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Budget constraints faced by social housing projects (SHPs) developers can lead to poor value delivery to the end-users. Without a structured method to guide the decision-making processes during product development, SHP often fails to meet user needs and aspirations. Function analysis (FA) is an essential step in a value management (VM) study. Still, FA practice in SHP has been treated with secondary importance. This paper aims to propose a method for improving FA practice in the VM process for a Brazilian SHP to achieve optimum benefits.

The research followed Design Science Research (DSR) in a specific single case study context, focusing on solving practical problems while contributing to theory. The method has 11 steps and guides a complete VM exercise. Its development was based on prior VM research. Focus group meetings were held to get feedback about the initial method's version to increase its relevancy and applicability in the studied context.

The proposed method suggests that scarce financial resources in SHP do not necessarily lead to low-value delivery and low-design quality. When FA is fully implemented, opportunities for cost reallocations to enhance value are identified.

VM prior research in construction has not provided a specific method for improving FA practice for social housing developers to enhance value in the context of scarce financial resources.

Challenges in social housing projects (SHP) in Brazil are mainly related to design and construction quality and cost constraints. Value delivery to end-users must be a goal, however, jointly considered with the restrictions of such developments. In the SHP context, tight cost constraints frequently have a negative impact on delivering value to end-users. The purpose of this paper is to put forward the proposition that value enhancement can be achieved by reallocating costs to better meet the attributes most valued by end-users, without increasing initial project costs.

A set of tools used in value methodology (VM) is adopted to assist a systematic process with the goal of attaining an optimal functional balance between costs and value delivery to end-users. Desired values were indicated by users in a previous study, resulting in an Index of General Significance. A single case study was carried out to test the approach in a SHP. Opportunities for improvement guided by the desired values of end-users were evaluated.

The VM approach suggests that initial project cost constraints do not necessarily induce value loss for end-users, a recurrent problem that designers and stakeholders frequently face in such contexts. Improvements were made possible through simple cost reallocation.

A single case study was carried out to validate this approach. To create a generalized approach for other similar context further tests should be undertaken.

The proposed VM approach was shown to be efficient in assessing decisions which designers and stakeholders must take, bearing in mind cost constraints and improvements in value delivery to end-users.

Currently in Brazil, end-users’ perceptions are rarely considered into the design process of SHP. The research shows that the proposed approach could be used in similar contexts of social housing to enrich the design process and attain higher satisfaction levels.

An important lesson learned was that subjective parameters based on the desired values of end-users could be combined with technical and functional analysis, thus an objective improvement process was devised. The approach can have clear implications for the product development of SHPs to best match the end-user's value propositions, without neglecting financial and economic needs in such a context.

The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.

This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.

At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.

The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.

Since Hayek’s pioneering work in the 1930s, the Austrian business cycle theory (ABCT) has been presented as a disequilibrium theory populated by less-than-perfectly rational agents. In contrast, we maintain that (1) the Austrian business cycle theory is consistent with rational expectations and (2) the post-boom adjustment process can be understood in an equilibrium framework. Hence, we offer a new interpretation of the existing theory. In doing so, we also address concerns raised with Garrison’s (2001) diagrammatic approach, wherein the economy moves beyond the production possibilities frontier. Our interpretation might accurately be described as a monetary disequilibrium approach grounded in an implicit general equilibrium framework with positive costs of reallocation.

Over the past few years, mathematical and computational models of organizations have attracted a great deal of interest in various fields of scientific research (see Lin & Carley, 1993 for review). The mathematical models have focused on the problem of quantifying the structural (mis)match between organizations and their tasks. The notion of structural congruence has been generalized from the problem of optimizing distributed decision-making in structured decision networks (Pete, Pattipati, Levchuk, & Kleinman, 1998) to the multi-objective optimization problem of designing optimal organizational structures to complete a mission, while minimizing a set of criteria (Levchuk, Pattipati, Curry, & Shakeri, 1996, 1997, 1998). As computational models of decision-making in organizations began to emerge (see Carley & Svoboda, 1996; Carley, 1998; Vincke, 1992), the study of social networks (SSN) continued to focus on examining a network structure and its impact on individual, group, and organizational behavior (Wellman & Berkowitz, 1988). Most models, developed under the SSN, combined formal and informal structures when representing organizations as architectures (e.g., see Levitt et al., 1994; Carley & Svoboda, 1996). In addition, a large number of measures of structure and of the individual positions within the structure have been developed (Roberts, 1979; Scott, 1981; Wasserman & Faust, 1994; Wellman, 1991).

Summarizes a study that was carried out on behalf of a government department in Hong Kong, which provides service to public facilities. The department’s overall performance and the performance of its key divisions were examined as part of an investigation to determine whether they were in a position to compete with the private sector when the government ended the department’s monopoly in this particular sector. The department’s performance profile for a period of 16 months was constructed and the performances of two key divisions were compared. All performance measurements were made using a recent method called operational competitiveness rating (OCRA) analysis.

Work crew productivity and the application of limited resources are necessary elements in construction duration delay analysis. This study thus proposes a method to analyze construction delays and resource reallocation based on work crew productivity and resource constraints. The study also presents an economic feasibility analysis that maximizes economic effect by reducing construction duration, the cost of resource reallocation, delay liquidated damages (DLDs) and incentives for reducing contractual duration.

The proposed method involved three steps. First, work crew characteristics such as productivity, unit price and workload helped analyze delay information, including delay duration, reducible duration and daily reduced cost. Next, a goal programming method assessed resource reallocation based on the priority (as determined by decision-makers) of each constraint condition, such as the available number of workers, cost, goal workload and statutory working hours. Lastly, the level of reallocation was analyzed based on the results of the economic feasibility analysis and decision-makers’ delay attitudes.

A case study was performed to test the proposed method's applicability. Its involved sensitivity analysis indicated proposing to decision-makers a scenario based on the prioritization of economic feasibility. The proposed method's applicability proved high for decision-makers, as they can determine whether to reduce construction duration per the proposed data.

The proposed method's main contribution is the reallocation of resources to reduce construction duration based on work crew productivity and the prioritization of limited resources. The proposed method can analyze the differences in productivity between the plan and actual progress, as well as calculate the necessary number of workers. Decision-makers can then reduce the appropriate level of contractual duration based on their own delay attitude, constraint condition prioritization and results from daily economic feasibility analyses.

This paper seeks to provide a framework for understanding the role and contributions of virtual trade fairs in developing relationships. Using a relationship communication model, the paper aims to explore the determinants of value creation through virtual trade fairs, emphasising the impact of advanced information and communication technologies on contemporary marketing.

The paper is a conceptual work which derives research propositions from an extended literature review.

The paper provides a rationale for factors that determine value creation through virtual trade fairs. The exhibitor firm's understanding of the importance of information, network orientation, capability of customer integration, and relationship attributes are proposed as influences on the effectiveness of virtual trade fairs.

The research has limitations that are due to the exploratory nature of the work. The paper suggests opportunities for further research, particularly approaches to developing measures of effectiveness for virtual trade fairs and for developing integration and interdependencies with other communication instruments.

Referring to existing arguments about the pros and cons of virtual trade fairs, the paper provides a deeper understanding of the content and effectiveness of virtual trade fairs.

The paper sheds light on a phenomenon that, despite its increasing acceptance among practitioners, remains unexplored by marketing research. By providing a better understanding of virtual trade fairs, the paper enriches research on trade fair issues.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.