This research highlights a contextual application for big data within a HR case study setting. This is achieved through the development of a normative conceptual model that seeks to envelop employee behaviors and attitudes in the context of organizational change readiness. This empirical application considers a data sample from a large public sector organization and through applying Structural Equation Modelling (SEM) identifies salary, job promotion, organizational loyalty and organizational identity influences on employee job satisfaction (suggesting and mediating employee readiness for organizational change). However in considering this specific context, the authors highlight how, where and why such a normative approach to employee factors may be limited and thus, proposes through a framework which brings together big data principles, implementation approaches and management commitment requirements can be applied and harnessed more effectively in order to assess employee attitudes and behaviors as part of wider HR predictive analytics (HRPA) approaches. The researchers conclude with a discussion on these research elements and a set of practical, conceptual and management implications of the findings along with recommendations for future research in the area.

Information systems (IS) facilitate organisations to increase responsiveness and reduce the costs of their supply chain. This paper seeks to make a contribution through exploring and visualising knowledge mapping from the perspective of IS investment evaluation. The evaluation of IS is regarded as a challenging and complex process, which becomes even more difficult with the increased complexity of IS. The intricacy of IS evaluation, however, is due to numerous interrelated factors (e.g. costs, benefits and risks) that have human or organisational dimensions. With this in mind, there appears to be an increasing need to assess investment decision-making processes, to better understand the often far-reaching implications associated with technology adoption and interrelated knowledge components (KC). Through the identification and extrapolation of key learning issues from the literature and empirical findings, organisations can better improve their business processes and thereby their effectiveness and efficiency, while preventing others from making costly oversights that may not necessarily be only financial. In seeking to enlighten the often obscure evaluation of IS investments, this paper attempts to inductively emphasise the dissemination of knowledge and learning through the application of a fuzzy Expert System (ES) based knowledge mapping technique (i.e. Fuzzy Cognitive Map [FCM]). The rationale for exploring knowledge and IS investment evaluation is that a knowledge map will materialise for others to exploit during their specific technology evaluation. This is realised through conceptualising the explicit and tacit investment drivers. Among the several findings drawn from this research, the key resulting knowledge mapping through FCM demonstrated the complex, multifaceted and emergent behaviour of causal relationships within the knowledge area. The principal relationships and knowledge within IS investment evaluation are illustrated as being determined by a blend of managerial and user perspectives.

This article explores the relationship between sustainability strategies and future energy needs, supply chains need to reduce their CO2 emissions through developing their green credentials and improving performance. Knowledge management (KM) is an enabler to support collaboration efforts. The SCM and KM areas have largely focused on improving organisational performance. While the latter has yielded successful outcomes in different sectors, there is still a scarcity of research on identifying influential factors highlighting those aspects which may enable green supply chain collaboration (GrSCC), thus leading to sustainable energy futures and carbon-efficient production. This paper examines the role of KM in facilitating GrSCC. Through the identification of key factors extrapolated from the literature, a model for implementing GrSCC using a futures-based perspective is proposed. This paper inductively demonstrates the relationship between identified GrSCC factors through fuzzy cognitive mapping technique. Findings support a futures-based perspective that enhances understanding and refines forward-looking strategies for GrSCC.

Working collaboratively with internal and external partners (suppliers, customers and internal stakeholders) has been at the epicentre of product design. Knowledge sharing has been well recognised in this context. However, there is limited research that has addressed the role of social media/Web 2.0 in facilitating knowledge sharing for sense- and decision-making within product design. To address this gap, this study draws on the resource-based view (RBV) of the firm and two vignettes that relate to ‘collaborative co-design’ and ‘collaborative design-to-order’. We illustrate the role of social media/Web 2.0 in building knowledge sharing capabilities for sense- and decision-making for internal and external partners during product design. Limitations and further research into the use of social media/Web 2.0 are also discussed.

Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted substantial interest from both academics and practitioners. Big Data Analytics (BDA) is increasingly becoming a trending practice that many organizations are adopting with the purpose of constructing valuable information from BD. The analytics process, including the deployment and use of BDA tools, is seen by organizations as a tool to improve operational efficiency though it has strategic potential, drive new revenue streams and gain competitive advantages over business rivals. However, there are different types of analytic applications to consider. Therefore, prior to hasty use and buying costly BD tools, there is a need for organizations to first understand the BDA landscape.Given the significant nature of the BDand BDA, this paper presents a state-ofthe- art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/ employed by organizations to help others understand this landscape with the objective of making robust investment decisions. In doing so, systematically analysing and synthesizing the extant research published on BD and BDA area. More specifically, the authors seek to answer the following two principal questions: Q1 –What are the different types of BD challenges theorized/proposed/confronted by organizations? and Q2 – What are the different types of BDA methods theorized/proposed/employed to overcome BD challenges?. This systematic literature review (SLR) is carried out through observing and understanding the past trends and extant patterns/themes in the BDA research area, evaluating contributions, summarizing knowledge, thereby identifying limitations, implications and potential further research avenues to support the academic community in exploring research themes/patterns. Thus, to trace the implementation of BD strategies, a profiling method is employed to analyze articles (published in English-speaking peer-reviewed journals between 1996 and 2015) extracted from the Scopus database. The analysis presented in this paper has identified relevant BD research studies that have contributed both conceptually and empirically to the expansion and accrual of intellectual wealth to the BDA in technology and organizational resource management discipline.

Even after more than a decade of intensive research work in the area of electronic government (e-government) adoption and diffusion, no study has yet undertaken a theoretical evaluation of research related to ‘e-government satisfaction'. The purpose of this study is to undertake a comprehensive review of the literature related to e-government satisfaction and adoption with a particular focus on the most critical factors and their manifested variables that influence user satisfaction in e-government. Usable data relating to e-government research were collected from 147 papers identified from the Scopus database and by manually identifying relevant articles from journals dedicated to e-government research such as Electronic Government, an International Journal (EGIJ), International Journal of Electronic Government Research (IJEGR) and Transforming Government: People, Process, and Policy (TGPPP). A meta-analysis of existing e-government studies found that the majority of the construct relationships demonstrated a significant range of average summative correlation, and effect size, but the influence of perceived ease of use, effort expectancy on behavioural intention, behavioural intention on use behaviour, and perceived trust on risk were still found to be non-significant. A broader analysis of e-government satisfaction and adoption research seems to reflect that although a large number of theories and theoretical constructs were borrowed from reference disciplines such as Information Systems, e-commerce and public administration, their utilisation by e-government researchers appears to be largely random in approach.

Transportation infrastructure projects are prone to cost and schedule overruns. At the time of contract award, a construction contingency budget is often used to accommodate for unplanned events such as scope changes. Recent empirical research has shown that rework during construction as a result of design changes, errors and omission are the major contributors of overruns in projects. The statistical characteristics of rework, and cost and schedule overruns that are experienced from a project's contract award for 58 Australian transportation infrastructure projects are analysed. Theoretical probability distributions are fitted to the rework, cost and schedule overrun data. Goodness of fit tests are used in conjunction with probability-probability (P-P) plots to compare the sample distribution from the known theoretical distribution. A Generalised Logistic probability density function is found to describe the behaviour of cost-overruns and provides the best overall distribution fit. The best fitting distribution for schedule overruns and rework data were the Four Parameter Burr and a Johnson SB distribution, respectively. The distributions are used to calculate the probability of rework, cost and schedule overruns being experienced. A case illustration is presented and discussed to demonstrate how the derived probabilities may be utilised in practice.

This research seeks to measure citizen satisfaction with the electronic Prescription Prepayment Certificate (PPC) offered by National Health Service (NHS) in the United Kingdom (UK). The paper reports on the findings of a survey of over 500 users of the NHS PPC service. Satisfaction is measured using the four dimensions from the COBRA framework (Osman et al. (2011) [1]) which comprise the cost, opportunity, benefits and risk assessment constructs. This is the first study to measure citizen satisfaction with the electronic PPC in the UK across these constructs. The results show that most citizens using the PPC electronic service are satisfied with this service and that the service meets their essential needs. The paper also presents the results of qualitative feedback obtained from the participants that can be used to determine the areas that need further improvement in the current electronic PPC service and potential influence on user satisfaction.

Within the workplace, justice is influenced by the interpersonal relationships between colleagues and/or management among other things. The main reason for this research is to examine the correlation between organisational justice and the ethical behaviour of employees. Based on the literature, the conceptual model developed in this paper integrates distributive, procedural, interpersonal and informational justice in relation to ethical behaviour. By applying an adapted survey questionnaire, data were collected from teaching staff at public sector higher education institutions. Multiple regression analysis was applied to 360 samples and this showed that distributive and procedural justice have a more positive and significant impact than informational and interpersonal justice on the ethical behaviour of employees. This is an empirical study which may contribute to the literature on ethical behaviour, organisational development and employee development.

Consumer brand preference is an essential step towards understanding consumer choice behaviour, and has therefore always received great attention from marketers. However, the study of brand preference has been limited to traditional marketing focusing on functional attributes to maximise utility. But now the shift to experiential marketing broadens the role of the brand from a bundle of attributes to experiences. Technological advancements have helped to increase the similarities between brand attributes and product commoditisation. Consequently, consumers cannot shape their preferences among brands using rational attributes only. They seek out brands that create experiences; that intrigue them in a sensorial, emotional and creative way. This study seeks to develop a model that provides an understanding of how brand knowledge and brand experience determine brand preference and to investigate its impact on brand repurchase intention. Accordingly, exploratory focus group discussions are employed followed by a survey of mobile phone users in Egypt. The findings provide insights into the relative importance of consumer perceptions on different brand knowledge factors in shaping brand preferences. It also demonstrates the significance of consumers’ experiential responses towards brands in developing their brand preferences that in turn influence brand repurchase intention. The model therefore offers managers a new perspective for building strong brands able to gain consumer preferences.