCDM problem and by using the AHP as the methodology to determine the weights of various factors influencing adoption of e-government by employees.

Taylor, Mark; Reilly, Denis

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-08-2016-0051

PurposeThis paper aims to present the application of situation calculus for knowledge representation in missing persons investigations.Design/methodology/approachThe development of a knowledge representation model for the missing persons investigation process based upon situation calculus, with a demonstration of the use of the model for a missing persons example case.FindingsSituation calculus is valuable for knowledge representation for missing persons investigations, as such investigations have state changes over time, and due to the complexity of the differing investigation activities applicable to different situations, can be difficult to represent using simpler approaches such as tables or flowcharts.Research limitations/implicationsSituation calculus modelling for missing persons investigations adds formalism to the process beyond that which can be afforded by the current use of text, tables or flowcharts. The additional formalism is useful in dealing with the uncertainty present in such investigations.Practical implicationsThe implications are a simplification of the application of the current police guidelines, and thoroughness in the application of such guidelines for missing persons investigations via situation calculus modelling.Social implicationsThis paper supports the management of missing person investigations, by using the most critical variables in a missing persons investigation to determine relevant investigation and search activities applicable to the circumstances of a given case.Originality/valueThe novelty of the knowledge representation approach is the application of situation calculus via state and action vectors and a matrix of fluents to the process of missing persons investigations.

Bueno, Salvador; Gallego, M. Dolores

2017 Journal of Systems and Information Technology

doi: 10.1108/JSIT-06-2017-0043

PurposeTop management support (TMS) is considered as a critical factor for the success of information systems (ISs) projects. The literature shows that TMS has a positive impact on achieving success in ISs’ projects in different aspects. However, the enabling factors for TMS in complex ISs’ projects have barely been tested, something which this study aims to rectify.Design/methodology/approachThis study has designed a research model based on structural equation modelling (SEM) with the intention of analysing the perception of IS end users regarding the effect on TMS of the following factors: technological complexity and training and organizational communication. The application of the study has focused on an enterprise resource planning–open source software (ERP-OSS) environment.FindingsThe findings show how end users have a perception that organizational communication and training have a positive relation with TMS. Based on these findings, the authors have suggested several practical considerations.Research limitations/implicationsThere are two limitations to this study. First, this study is based on the perception of complex IS/IT users. It would be interesting to add the perception of top managers to provide more solid findings. The second limitation is that this study has not suggested any additional potential factors which could affect TMS.Practical implicationsFirst, this article provides a study of the key role of TMS when an organization needs to implement a complex IS/IT. Second, organizations must develop mechanisms for increasing training and communication relating to the new complex IS/IT projects. Finally, the complexity of an IS/IT project does not constitute an enabling factor incentivizing TMS and should therefore not be a determining factor in increasing TMS within an organization selecting an IS/IT.Originality/valueThis study contributes to advancing theory in the field of TMS in information systems projects.