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Married couples receive tax benefits such as favorable tax rates, higher exclusions, higher phase-outs, and combined deductions. However, joint and several tax liability is a major issue facing these taxpayers. The term innocent spouse relief, within the Internal Revenue Code, is a direct result of one spouse failing to satisfy the joint liability for the married couple. Since both individuals are jointly and severally liable for the combined liability, the innocent spouse may be responsible for the liability in whole or in part. Our study examines this highly litigated arena of innocent spouse relief. To assist in this area of taxation, the Internal Revenue Service has provided taxpayers and tax practitioners with guidance. Revenue Procedure 2003-61 (2003-2 CB 296) outlines factors useful in determining whether innocent spouse relief should be granted. Additionally, this study creates a predictive model containing only three significant factors (economic hardship, knowledge/reason, significant benefit) capable of predicting with approximately 89% accuracy. These same three variables are significant after running multiple regression with p-values of 0.002 (economic hardship), 0.000 (knowledge/reason to know), and 0.001 (significant benefit). These factors provide valuable insight to practitioners when advising clients on challenging or accepting the Internal Revenue Service's decision. Additionally, abuse is marginally significant in the regression model. Also, judge gender and political affiliation are analyzed. However, the gender of the judge and political affiliation fail to be statistically significant using the chi-square test and regression model.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

This experimental study investigates the connotative (measured) meaning of the concept “auditor independence” within three audit engagement case contexts, including two acknowledged in the literature to represent significant potential threats to independence. The study’s research design utilises the measurement of meaning (semantic differential) framework originally proposed by Osgood et al. (1957). Findings indicate that research participants considered the concept of independence within a two factor cognitive structure comprising “emphasis” and “variability” dimensions. Participants’ connotations of independence varied along both these dimensions in response to the alternative experimental case scenarios. In addition, participants’ perceptions of the auditor’s independence in the three cases were systematically associated with the identified connotative meaning dimensions.

The interest in corporate social responsibility (CSR) has become burgeoning in the construction industry as firms are under constant pressure from socially conscious stakeholders to demonstrate their efforts to address various CSR issues. This study aims to unveil the key practices and impact factors (KPIFs) of CSR implementation in construction firms and the interrelationships among different key impact factors toward attaining CSR practices.

Mobilizing the integrated institutional, stakeholder and self-determination theories, a theoretical framework was first developed to elaborate the potential inter-relationships among the key impact factors toward CSR implementation. Data were collected from extra-grade contractors through an online questionnaire survey and was then analyzed by the partial least square structural equation modeling method.

The results show that construction firms' CSR practices could be classified into eight distinct key dimensions, e.g. shareholders' interests, government commitment and environment preservation. It is found that three groups of key impact factors – external institutional factors (especially coercive-normative factors), intrinsic factors (especially strategic business direction and organizational culture) and identified factors (i.e. the perceived importance of CSR practices) – have statistically significant positive impacts on most key dimensions of CSR practices.

The research findings have implications for top management to better understand CSR implementation, thereby helping them secure legitimacy to survive and advance in the competitive construction businesses.

The findings contribute to the theoretical body of knowledge in CSR by modeling and empirically demonstrating the influence mechanism of CSR implementation in construction within an integrated model.

The decision to bid or not to bid for new projects determines contractors’ propensity for business success or failure. The purpose of this paper is to investigate the factors that affect the decision of indigenous construction contractors to bid or not to bid in Nigeria.

Analysis was conducted on data from questionnaires received from 64 engineering management employees of leading construction companies which are members of Nigeria’s Federation of Construction Industry. The study identified 41 significant decision factors often considered by Nigerian indigenous contractors before the bid. Mean item scores were obtained for each of the factors. Principal component analysis was used to point out the most significant decision factors.

Results revealed significant orthogonal relationships between the factors. Only 11 of the 41 factors are statistically significant to influence contractors’ decision to bid or not to bid. Most of the significant items were amongst the least rated items by the participants. The post hoc decision factors include consultant’s interpretation of project specifications, previous relationship between the intending bidder and client, availability of other projects at the time of bidding, technological complexity of the project under consideration and prequalification requirements. Others include the propensity for resource price fluctuation, business capacity of partners, amount of own work vs subcontracted work, required rate of return on investment and difficulty in obtaining finance.

The practical implication of these findings are as follows: the orthogonal relationship between the decision factors implies non-linear relationship between the factors and actual decision to bid or not to bid, and that bid success is often not predictable by bid behaviour; many of the bid decision factors rated highest by indigenous contractors seldom impact the contractors’ actual bid decisions; local and international players can adopt the significant decision factors elicited in this study for managing their structures for inter-organizational partnerships.

This article initially aims to explore the factors of every quality construct of the 5Qs model of service quality and, second, identify the significant factors affecting the total quality of e-healthcare services and its association with consumer satisfaction using a multidimensional hierarchical 5Qs model of e-healthcare service quality.

Questionnaire-oriented research was performed at three public hospitals of Punjab and Chandigarh. In total, 53 variables were covered in all quality constructs for data collection from the designated public hospitals. The respondents who agreed to have knowledge regarding e-Healthcare services and were availing these services were included in the study. The analysis comprised structural equation modeling technique using AMOS 21.

The outcomes suggest that the 5Qs model is more comprehensive and can be used to evaluate service quality perceptions using e-Healthcare services. The research identified 11 sub-dimensions for the five quality constructs of the 5Qs model, representing total quality, which is primary to consumer satisfaction. “Overall objectivity” and “technical objectivity” defined the quality of object. The quality of process of e-Healthcare services was characterized by “functionality,” “timeliness” and “responsiveness.” Quality of infrastructure was defined by “technical infrastructure,” “physical infrastructure,” “manpower skills” and “organizational infrastructure.” “Manner of interaction” and “timely interaction” defined the quality of interaction. The atmosphere was represented by only one factor. The results also suggest that quality of infrastructure, quality of interaction and quality of atmosphere play the most significant role in total quality leading to consumer satisfaction.

Theoretical implications: The multidimensional hierarchical model will help the researchers study the e-Healthcare service quality in a more organized manner, and the outcomes of this study can be linked with that of future studies for more generalized application in other public hospitals. The sub-dimensions of each quality construct of the 5Qs model can be applied in private hospitals, and the hierarchical model can be tested in different industries to measure service quality perceptions of the consumer

The outcomes of the study can be applied in various public sector hospitals to redesign the e-Healthcare services based on consumers' perception for better consumer satisfaction and quality services. This paper identifies the role of each quality construct in e-Healthcare services for improvement in the total quality, which in turn will lead to higher satisfaction for the consumers.

In this study, the original 5Qs model has been used for the first time in a new instrument to understand better and design quality e-Healthcare services. The paper explores the sub-factors of each quality construct and its significance in measuring the total quality.

The purpose of this study is to analyze and compare the impact of project-factors and organization-factors on five indicators of project performance for small and medium enterprise (SME) and large construction contracting firms that are fully responsible for the successful completion of the projects. The five performance indicators are time, cost, safety, quality and financial.

A questionnaire survey was conducted to solicit responses from project managers/directors from 342 construction firms in Malaysia. The construction firms included in this study came from various sectors: civil, building and infrastructure; oil and gas; marine and multidiscipline. Hierarchical multiple-regression was used to analyze the data.

The salient findings are as follows: (1) impacts of project-factors and organization-factors on performance indicators are different for SMEs and large construction firms and (2) relative impact of organization-factors on performance is much higher than the project-factors.

Analyzing the relative impact of project- and organization-factors on the performance of SMEs and large construction firms can significantly enhance the body of knowledge about performance levels and boost best practices in this respect related to construction industry.

The purpose of this paper is to discover factors of new ventures performance in Russia and to combine them in a model which describes the influence of these factors on the performance of a new venture.

A cross‐sectional study of new ventures was conducted by a field survey in six regions in Russia. One‐factor variance analysis and regression analysis were used to identify significant factors.

Three groups of factors were identified as significantly influencing performance of new ventures in Russia: environmental factors, style of management and type of strategic behaviour. For environmental factors the following variables were included: crisis in industry, increase in product demand, predictability of regulatory authorities behaviour, predictability of financial markets, and environmental hostility. For company management style, several variables were statistically significant: level of centralization, concentration of management in the hands of the founder, and role of the middle management. For strategic behaviour, only the strategy of prospector in terms of Miles and Snow was found to have significant influence on the new venture performance (NVP).

The research ignores industry specifics that may be reflected in different new ventures performance factors.

Entrepreneurs starting new ventures in Russia should take into account the identified factors which can influence their companies’ performance.

Although there have been many studies on NVP factors, no such research has been performed in Russia.

Guaranteed maximum price (GMP) contracts are becoming an increasingly popular contract solution; however, many projects experience higher levels of risk and exceed predetermined GMPs, failing to accomplish the main motive behind the concept. Thus, the study identified a risk management process for GMP projects.

The study adopted a quantitative approach consisting of three Delphi rounds. The collected data were analysed using statistical data analysis tools.

The study identified 17 highly significant risk factors in GMP projects and determined their levels of severity. Subsequently, risk allocation amongst the client, contractor and consultant and strategies to handle the most significant risk factors were determined. The study identified poorly defined scope and design changes as the most critical risks in GMP projects. Moreover, strategies such as clearly defining the project scope, preparing precise documentation, early involvement of the contractor and using a partnering approach can be deployed to reduce the risk in GMP projects. Each risk has to be assigned to the party who can best manage it, depending on its nature.

The study addresses the literature gap pertaining to risk management of GMP contracts by identifying its overall process, including the identification of significant risks based on the severity levels; risk allocation amongst the client, contractor and consultant; and identification of risk handling techniques suitable for each significant risk factor. The study contributes to the industry by identifying a systematic risk management process to implement GMP projects successfully within the stipulated time, cost and quality.