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The purpose of this paper is to develop a quantitative comprehensive model for construction project success evaluation, from the viewpoint of a contractor company.

In this paper, the authors used a comprehensive definition of project success consisting of two components: Product success, which deals with the effect of the project's final product; and Project Management success, which focuses upon the project process. The research methodology includes five steps: identification of the critical performance indices for the two above mentioned components; quantification of the performance indices; normalization of the indices; integration of the various performance indices to develop an overall project performance function; and applying the model on a real project in Iran and analyzing the results.

This paper introduces a novel model to evaluate and measure the construction project success from the viewpoint of a contractor company. The results show that this model can be used as a reliable tool to measure the project performance of contractors and their points of strength and weakness can be determined precisely.

Analyzing the results of the case study shows that the evaluation model is absolutely applicable. All necessary elements to quantify the critical performance indices and overall project success can be recorded precisely and easily. Thus, this model can be used in every contractor company concerned about its projects’ performance.

The evaluation model proposed in this paper is a unique and comprehensive quantified model which considers difference between project success and project management success and all critical indices which can affect them.

Concerning the general patent trading mechanism, this paper proposes a systematic patent appraisal model to provide patent transferors and transferees a reasonable price suggestion of the target patent.

Based on the appraisal factors (including the patent transferor, patent transferee, patent features, and patent trading specifications) and regression model, a patent trading system is developed with an automatic patent appraisal function.

Based on the case study, it is found that the system performance is better if the non‐critical factors can be identified and dropped out from the appraisal model.

The proposed model and platform can enhance patent trading performance and, therefore, the enterprise R&D tasks can be accomplished more efficiently.

This study proposes quantitative models of patent appraisal factors and a multiple regression model for patent appraisal to present an automatic patent price determination mechanism.

Presents the methodology for designing, creating and maintaining a performance index of properties held in institutional portfolios. Illustrates the technique using the Russell Canadian Property Index (RCPI). Notes that it can be used for asset allocation and performance measurement purposes. Concludes that the introduction of real estate indices to institutional investors′ allocation and evaluation frameworks will assist in promoting and entrenching this asset class as a necessary component of any pension portfolio.

This paper aims to explore the effect of hiring outside chief executive officers (CEOs) on restaurant performance. As outside CEOs have a mandate to bring changes but lack internal knowledge, this study expected that outside CEOs impose a significant influence on restaurant performance. It was further expected that the relationship is substantially moderated by franchising and recession.

The CEO data was manually collected from firms’ annual filings and the EXECOMP database. The COMPUSTAT database was used for company financial data. A two-way panel regression was used to examine the proposed relationships.

The results revealed that outside CEOs have a positive effect on growth but a negative effect on restaurant profitability. It was further turned out that franchising significantly moderates the outside CEO-performance relationship. However, the moderating effect of recession turned out to be insignificant.

The results suggested that outside CEOs play a critical role in determining restaurant performance. The results further imply that franchising helps to maximize the positive effect of outside CEOs while mitigating the adverse effects of outside CEOs.

This study is one of the first to examine the effect of outside CEOs in the hospitality context. Moreover, this study extended the literature by revealing the relationship in the restaurant industry and highlighting the importance of long-term organizational context.

In an environment of intensive global mobility, this study aims to investigate the performance role of staffing choices within diverse MNE subsidiary strategies. Incorporating the integration-responsiveness (IR) framework with a contingency perspective, this study proposes that the performance success of distinct MNE subsidiary strategies depends on staffing choices. This study argues that performance differences of staffing choices such as assigned expatriates, self-initiated expatriates, former inpatriates and host-country nationals derive from their different knowledge/experience advantages regarding the intra-firm environment and local market conditions.

The study utilizes a unique sample of 169 foreign subsidiaries located in Greece that faced the outbreak of the COVID-19 pandemic (in 2020). For robustness reasons, this study also captures the imposition of capital controls (in June 2015).

This study finds important mediating performance effects of a diversified human resource portfolio across distinct subsidiary strategies in difficult times. Integration strategy tends to use more assigned expatriates, locally responsive strategy tends to utilize more host-country nationals, whereas multi-focal strategy favors self-initiated expatriates and former inpatriates, with positive subsidiary performance effects accordingly. So, staffing policies that are suitable to balance the needs of Human Resource Management (HRM) portfolio differ from strategy to strategy. Moreover, this study finds that managing HRM diversity is crucial in turbulent times.

While the empirical evidence has been predominantly accumulated from large economies, largely neglecting performance effects of MNE subsidiary staffing in crisis contexts, the analysis sheds light on a small open economy (i.e. the Greek context) emphasizing rapidly environmental deterioration. The findings extend existing theorizing on international performance and HRM management by providing an integrative conceptual framework linking integration-responsiveness motivated strategies with distinct groups of high-quality human resources under contingency considerations, so creatively synthesizing largely fragmented IB and HRM research streams. The study provides valuable insights into the performance role of non-conventional staffing choices such as self-initiated expatriates and former inpatriates, given that relevant studies examine either exclusively expatriates or compare expatriates with host country nationals, reaching inconclusive results.

This paper aims to examine the effect of R&D laboratories on the perceived performance of MNE subsidiaries during recession.

Employing resource-based view and knowledge-based theory, the authors investigate a unique sample of 171 technologically heterogenous foreign MNE subsidiaries located in Greece over the period of recession 2009–2016. The sample subsidiaries operate different types of R&D laboratories.

The authors find that MNE subsidiaries with advanced R&D laboratories such as locally integrated laboratories (LILs) and internationally interdependent laboratories (IILs) perform better in recession than subsidiaries with support laboratories (SLs) or subsidiaries without R&D laboratories. Overall, the authors find an asymmetric performance contribution of R&D laboratories at subsidiary level.

The study provides useful insights into the environmentally derived “knowledge-based - performance” context, so filling an important research gap, since little is known about the performance impact of the input-side of technological activity at MNE subsidiary level, especially as regards R&D facilities/infrastructure. Based on the findings the authors identify important managerial implications.

Across the globe, the dearth of certainty about the cost of sustainable buildings (SBs) remains a critical disincentive to their adoption. This study explored the factually incorrect knowledge about the cost of SBs and their implications on adoption.

The study adopted sequenced mixed qualitative and quantitative approaches involving a literature review, Delphi study and survey. Semi-structured and structured self-study questionnaires were administered to a random sample of green building experts, researchers and registered construction professionals with deep knowledge of SB. The dataset from 254 stakeholders was analysed for commonality, principal components and critical misperceptions using multivariate approaches.

The predominant misperceptions in the study linked low adoption of SB to cost premium, portray cost premium as a property of luxury sustainable features and suggest related practices are suitable for exemplary projects only. The critical misperceptions produced various misinterpretations that inhibit the adoption of SB through the dearth of policies, increased complexities and inflation of budget to curb perceived risks.

The study buttressed the imperative to improve cost information, knowledge, skills and stakeholders' risk perceptions to increase SB adoption. The results provide insight into the regional misperceptions and knowledge gaps that could explain the low adoption of SB in a typical emerging green market.

The study showed that the prevalent knowledge about the cost of SB among construction stakeholders are unsupported beliefs and directs attention to emerging issues critical to SBs' adoption in emerging markets.

This study aims to determine how changes in macroeconomic indicators and the housing prices index (HPI) are related. These factors can cause short-term and long-term changes in the housing market in Spain.

The study used cointegrating regression, fully modified ordinary least squares and dynamic ordinary least squares methodologies. The models are trained using quarterly time series data for these parameters from 2010 to 2022. A comprehensive examination is conducted to explore the relationship between macroeconomic issues and fluctuations in the HPI.

The results indicate statistically significant short-run effects (p < 0.05) of economic growth, inflation, Spanish stock indices, foreign trade and the interest rate on HPI. The inflation variables, Spain’s stock indices, interest rate and monetary rate, have statistically significant long-run effects (p < 0.05) on HPI. The exchange rate, unemployment and money supply have no substantial impact on HPI in Spain.

The study’s findings significantly contribute to increased information concerning the level of investing activity in the Spanish housing sector. After conducting an in-depth study of both the long-run and short-run connections with HPI, the study proved to be highly effective in formulating appropriate policies.

Search engines and web applications have evolved to be more tailored toward individual user’s needs, including the individual’s personal preferences and geographic location. By integrating the free Google Maps Application Program Interface with locally stored metadata, the author created an interactive map search for users to locate, and navigate to, destinations on the University of New Mexico (UNM) campus. The purpose of this paper is to identify the characteristics of UNM map search queries, the options and prioritization of the metadata augmentation, and the usefulness and possible improvement of the interface.

Queries, search date/time, and the number of results found were logged and examined. Queries’ search frequency and characteristics were analyzed and categorized.

From November 1, 2012 to September 15, 2013, the author had a total 14,097 visits to the SearchUNM Maps page (http://search.unm.edu/maps/). There were total 5,868 searches (41 percent of all the page visits), and out of all the search instances, 2,297 of them (39 percent) did not retrieve any results. By analyzing the failed queries, the author was able to develop a strategy to increase successful searches.

Many academic institutions have implemented interactive map searches for users to find locations and navigate on campus. However, to date there is no related research on how users conduct their searches in such a scope. Based on the query analysis, this paper identifies user’s search behavior and discusses the strategies of improving searches results of campus interactive maps.

The overall equipment effectiveness (OEE) is a powerful metric in production as well as one of the methods in evaluating function for measuring productivity in the production process. In the existing method, measuring OEE is based on three main elements consisting availability, performance and quality. The purpose of this paper is to evaluate the recognized metrics of production: OEE and overall line effectiveness (OLE) by using smart systems techniques.

In this paper, to improve the calculative methods and productivity with three methods: measuring OEE using Mamdani fuzzy inference systems (FIS), measuring OEE using Sugeno FIS, and measuring OLE using FIS and artificial neural networks (ANNs) are proposed.

The proposed methodologies aim to decrease some weaknesses of OEE and OLE methods by exploiting intelligent system techniques, such as FIS and ANNs. In particular, this research will solve the following issues that occur in manual and automatic data gathering. This technique is an effective way of measuring OEE and OLE with regard to different weights of losses as well as difference in the weight of the machines. In addition, it allows the operator’s knowledge to take a part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.

In relation to other methodologies, it allows the operator’s knowledge to take part in the measurement using uncertain input and output with implementation of linguistic terms. The presented method is the details and capabilities of those methods in various tested scenarios, and the results have been fully analyzed.