Editorial

Citation

Kamal, Z.I.a.M. (2014), "Editorial", Journal of Enterprise Information Management, Vol. 27 No. 4. https://doi.org/10.1108/JEIM-03-2014-0025

Editorial

Article Type: Editorial From: Journal of Enterprise Information Management, Volume 27, Issue 4

It gives us great pleasure to welcome our readers to the fourth issue of the 27th volume of Journal Enterprise Information Management (JEIM), and to express our appreciation for their continuous support during the past year. The continuous update of the journal's scope to promote theory and practice has led to an increase in submissions that has allowed us to further the quality of the journal. This issue incorporates excellent “quality” submissions that focus on providing pragmatic contributions to theory and practice.

The fourth issue of volume 27 commences with a research paper by Arpan Kumar Kar and Ashis Kumar Pani, entitled “How can a group of procurement experts select suppliers? An approach for group decision support”. Effective supply chain management manages supply chain activities to maximise customer value and realise a sustainable competitive advantage, resulting in the overall competitiveness of the organisation (Hassini, 2008). The authors argue that it is vital to optimise imperative activities (e.g. procurement management, supplier selection, etc.) in the supply chain using systemic approaches. According to Kerr and Tindale (2004), intricate processes and the communal intellect of a group of decision makers in agreement is often considered as more effective than the same decision makers functioning in segregation and then “summed” together. The literature review presented in the paper argues that there is limited research focusing on applying theories for group decision making to the supplier selection problem, even though on an individual basis both domains have a plethora of literature. The authors assert that this literature void highlights the need to assimilate the two forms of knowledge (i.e. group decision making and supplier selection problem) to supplement decision support literature in procurement. In order to address this void, the authors use the analytic hierarchy process (AHP) technique (Saaty, 1980) to provide group decision support to the supplier selection problem, thereby, using a case study to test the theories of consensual group decision making when compared with other approaches. The empirical research clearly endorses that Row Geometric Mean Method of the AHP as a robust technique for solving supplier selection-related problems.

The above paper is followed by another research paper by Ying Xie, Colin James Allen and Mahmood Ali, entitled “An integrated decision support system for ERP implementation in small and medium sized enterprises”. Over several years, enterprise resource planning (ERP) systems have supported large and multinational organisations in automating their core operations including optimising the flow of information and resources throughout the entire supply chain (Umble et al., 2003; King and Burgess, 2006; Raymond and Uwizeyemungu, 2007). Despite the many success stories (e.g. ranging from the airline industry through to the construction sector, implementing ERP is still considered as a challenging task specifically in SMEs (Sun et al., 2005). The authors argue that in general when ERP employment is considered, there are several parameters and dynamics affecting its successful implementation and as a result, it becomes demanding to develop a clear-cut mathematical model measuring the relationships among these parameters and dynamics. In line with these literature conceptions, this research develops an integrated decision support system for ERP implementation (i.e. DSS_ERP) to facilitate resource allocation and risk analysis in SMEs. This system is a combination of:

• analytical regression models;

• a simulation model; and

• a nonlinear programming model.

All the above are pooled together to predict ERP project implementation outcomes and facilitate allotting resources. To develop a parametric effort prediction system for ERP implementation in SMEs, this research captures the predominant critical success factors (CSFs) impacting on ERP implementation performance, and models them through regression analysis that creates expected values and provides confidence levels. To quantify the response variable, i.e. dynamic ERP implementation performance, into predictor variables, i.e. time and cost spent on CSFs, Cantu's framework (i.e. a prominent framework used for investigating CSFs exclusively for ERP implementation in SMEs) is adopted in this research with some revisions. The authors aim to contribute to the scarce research on ERP implementation using scientific methods, i.e. by constructing a novel nonlinear programming model for ERP implementation under time and budget limitations, facilitating resource allocations in an ERP implementation, which has not been reported in any previous research.

Then we have Mahmud Akhter Shareef, Vinod Kumar, Uma Kumar and Yogesh Dwivedi presenting their research paper, entitled “Factors affecting citizen adoption of transactional electronic government”. This research is about investigating the adoption criteria of citizens’ e-government services at the transaction maturity stage. Gottschalk (2009) argues that from the developer's and users’ perspective, different e-government stages, i.e. service maturity and offerings have substantial differences in:

• characteristics;

• functionality;

• facilities;

• technological association; and

• security and privacy concerns.

Over the years, a number of countries (e.g. from the European to Middle Eastern region) have enthusiastically invested large amounts of resources to increase the efficiency and effectiveness of their governments and to achieve seamless service delivery, i.e. in the form of transaction phase in e-Government (Jansen et al., 2010; Johnson, 2012). Despite the huge investment, the authors argue that there is limited research conducted that focuses on adoption criteria distinctively for transaction stage of e-Government. In so doing, this study, using the primary e-Government Adoption Model, i.e. GAM model (e.g. Shareef et al., 2011) under the same context following the same methodology, has attempted to identify and model adoption criteria of citizens for e-Government service at the transaction maturity stage, which is manifested by multidimensional aspects like technological, cultural, social, behavioural, political, economic and organisational. The research methodology adopted in this study is similar to that adopted by Shareef et al. (2011) for developing and validating GAM model. The survey-based empirical research was conducted among the citizens of Ontario, Canada, who had experience of using Canadian e-Government system. A total of 2,200 survey-based questionnaires were disseminated in the four cities in a total three month period with a response rate of 11 per cent (i.e. 245 questionnaires received) was achieved. The authors claim originality in this research by concluding that e-Government functional characteristics are not only different at varying levels of service maturity, but adoption factors at different levels of service maturity are also potentially different. From static to interaction to transaction, citizens perceive different factors to be important for creating the behavioural attitude and intention to accept the e-Government system and to use it.

Thereafter, we have another research paper by Poonam Garg and Divya Agarwal, entitled “Critical success factors for ERP implementation in a Fortis hospital: an empirical investigation”. In this paper, Poonam and Divya conduct their empirical research in Fortis Healthcare – a well-established chain of super speciality hospitals in Delhi, Bangalore and across others parts of India. Healthcare is considered as one of the fastest growing sectors in India. According to Fitch – the rating agency (as reported in this paper), the healthcare sector in India is currently valued to be worth US$65 billion and is expected to reach US$100 billion by 2015. Similarly and according to Pricewaterhouse Coopers in its study, the healthcare sector is expected to touch US$250 billion by 2020. Over the years, the trend has shifted to a more intricate paradigm in response to maximising profits, reducing costs and achieving a seamless healthcare continuum. In this context, it has become imperative to improve the efficiency of back-end business across functions such as supply chain management, inventory management, human resource management, patient administration management, patient care management, finance and billing, etc. The authors argue that this can be accomplished by business process optimisation and technology enablement through successful hospital ERP implementation. In so doing, this research examines the success of ERP implementation based on five identified items:

• top management commitment;

• user involvement;

• business process reengineering;

• project management; and

• ERP teamwork and composition factors at Fortis hospital, Bangalore, India.

This empirical research also examines hypotheses and inspects the conjectural relationships among critical success items and success of ERP implementation. This study was based on empirical data collected through interviewing managers, key users of Fortis hospital who had an important role during ERP implementation and consultants who participated in this project. The authors claim to contribute to the academic literature by generating practical evidence to support the theories of ERP implementation success and CSFs. This study has succeeded to develop a framework and examined the relationships among the abovementioned five items and success of ERP implementation at Fortis hospital, India.

Subsequently, we have Poonam Garg and Atul Garg presenting a research paper, entitled “Factors influencing ERP implementation in retail sector: an empirical study from India”. In this paper, Poonam and Divya focus on the retail sector where integration of the various business functions is considered as an essential prerequisite for any retail organisation. Poonam and Divya also report that retail chain in India heavily depend on ERP-based infrastructure to track the:

• supply chain;

• financial process;

• inventory;

• sales and distribution;

• overall visibility of the consumer across every channel; and

• take customer centricity to a new level.

Despite the huge success of ERP, many retailers in India are still using various incongruent systems that are not integrated with each other to manage their core business functions, resulting in lower levels of effectiveness and efficiency. On the other hand, there are several exemplars highlighting ERP implementation failures (e.g. Somers and Nelson, 2001; Singh and Wesson, 2009), clearly indicating the compelling reason for investigating the factors that may influence the success of ERP implementation in organisations. In line with these conceptions, Poonam and Atul conducted an empirical study to provide some insight into those factors that may influence the ERP implementation success in the India retail sector and further examine the relationship between factors that influence ERP implementation and the success of ERP implementation in Indian retail sector. In order to understand the influencing factors of ERP implementation in this sector, the authors employed a survey strategy. The data were collected through a survey from practitioner such as project sponsors, project managers, implementation consultants and team members who were involved in ERP implementation in the retail sector. The results of the study have empirically verified that strategic, technological, people and project management factors are positively influencing ERP implementation success.

The above ERP implementation research is following by another survey-based research by Rakhi Tripathi and M.P. Gupta, entitled “Evolution of government portals in India: mapping over stage models”. Over the last decade, a number of e-Government stage models have been proposed. For instance, according to Coursey and Norris (2008) a number of these models are partially descriptive, somewhat foretelling and relatively normative. Sandoval-Almazan and Gil-Garcia (2012) argue that in essence all these models attempt to describe what might be considered as the normal evolution of e-Government from its most basic online presence (i.e. static web pages, cataloguing) to fully developed e-Government (i.e. transformational government). In examining these models, it appears that, for the most part, the descriptions in these models provide a reasonably accurate portrait of e-Government in its early stages, from initial web presence to information provision to interactivity. Beyond this, however, the models become both predictive and normative and their empirical accuracy declines impulsively. In line with these conceptions, this paper attempts to examine conception, i.e. whether the e-Government stage models developed over the last one decade offer a factual indication of e-Government development in a developing country like India. A number of methods can be used to assess e-Government stage model for instance:

• statistical methods;

• best practices;

• historical analyses; and

• questionnaires.

In this study, the latter questionnaire method is used because it offers an opportunity to capture the prevailing perceptions of users-stakeholders. Thus, this exploratory study was conducted through a survey-based questionnaire from 300 portals of government departments and public sector undertakings (PSUs) in India. Empirical findings indicate that on e-Government stage model; only 28 per cent of the surveyed government department have achieved the transactional stage whereas 58 per cent have reached at least a minimum level of vertical integration. In total, 74 per cent of PSUs are reported as being at a transactional level, with 69 per cent having achieved at least a minimum level of vertical integration. The findings also indicate that there are few government portals that do not follow the proposed stage models and achieve the integration level before attaining the transaction level.

Then we have Dana Al-Najjar and Basil Al-Najjar with there research paper, entitled “Developing a multi stage predicting system for corporate credit rating in emerging markets: Jordanian case”. Dana and Basil report on the significance of credit risk forecasting by stating that it has gained substantial concerns due to financial market instability and the globalised capital markets. Recently, however, a number of research studies have devoted their focus to developing prediction models for credit ratings (Manganelli and Engle, 2001; Schuermann, 2004; Huang et al., 2004). Credit ratings are imperative for organisations because of the high risk associated with the incongruous credit decisions that may result in great financial damages. The literature indicates different techniques that can be used to examine credit ratings, for instance:

• artificial intelligence approaches;

• multi-criteria decision-making methods;

• mathematical programming techniques;

• linear regression analysis;

• logistic regression modelling; and

• linear discriminate analysis.

In this research, Dana and Basil apply two types of neural networks: Kohonen self-organised mapping and back propagation neural network models (BPNN) – researchers such as West (2000) and Yijun et al. (2009) support that these two types are efficient and form a useful method for corporate credit rating predictions. The authors made use of interim bulletins from the Amman Stock Exchange in Jordan, company guides and annual financial reports. Jordanian manufacturing companies (i.e. a sample of nonfinancial companies listed at Amman Stock Exchange during the period from 2000 to 2007) were selected as they share similar features of companies in developed markets and also due to the availability of the financial data. The prime conclusion of this research is that the proposed neural network technique predicts appropriately the firms which are in a default situation in Amman Stock Exchange for the investigated period in this research.

Finally, we have Hemlata Gangwar, Hema Date and A.D. Raoot presenting their review paper, entitled “Review on IT adoption: insights from recent technologies”. This review paper examines research studies from 2000 to 2012 by addressing technology adoption in the context of:

• e-Commerce;

• ERP systems;

• radio-frequency identification;

• electronic data interchange; and

• knowledge management.

Based on their analysis of the extant literature, the authors report that technology adoption is one of the widely investigated areas in the information technology (IT)/information systems (IS) domain. A number of research studies within the IT/IS area have led to the development of conceptual models and frameworks (e.g. Technology Acceptance Model, Innovation Diffusion Theory, Theory of Reasoned Action, Theory of Planned Behaviour, Technology-Organisation-Environment Framework) to understand the relationship of those factors associated with the adoption behaviour. These models and frameworks have primarily aimed at understanding, anticipating and explicating factors inducing adoption behaviour at both individual and organisational levels, to accept and use technological innovations. In line with this research stream, the paper scrutinises such relevant studies including an appreciation of the importance associated with the TAM model (Davis, 1989) and TOE framework (Tornatzky and Fleischer, 1990), including identifying parameters necessary to integrate TAM with TOW for firm-level technology adoption. Through this integration, the authors intend to enhance extrapolative authority of the resulting model. The authors assert that this review paper presents a set of key variables which can be employed to further investigate adoption of similar technologies in the author's future research endeavours.

We would very much like to thank all our contributors for their excellent high-quality contributions to this regular issue and hope JEIM readers will find the submissions stimulating, original and valuable.

Zahir Irani and Muhammad Kamal

References

Coursey, D. and Norris, D. (2008), “Models of E-Government: are they correct? An empirical assessment”, Public Administration Review, Vol. 68 No. 3, pp. 523-536

Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13 No. 3, pp. 319-340

Gottschalk, P. (2009), “Maturity levels for interoperability in digital government”, Government Information Quarterly, Vol. 26 No. 1, pp. 42-50

Hassini, E. (2008), “Building competitive enterprises through supply chain management”, Journal of Enterprise Information Management, Vol. 21 No. 4, pp. 341-344

Huang, Z., Chen, H., Hsu, C.-J., Chen, W.-H. and Wu, S. (2004), “Credit rating analysis with support vector machines and neural networks: a market comparative study”, Decision Support Systems, Vol. 37 No. 4, pp. 543-558

Jansen, J., de Vries, S. and van Schaik, P. (2010), “The contextual benchmark method: benchmarking e-government services”, Government Information Quarterly, Vol. 27 No. 3, pp. 213-219

Johnson, M. (2012), “A study of e-market adoption barriers in the local government sector”, Journal of Enterprise Information Management, Vol. 25 No. 6, pp. 509-536

Kerr, N.L. and Tindale, R.S. (2004), “Group performance and decision-making”, Annual Review of Psychology, Vol. 55, pp. 623-655

King, S.F. and Burgess, T.F. (2006), “Beyond critical success factors: a dynamic model of enterprise system innovation”, International Journal of Information Management, Vol. 26 No. 1, pp. 59-69

Manganelli, S. and Engle, R.F. (2001), “Value at risk models in finance”, European Central Bank Journal, Vol. 4 No. 75, pp. 1-40

Raymond, L. and Uwizeyemungu, S. (2007), “A profile of ERP adoption in manufacturing SMEs”, Journal of Enterprise Information Management, Vol. 20 No. 4, pp. 487-502

Saaty, T.L. (1980), Multicriteria Decision-Making: The Analytic Hierarchy Process, McGraw-Hill, New York, NY

Sandoval-Almazan, R. and Gil-Garcia, J.R. (2012), “Are government internet portals evolving towards more interaction, participation, and collaboration? Revisiting the rhetoric of e-government among municipalities”, Government Information Quarterly, Vol. 29 No. 2, pp. 72-81

Schuermann, T. (2004), “A review of recent books of credit risk”, Federal Reserve Bank of New York, Vol. 10 No. 1, pp. 1-11

Shareef, M.A., Kumar, U., Kumar, V. and Dwivedi, Y.K. (2011), “E-government adoption model (GAM): differing service maturity levels”, Government Information Quarterly, Vol. 28 No. 1, pp. 17-35

Singh, A. and Wesson, J. (2009), “Evaluation criteria for assessing the usability of ERP systems”, Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists, pp. 87-95

Somers, T.M. and Nelson, K.G. (2001), “The impact of critical success factors across the stages of enterprise resource planning implementations”, Proceedings of the 34th Hawaii International Conference on System Sciences, No. 8016, Outrigger Wailea Resort, Island of Moui, 3-6 January

Sun, A.Y.T., Yazdani, A. and Overend, J.D. (2005), “Achievement assessment for enterprise resource planning (ERP) system implementations based on critical success factors (CSFs)”, International Journal of Production Economics, Vol. 98 No. 2, pp. 189-203

Tornatzky, L. and Fleischer, M. (1990), The Process of Technology Innovation, Lexington Books, Lexington, MA

Umble, E.J., Haft, R.R. and Umble, M.M. (2003), “Enterprise resource planning: implementation procedures and critical success factors”, European Journal of Operational Research, Vol. 146 No. 2, pp. 241-257

West, D. (2000), “Neural network credit scoring models”, Computers and Operations Research, Vol. 27 No. 11, pp. 1131-1152

Yijun, L., Qiuru, C., Ye, L., Jin, Q. and Feiyue, Y. (2009), “Artificial neural networks for corporation credit rating analysis”, International Conference on Networking and Digital Society, Vol. 1, pp. 81-84