Understanding informations systems outsourcing success and risks through the lens of cognitive biases

Because outsourcing of information systems (IS) is now widespread, it is generally assumed to be successful. It is also often assumed that outsourcing risks are easily managed. In this paper we adopt an “evidence based management” approach to first test these assumptions through a qualitative metaanalysis of academic studies into IS outsourcing outcomes. Our research reveals a shortage of reliable and valid evidence for outsourcing’s benefits, and for the level of risk involved. We then use data from a series of focus groups to explain the paradox of widespread adoption of a strategy with limited empirical support. These focus groups were interpreted through the lens of research on a
range of cognitive mechanisms and biases that are known to affect decision makers. We conclude that cognitive mechanisms that are likely to affect sourcing decisions include framing biases, cognitive dissonance, attribution error, and the “optimism”, “confirmation”, “disconfirmation” and “overconfidence” biases. Given the shortage of supporting evidence, and the potential for these biases to operate, we argue that researchers need to be more critical in their analysis of reports of the success and risks of IS outsourcing.

Decision-making models used by `graduate nurses` managing patients` medications

Background. Nurses in a graduate programme in Australia are those who are in the first year of clinical practice following completion of a 3-year undergraduate nursing degree. When working in an acute care setting, they need to make complex and ever-changing decisions about patients' medications in a clinical environment affected by multifaceted, contextual issues. It is important that comprehensive information about graduate nurses' decision-making processes and the contextual influences affecting these processes are obtained in order to prepare them to meet patients' needs.
Aim. The purpose of this paper is to report a study that sought to answer the following questions: What are the barriers that impede graduate nurses' clinical judgement in their medication management activities? How do contextual issues impact on graduate nurses' medication management activities? The decision-making models considered were: hypothetico-deductive reasoning, pattern recognition and intuition.
Methods. Twelve graduate nurses who were involved in direct patient care in medical and surgical wards of a metropolitan teaching hospital located in Melbourne, Australia participated in the study. Participant observations were conducted with the graduate nurses during a 2-hour period during the times when medications were being administered to patients. Graduate nurses were also interviewed to elicit further information about how they made decisions about patients' medications.
Results. The most common model used was hypothetico-deductive reasoning, followed by pattern recognition and then intuition. The study showed that graduate nurses had a good understanding of how physical assessment affected whether medications should be administered or not. When negotiating treatment options, graduate nurses readily consulted with more experienced nursing colleagues and doctors.
Study limitations. It is possible that graduate nurses demonstrated a raised awareness of managing patients' medications as a consequence of being observed.
Conclusions. The complexity of the clinical practice setting means that graduate nurses need to adapt rapidly to make sound and appropriate decisions about patient care.

If the Tasmanian Tiger were found, what should we do? An interdisciplinary guide to endangered species recovery

The Tasmanian tiger, or thylacine (Thylacinus cynocephalus), is a wolf-like carnivorous marsupial last reported in the 1930s in Tasmania, an island state of Australia. Although the species is likely extinct, sightings are reported annually. A fictional scenario is described in which a female thylacine with four pouched young is captured. This scenario is explored and an interdisciplinary approach to endangered species recovery is introduced. This approach is applicable to all endangered species recovery efforts and focuses on the principal dimensions of recovery: (1) orienting to the problem at hand and meeting it successfully; (2) understanding the recovery effort itself, its full context, and the required management (decision) process; (3) using a broad range of methods; and (4) integrating research results into a comprehensive recovery process (picture of the whole). By using this interdisciplinary approach, recovery can be systematically understood, best managed, and restoration prospects enhanced.

Quality as the criterion for delivered information systems effectiveness

One of the major challenges of MIS activities is the difficulty in measuring the effectiveness of delivered systems. The principal purpose of my research is to explore this field in order to develop an instrument by which to measure such effectiveness. Conceptualisation of Information System (IS) Effectiveness has been substantially framed by DeLone and McLean's (1992) Success; Model. But with the innovation in Information Technology (IT) over the past decade, and the constant pressure in IT to improve performance, there is merit in undertaking a fresh appraisal of the issue. This study built on the model of IS Success developed by DeLone and MeLean, but was broadened to include related research from the domains of IS, Management and Marketing. This analysis found that an effective IS function is built on three pillars: the systems implemented; the information held and delivered by these systems; and, the service provided in support of the IS function. A common foundation for these pillars is the concept of stakeholder needs. In seeking to appreciate the effectiveness: of delivered IS applications in relation to the job performance of stakeholders, this research developed an understanding of what quality means in an IT context I argue that quality is a more useful criterion for effectiveness than the more customary measures of use and user satisfaction. Respecification of the IS Success Model was then proposed. The second phase of the research was to test this model empirically through judgment panels, focus groups and interviews. Results consistently supported the structure and components of the respecified model. Quality was determined as a multi-dimensional construct, with the key dimensions for the quality of delivered IS differing from those used in the research from other disciplines. Empirical work indicated that end-user stakeholders derived their evaluations of quality by internally evaluating perceived performance of delivered IS in relation to their expectations for such performance. A short trial explored whether, when overt measurement of expectations was concurrent with the measurement of perceptions, a more revealing appraisal of delivered IS quality was provided than when perceptions alone were measured. Results revealed a difference between the two measures. Using the New IS Success Model as the foundation, and drawing upon the related theoretical and empirical research, an instrument was developed to measure the quality/effectiveness of delivered IS applications. Four trials of this instrument, QUALIT, are documented. Analysis of results from preliminary trials indicates promise in terms of business value: the instrument is simple to administer and has the capacity to pinpoint areas of weakness. The research related to the respecification of the New IS Success Model and the associated empirical studies, including the development of QTJALIT, have both contributed to the development of theory about IS Effectiveness. More precisely, my research has reviewed the components of an information system, the dimensions comprising these components and the indicators of each, and based upon these findings, formulated an instrument by which to measure the effectiveness of a delivered IS.

Neurofuzzy decision support system for efficient risk allocation in public-private partnership infrastructure projects

The performance of public-private partnership (PPP) infrastructure projects is largely contingent on whether the adopted risk allocation (RA) strategy is efficient. Theoretical frameworks drawing on the transaction cost economics and the resource-based view of organizational capability are able to explain the underlying mechanism but unable to accurately forecast efficient RA strategies. In this paper, a neurofuzzy decision support system (NFDSS) was developed to assist in the RA decision-making process in PPP projects. By combining fuzzy and neural network techniques, a synthesized fuzzy inference system was established and taken as the core component of the NFDSS. Evaluation results show that the NFDSS can forecast efficient RA strategies for PPP infrastructure projects at a highly accurate and effective level. A real PPP infrastructure project is used to demonstrate the NFDSS and its practical significance.

PROJAM : the management of complex projects and programs

Challenges the existing normal science in project management with its limitations of high certainty in scope definition and develops a contingency based model for project / program management (PROJAM). The PROJAM concept is theoretically supported through the identification of eight inter related aspects - uncertainty, maturity, stakeholders, pareto, reward, transparency, partnering, and program management. The ideas presented represent a radical change to the eisting project management body of knowledge and expand the scope of project management to deal with complex projects / programs including organisational change, core function outsourcing (asset management) and IT hardware and software outsourcing.

An overview of previous studies in stakeholder management and its implications for construction industry

Purpose – The purpose of this paper is to provide an overview of previous studies in the field of stakeholder management, and propose implications for the construction industry.

Design/methodology/approach – Three major databases are searched: ABI, EI CompendexWeb, and ISI web of knowledge. Papers are searched on topic by using the keywords of “stakeholder management”, “management of stakeholders” and “management of stakeholder”. A brief review of the abstracts and conclusions of these papers is conducted to filter out the irrelevant and/or duplicate papers. After filtering, 159 articles with content relevant to stakeholder management are selected for analysis.

Findings – An overview of previous studies reveals that research interest in stakeholder management has turned to the descriptive approach. Through a critical review of stakeholder management process, three main problems of previous studies are identified: very few methods and tools are available to identify all stakeholders and their interests; limited studies involve the change management about the stakeholders' influence and relationship; and few studies are capable of reflecting the influence of the entire relationship network in practice.

Research limitations/implications – Two implications for the construction industry are suggested: establish a practical framework for managing stakeholders; and apply social network theory (SNT) in developing a stakeholder relationship model.

Originality/value – The overview and implications lead to new knowledge and an improved understanding of the management of multiple stakeholders in construction projects. The perspective of SNT avoids the deficiency of Freeman's dyadic ties model, and the project managers can make decisions in response to the stakeholder behaviours according to the entire relationship.

Major quantitative techniques for risk analysis in the construction industry : a comparative analysis

Risk analysis is one of the critical functions of the risk management process. It relies on a detailed understanding of risks and their possible implications. Construction projects, because of their large and complex nature, are plagued by a variety of risks which must be considered and responded to in order to ensure project success. This study conducts an extensive comparative analysis of major quantitative risk analysis techniques in the construction industry. The techniques discussed and comparatively analyzed in this report include: Programme Evaluation and Review Technique (PERT), Judgmental Risk Analysis Process (JRAP), Estimating Using Risk Analysis (ERA), Monte Carlo Simulation technique, Computer Aided Simulation for Project Appraisal and Review (CASPAR), Failure Modes and Effects Analysis technique (FMEA) and Advanced Programmatic Risk Analysis and Management model (APRAM). The findings highlight the fact that each risk analysis technique addresses risks in any or all of the following areas – schedule risks, budget risks or technical risks. Through comparative analysis, it has been revealed that a majority of risk analysis techniques focus on schedule or budget risks. Very little has been documented in terms of technical risk analysis techniques. In an era where clients are demanding and expecting higher quality projects and finishes, project managers must endeavor to invest time and resources to ensure that the few existing technical risk analysis techniques are developed and further refined, and that new technical risk analysis techniques are developed to suit the current construction industries requirements.

Global positioning systems in the AFL : worthwhile or waste of time?

Global Positioning Systems (GPS) in the Australian Football League (AFL) are the big-ticket item that sees clubs trying to gain any competitive advantage over their opposition that they can. This paper explores whether the current application of GPS by clubs is worthwhile or a waste of time from three core perspectives: technical, organisational and personal. Issues include poor data storage and analysis, inaccurate units, lack of appropriate business processes in place, and resistance to use. Although many of these issues can be addressed through improved technology, resolving the organisational and personal issues will require a change in mindset to ensure the use of GPS in the AFL is a worthwhile endeavour. The paper concludes that the current use of GPS devices in the AFL is a waste of time.

Stakeholder participation in estuary management: the development of Victoria's Estuary Entrance Management Support System

Stakeholder involvement in the management of estuaries is a necessary element of good environmental governance. In Victoria, Australia, a key challenge for estuary managers is whether or not estuaries should be artificially opened since many river mouths close ‘naturally’ from time to time. Estuary closure resulting in raised estuarine water levels leads to economic and social impacts on local communities. In the past these effects have been addressed by artificial river mouth openings, often without reference to associated environmental impacts. This article discusses the development and features of an Estuary Entrance Management Support System and considers its performance against principles of effective environmental management. It concludes that, in bringing together technical information with stakeholder input through a structured process, such a system makes a useful contribution to improving estuary entrance management.

New frontiers in biologging science

The term ‘biologging’ refers to the use of miniaturized animal-attached tags for logging and/or relaying of data about an animal's movements, behaviour, physiology and/or environment. Biologging technology substantially extends our abilities to observe, and take measurements from, free-ranging, undisturbed subjects, providing much scope for advancing both basic and applied biological research. Here, we review highlights from the third international conference on biologging science, which was held in California, USA, from 1 to 5 September 2008. Over the last few years, considerable progress has been made with a range of recording technologies as well as with the management, visualization, integration and analysis of increasingly large and complex biologging datasets. Researchers use these techniques to study animal biology with an unprecedented level of detail and across the full range of ecological scales—from the split-second decision making of individuals to the long-term dynamics of populations, and even entire communities. We conclude our report by suggesting some directions for future research.

Categorization of disaster decision support needs for the development of an integrated model for DMDSS

The wide variety of disasters and the large number of activities involved have resulted in the demand for separate Decision Support System (DSS) models to manage different requirements. The modular approach to model management is to provide a framework in which to focus multidisciplinary research and model integration. A broader view of our approach is to provide the flexibility to organize and adapt a tailored DSS model (or existing modular subroutines) according to the dynamic needs of a disaster. For this purpose, the existing modular subroutines of DSS models are selected and integrated to produce a dynamic integrated model focussed on a given disaster scenario. In order to facilitate the effective integration of these subroutines, it is necessary to select the appropriate modular subroutine beforehand. Therefore, subroutine selection is an important preliminary step towards model integration in developing Disaster Management Decision Support Systems (DMDSS). The ability to identify a modular subroutine for a problem is an important feature before performing model integration. Generally, decision support needs are combined, and encapsulate different requirements of decision-making in the disaster management area. Categorization of decision support needs can provide the basis for such model selection to facilitate effective and efficient decision-making in disaster management. Therefore, our focus in this paper is on developing a methodology to help identify subroutines from existing DSS models developed for disaster management on the basis of needs categorization. The problem of the formulation and execution of such modular subroutines are not addressed here. Since the focus is on the selection of the modular subroutines from the existing DMDSS models on basis of a proposed needs classification scheme.

The succession decision in Chinese–Australian family businesses : an exploratory study

This article explores the factors used to make succession choices as ethnic Chinese family business founders integrate into their host country, Australia. An empirical study of six Chinese–Australian family businesses was used to analyse what factors influence the succession decision-making process. Results show three broad factors influenced the founders’ decisions, including the aspirations and visions of the business founders, cultural and individual values shaped in the integration process, and the options that are available for succession. Findings challenge the anticipated option of intergenerational succession, with its emphasis on family-oriented collectivistic values as expectations. It provides future support for considering how the cultural value orientation (collectivistic, individualistic, or transitional) has impacted on the founder’s succession choices. Further research is required to understand how the flexible, changing, situational founder’s succession intentions are manifested among family businesses in cultural transition.

Comprehensive analysis of big data variety landscape

Big data presents a remarkable opportunity for organisations to obtain critical intelligence to drive decisions and obtain insights as never before. However, big data generates high network traffic. Moreover, the continuous growth in the variety of network traffic due to big data variety has rendered the network to be one of the key big data challenges. In this article, we present a comprehensive analysis of big data variety and its adverse effects on the network performance. We present taxonomy of big data variety and discuss various dimensions of the big data variety features. We also discuss how the features influence the interconnection network requirements. Finally, we discuss some of the challenges each big data variety dimension presents and possible approach to address them.