Archives For Publications

ISM Editorial Team Appointment

Tuesday, September 12, 2017

I have joined the Editorial Team of Information Systems Management. Journal information:

Information Systems Management (ISM) is the on-going exchange of academic research, best practices, and insights based on managerial experience. The journal’s goal is to advance the practice of information systems management through this exchange.
ISM is indexed and abstracted in: Science Citation Index Expanded, Scopus, and Inspec, among others.

Excited about the new appointment!

Developing BI capabilities

Tuesday, August 1, 2017

A new publication appeared in July 2017 issue of Journal of the Association for Information Systems on developing BI capabilities, co-authored with U. Kulkarni and J. A. Robles-Flores: Business Intelligence Capability: The Effect of Top Management and the Mediating Roles of User Participation and Analytical Decision Making Orientation. Here is the abstract:

In this study, we draw on the structurational model of technology in an institutional setting to investigate how top management affects the development of a firm’s business intelligence (BI) capability. We propose a multiple mediator model in which organizational factors, such as user participation and analytical decision making orientation, act as mediating mechanisms that transmit the positive effects of top management championship to advance a firm’s BI capability. BI capability has two distinct aspects: information capability and BI system capability. Drawing on data collected from 486 firms from six different countries, we found support for the mediating effects of top management championship through user participation and analytical decision making orientation. These findings contribute to a nuanced understanding of how firms can develop BI capability. This study is one of the first to comprehensively investigate the antecedents of BI capability.

The purpose of MIS Quarterly Research Curations is to identify topics of significant interest to the IS field and other disciplines, identify MIS Quarterly articles that make significant contributions to these topics, and provide researchers with easy access to a bundle of MIS Quarterly articles on which to further build or extend research.

The Information Privacy curation, co-authored with H. Jeff Smith (Miami University), James Y.L. Thong (Hong Kong University of Science and Technology), and Sunil Wattal (Temple University), highlights the 22 articles with a primary focus on information privacy that have been published in MIS Quarterly. The goal of this curation is to offer a starting point for future research on information privacy.

A new work appears in May 2017 issue of Expert Systems with Applications on the topic of sentiment prediction from customer reviews, co-authored with M. Castelli, L. Manzoni, and L. Vanneschi: An expert system for extracting knowledge from customers’ reviews: The case of, Inc.. Here is the abstract:

E-commerce has proliferated in the daily activities of end-consumers and firms alike. For firms, consumer satisfaction is an important indicator of e-commerce success. Today, consumers’ reviews and feedback are increasingly shaping consumer intentions regarding new purchases and repeated purchases, while helping to attract new customers. In our work, we use an expert system to predict the sentiment of a product considering a subset of available customers’ reviews.

A new study appears in October 2016 issue of Journal of Business Research on the topic of consumer privacy concerns in adopting new technological innovations, co-authored with C. Lancelot Miltgen, J. Henseler, and C. Gelhard, : Introducing new products that affect consumer privacy: A mediation model. Here is the abstract:

Many innovative products can only fully deploy their value if they rely on consumers’ personal information. This issue challenges the confidence that consumers have in new innovations, and revolutionizes marketing practices. Malhotra, Kim, and Agarwal’s (2004) framework provides the theoretical basis for hypotheses on the consequences of privacy concerns. An empirical study in the context of four pervasive IT innovations involving various privacy issues helps to test these hypotheses. The findings consistently show that privacy concerns have an adverse effect on consumers’ intention to accept IT innovation. However, trust and risk perceptions both mediate this relationship. By understanding the underlying mechanism, firms can alleviate the potential downsides of their products and increase the odds of their market success.

A new publication appeared in April 2016 issue of Government Information Quarterly on the role of ‘institutional entrepreneurs’ for digital era governance, co-authored with R. Tassabehji and R. Hackney: Emergent digital era governance: Enacting the role of the ‘institutional entrepreneur’ in transformational change. Here is the abstract:

As e-government matures the realisation of its potential to enact organisational change in the public sector remains unclear. This study examines e-government towards digital era governance (DEG) and the actors involved in this transformational change. We draw upon the concept of ‘enactment’ as a lens to provide insights into relevant theoretical issues. These are operationalised through an enhanced Technology Enactment Framework (TEF) to consider reforms to explore the DEG environment and, specifically, the interventions of the CIO on e-government policies. We employed a case analysis approach from public sector authorities in the US States of California and Nevada with data from CIOs and other key informants. Our findings reveal how public sector CIOs adopt the role of an ‘institutional entrepreneur’, who demonstrate a series of initiatives augmented through identified behaviours. These relate to proactive community mobilisation (leadership, member focus) and legitimisation (discourse, success stories). We outline the policy implications of DEG and the risk factors of senior managers who enact these processes towards complex technological change. Furthermore, the characterisation of institutional entrepreneurial enactment appears to be extremely beneficial to the transformation to DEG within any contemporary public sector context.

CSFs for implementing BI systems

Wednesday, December 23, 2015

There is a new publication in January 2016 issue of Journal of the Association for Information Science and Technology on the topic of business intelligence systems implementation, co-authored with W. Yeoh: Extending the understanding of critical success factors for implementing business intelligence systems. It is an important step in extending our understanding of critical success factors for implementing business intelligence systems. Here is the abstract:

Extant studies suggest implementing a business intelligence (BI) system is a costly, resource-intensive and complex undertaking. Literature draws attention to the critical success factors (CSFs) for implementation of BI systems. Leveraging case studies of seven large organizations and blending them with Yeoh and Koronios’s (2010) BI CSFs framework, our empirical study gives evidence to support this notion of CSFs and provides better contextual understanding of the CSFs in BI implementation domain. Cross-case analysis suggests that organizational factors play the most crucial role in determining the success of a BI system implementation. Hence, BI stakeholders should prioritize on the organizational dimension ahead of other factors. Our findings allow BI stakeholders to holistically understand the CSFs and the associated contextual issues that impact on implementation of BI systems.

A new study emphasizing the value of predictive analytics for predicting energy consumption, co-authored with M. Castelli, L. Trujillo, and L. Vanneschi, is scheduled to appear in September 2015 issue of Energy and Buildings. The work titled Prediction of energy performance of residential buildings: A genetic programming approach shows – through an experimental research based on real-data – how utilizing predictive analytics can assist the prediction of energy consumption in residential buildings. Abstract:

Energy consumption has long been emphasized as an important policy issue in today’s economies. In particular, the energy efficiency of residential buildings is considered a top priority of a country’s energy policy. The paper proposes a genetic programming-based framework for estimating the energy performance of residential buildings. The objective is to build a model able to predict the heating load and the cooling load of residential buildings. An accurate prediction of these parameters facilitates a better control of energy consumption and, moreover, it helps choosing the energy supplier that better fits the energy needs, which is considered an important issue in the deregulated energy market. The proposed framework blends a recently developed version of genetic programming with a local search method and linear scaling. The resulting system enables us to build a model that produces an accurate estimation of both considered parameters. Extensive simulations on 768 diverse residential buildings confirm the suitability of the proposed method in predicting heating load and cooling load. In particular, the proposed method is more accurate than the existing state-of-the-art techniques.

Embryonic data mining success

Wednesday, April 22, 2015

A study exploring the critical success factors of embryonic data mining implementation, co-authored with U. Bole, J. Žabkar, G. Papa, and J. Jaklič, has appeared in April 2015 issue of International Journal of Information Management. In the work titled A case analysis of embryonic data mining success we propose and validate, through a series of cases, a conceptual framework to guide practitioners’ adoption of data mining practices. Abstract:

Within highly competitive business environments, data mining (DM) is viewed as a significant technology to enhance decision-making processes by transforming data into valuable and actionable information to gain competitive advantage. There appears, however, to be a dearth of empirical case studies which consider in detail the initial stages in DM management to enable apt foundation for its later successful implementation. Our research applied a multi-method strategy to determine the critical success factors of embryonic DM implementation. We propose and validate, through a series of cases, a conceptual framework to guide practitioners’ adoption of DM. Our findings reveal additional issues for applied decision making in the context of DM success.

Predicting natural disasters

Thursday, April 2, 2015

A new publication emphasizing the role of predictive analytical capabilities in natural disaster management, co-authored with M. Castelli and L. Vanneschi (2015): Predicting Burned Areas of Forest Fires: An Artificial Intelligence Approach appeared in one of the most prestigious international journals in fire ecology field. Abstract:

The ability of accurately predicting forest fire areas may significantly aid optimizing fire management efforts. Given the complexity of the task, powerful computational tools are needed for predicting the amount of area that will be burned during a forest fire. The purpose of this study was to develop an intelligent system based on genetic programming for the prediction of burned areas, using only data related to the forest under analysis and meteorological data. We used geometric semantic genetic programming based on recently defined geometric semantic genetic operators for genetic programming. Experimental results showed the appropriateness of the proposed system for the prediction of the burned areas. In particular, the obtained results were significantly better than those produced by standard genetic programming and other state of the art machine learning methods.

Academic Journal Guide 2015

Thursday, February 26, 2015

At last, the long-awaited Association of Business Schools’ Academic Journal Guide 2015 is out!

IMDS Editorial Team Appointment

Friday, February 20, 2015

I have joined the Editorial Team of Industrial Management & Data Systems. Journal information:

Industrial Management & Data Systems (IMDS) provides the necessary information to enable managers to exploit the potential of new technology knowledgeably and improve understanding of all aspects of management activity such as management information systems, business process management and supply chain management.
IMDS is indexed and abstracted in: Science Citation Index Expanded and Scopus, among others.

Very excited about the new appointment!

A new publication linking information-sharing values to business intelligence systems use, co-authored with R. Hackney, P. S. Coelho, and J. Jaklič (2014): How information-sharing values influence the use of information systems: An investigation in the business intelligence systems context, appeared in one of the leading IS journals. The work significantly adds to our understanding of how information-sharing values influence the use of information systems. Abstract:

Although the constituents of information systems (IS) success and their relationships have been well documented in the business value of information technology (IT) and strategic IS literature, our understanding of how information-sharing values affect the relationships among IS success dimensions is limited. In response, we conduct a quantitative study of 146 medium and large firms that have implemented a business intelligence system in their operations. Our results highlight that in the business intelligence systems context information-sharing values are not directly linked to IT-enabled information use, yet they act as significant moderators of information systems success dimensions relationships.

Mobile banking adoption

Wednesday, July 23, 2014

A study linking UTAUT, TTF and ITM in the context of mobile banking adoption, co-authored with T. Oliveira, M. Faria, and M. A. Thomas, is scheduled to appear in October 2014 issue of International Journal of Information Management. The work titled Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM shows – through an empirical research conducted in Portugal – how utilizing and blending UTAUT, TTF, and ITM helps us understand mobile banking adoption. Abstract:

Mobile banking (mBanking) enables customers to carry out their banking tasks via mobile devices. We advance the extant body of knowledge about mBanking adoption by proposing a model for understanding the importance and relationship between the user perception of mBanking, initial trust in mBanking services, and the fit between the technology and mBanking task characteristics. We synergistically combine the strengths of three IS theories – task technology fit (TTF) model, unified theory of acceptance and usage of technology (UTAUT), and initial trust model (ITM). The model was tested in a study conducted in Portugal, one of the European Union (EU) countries with the highest mobile phone adoption. Based on the sample of 194 individuals we applied partial least squares (PLS) to test the conceptual model propose. The path significance levels were estimated using the bootstrapping method (500 resamples). The study found that facilitating conditions and behavioral intentions directly influence mBanking adoption. Initial trust, performance expectancy, technology characteristics, and task technology fit have total effect on behavioral intention. The paper offers valuable insights to decision-makers involved in the implementation and deployment of mBanking services. For researchers, the paper highlights the usefulness of integrating TTF, UTAUT and ITM in the development of a decision support framework to study the adoption of new technologies.

End-user acceptance of biometrics

Tuesday, December 3, 2013

A new publication is available on the topic of pervasive technology acceptance, co-authored with C. Lancelot Miltgen, and T. Oliveira (2013): Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. The work significantly adds to our understanding of the determinants of end-user acceptance of biometric systems. Abstract:

The information systems (IS) literature has long emphasized the importance of user acceptance of computer-based IS. Evaluating the determinants of acceptance of information technology (IT) is vital to address the problem of underutilization and leverage the benefits of IT investments, especially for more radical technologies. This study examines individual acceptance of biometric identification techniques in a voluntary environment, measuring the intention to accept and further recommend the technology resulting from a carefully selected set of variables. Drawing on elements of technology acceptance model (TAM), diffusion of innovations (DOI) and unified theory of acceptance and use of technology (UTAUT) along with the trust-privacy research field, we propose an integrated approach that is both theoretically and empirically grounded. By testing some of the most relevant and well-tested elements from previous models along with new antecedents to biometric system adoption, this study produces results which are both sturdy and innovative.We first confirm the influence of renowned technology acceptance variables such as compatibility, perceived usefulness, facilitating conditions on biometrics systems acceptance and further recommendation. Second, prior factors such as concern for privacy, trust in the technology, and innovativeness also prove to have an influence. Third, unless innovativeness, the most important drivers to explain biometrics acceptance and recommendation are not from the traditional adoption models (TAM, DOI, and UTAUT) but from the trust and privacy literature (trust in technology and perceived risk).

A study linking perceived risk to IT adoption determinants, co-authored with C. Martins and T. Oliveira, is scheduled to appear in February 2014 issue of International Journal of Information Management. The work titled Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application shows – through an empirical investigation – how perceived risk interplays with well-recognized UTAUT model variables. Abstract:

While understanding the main determinants of Internet banking adoption is important for banks and users, our understanding of the role of users’ perceived risk in Internet banking adoption is limited. In response, we develop a conceptual model that combines unified theory of acceptance and use of technology (UTAUT) with perceived risk to explain behaviour intention and usage behaviour of Internet banking. To test the conceptual model we collected data from Portugal (249 valid cases). Our results support some relationships of UTAUT, such as performance expectancy, effort expectancy, and social influence, and also the role of risk as a stronger predictor of intention.

Linking BI and BPM

Friday, August 30, 2013

A study linking business intelligence (BI) and business process management (BPM), co-authored with V. Bosilj Vukšić and M. Pejić Bach, appeared in August 2013 issue of International Journal of Information Management. The work titled Supporting performance management with business process management and business intelligence: A case analysis of integration and orchestration shows – through an informative case study – how BI and BPM support process performance management. Abstract:

The case(s) demonstrates the importance of business process management (BPM) and business intelligence systems (BIS) in achieving better firm performance. It has been well documented in the literature that research on the effectively usage and combination of knowledge from BPM and BIS in turbulent service environments is limited. In response, we conduct an exploratory comparative case study of four firms in banking and telecommunication industries that have implemented BPM initiative and BIS solution. Our results firstly highlight that actual results of applying BPM and BIS differ greatly from the results that were originally planned. Secondly, we find that BIS initiatives are usually driven by improving marketing and sales, while BPM initiatives are driven by improving business processes. Thirdly, we identify that there is a lack of strong commitment to using both systems for supporting performance management.

BIS success

Thursday, December 20, 2012

There is a new publication available on the topic of business intelligence systems success, co-authored with R. Hackney, P. S. Coelho, and J. Jaklič (2012): Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. It is an important step in better understanding business intelligence systems success determinants and their interrelations. Here is the abstract:

The information systems (IS) literature has long emphasized the positive impact of information provided by business intelligence systems (BIS) on decision-making, particularly when organizations operate in highly competitive environments. Evaluating the effectiveness of BIS is vital to our understanding of the value and efficacy of management actions and investments. Yet, while IS success has been well-researched, our understanding of how BIS dimensions are interrelated and how they affect BIS use is limited. In response, we conduct a quantitative survey-based study to examine the relationships between maturity, information quality, analytical decision-making culture, and the use of information for decision-making as significant elements of the success of BIS. Statistical analysis of data collected from 181 medium and large organizations is combined with the use of descriptive statistics and structural equation modeling. Empirical results link BIS maturity to two segments of information quality, namely content and access quality. We therefore propose a model that contributes to understanding of the interrelationships between BIS success dimensions. Specifically, we find that BIS maturity has a stronger impact on information access quality. In addition, only information content quality is relevant for the use of information while the impact of the information access quality is non-significant. We find that an analytical decision-making culture necessarily improves the use of information but it may suppress the direct impact of the quality of the information content.

Information quality in transport operations

Wednesday, September 5, 2012

A study exploring changes in transport operations due to use of the quality information, co-authored with A. Habjan, was published in September 2012 issue of Industrial Management & Data Systems. The work titled Exploring the effects of information quality change in road transport operations sheds light – through an exploratory comparative case study of three transport firms – how information quality improvements stimulate organizational benefits in road transport operations. Abstract:

The information system (IS) literature has previously emphasized the positive contribution of IT-enabled quality information on decision making and firm performance, particularly when firms operate in highly competitive and uncertain settings. Yet, our understanding of how such information potentially transforms transport operations and generates improvements in organizational performance is limited. In response, the authors conduct an exploratory comparative case study of three transport firms that have introduced the global positioning system (GPS) in their operations. The purpose of this paper is to focus on assessing changes in transport operations due to the use of the quality information GPS provides and the link between these changes and organizational benefits. Data were collected through semi-structured interviews, direct observations and archival documentation in the three transport firms. Applying methods of a comparative case study, the data were analyzed by employing iterative and inductive analyses. The results identify transport operations as the missing element in a more comprehensive explanation of previously hypothesized relationships between information quality improvements and organizational benefits in road transportation. Notably, it was found that different information quality affects transport operations in various ways. In addition, improved transport operations, namely transport service planning, vehicle routing and transport control, result in improved customer service, enhanced transport asset utilization, reduced transport costs and time, and in increased satisfaction of employees working within the transport process. The paper offers a series of propositions that aims to stimulate empirical research and theoretical thinking on this topical subject. The findings offer valuable insights to transport firms, while providing and improving information quality for transport service planning, vehicle routing and transport control that results in organizational benefits linked to customer service, transport asset utilization, costs, and employee satisfaction. For information to have practical value, firms must use it in those transport operations identified as adding value to the firms’ performance.

A study exploring business intelligence maturity that transcends technical aspects of business intelligence, co-authored with T. Lukman, R. Hackney, J. Jaklič, and Z. Irani was published in Special Issue of Information Systems Management journal. The work titled Business Intelligence Maturity: The Economic Transitional Context Within Slovenia tries to elucidate directions for future business intelligence development in firms within transition economy environment. Abstract:

This article proposes a new maturity model with three related dimensions (technological, information quality, and business) and provide its empirical analysis within Slovenian organizations. With the use of K-means clustering, the naturally present maturity groups are identified. This article is an attempt to establish clear directions for further business intelligence development in transition economy settings. The findings hold important implications for commercial enterprise success.