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The purpose of this study is to contribute to the theory and practice of project management in the construction industry by identifying the primary causes and extracting the underlying causes of construction delays and providing recommendations on delay mitigation measures.

AA survey was used to identify the importance of 47 causes of delays. The relative importance index was used to rank them, factor analysis was applied to extract the underlying causes and focus group interviews were used for discussion and development of mitigation measures.

Six of the ten most important causes are in the top ten universal delays in construction projects. Factor analysis revealed six underlying causes: improper planning, poor consultant performance, inefficient site management, owner influence, bureaucracy and sub-standard contracts.

The owner/sponsor/client must have adequate engineering and project management skills to be able to evaluate proposals and contractors more accurately, economically and technically. The bidding and contract award process should focus on the most economically advantageous proposal and contracts should provide for mechanisms for managing risks while executing projects. Contractors should select reliable, high-quality subcontractors and suppliers and should have competent site managers.

This work expands and improves the understanding of the causes of delays in construction projects by providing an empirical study of the causes of delays and respective mitigation measures in Portugal.

This study aims to study the sensitivity of nonlisted real estate investment companies’ accounting earnings to house prices. This study evaluates whether house price changes determined these companies’ return on equity (ROE) or if other factors influenced the industry’s profitability beyond house price growth.

The authors collected a ten-year sample with the aggregate ROE of Portugal’s real estate investment companies, split by regions, and data on house prices and the per capita gross domestic product as a control variable. The authors ran a national-level time series with the canonical cointegrating regression estimator, which is robust to a small sample size; the authors also performed a regression on regional-level panel data with the common correlated effects mean group estimator, thus allowing slope coefficient heterogeneity and controlling for cross-sectional dependence. The authors also ran ordinary least squares regressions as a means of comparison.

This study found that an increase in the house price is not translated into an increase in the aggregate ROE. The results are robust with a reduced survivorship-biased sample, meaning that even the best-succeeded real estate investment companies do not have their accounting ROE dependent on house price growth.

The sample size is small and specific to one country. This paper did not study the housing market structure to verify whether it operates under monopolistic competition, which could further explain the attained results.

Policy decision-makers should know that there are no excess profits in the real estate investment companies’ industry because of house price growth that could be subject to windfall taxes.

To the best of the authors’ knowledge, the connections between house prices and real estate investment companies’ accounting earnings have never been studied.

In the macroeconomic environment of the Iberian Peninsula, this paper aims to understand which factors, intrinsic to management, affect the performance of wine companies.

The sample comprises 3,113 wine Iberian companies between 2011 and 2018. This study has used the panel data methodology, specifically the generalized method of moments system estimation method of Arellano and Bond (1991); Arellano and Bover (1995); and Blundell and Bond (1998) to test the hypotheses proposed.

Using return on assets (ROA) and sales growth as measures of corporate performance, this study’s results suggest that sales growth is the variable that has the most significant determining factors, both specific to the company and given the macroeconomic environment. Investors and civil society well understand the meaning of sales growth, namely, in a sector close to the final consumer. When using ROA as a dependent variable, the results suggest that because it is a pure management variable, the manager tends to be more concerned with maintaining adequate levels of economic profitability to ensure sustainability and future solvency, without giving prominence to the macroeconomic environment.

To the best of the authors’ knowledge, this is the first time that a study has been carried out in the Iberian Peninsula on the wine industry using ROA and sales growth as measures of corporate performance. This study shows that sales growth is a measure traditionally known to external stakeholders, and to that extent, its determining factors are the variables that these players most value in the market.

The purpose of this paper is to explore the applicability of the failure mode and effects analysis (FMEA) as an effective tool for decreasing failure risk in the early phase of the new product development (NPD), which adds to existing literature on the application of FMEA in NPD.

Through the application of action research (AR) methodology, it was possible to develop a case study examining the use of FMEA to decrease NPD risk in an early phase of NPD execution.

The importance and immediate gains of identifying NPD failures support FMEA's usefulness for NPD risk decrease. Moreover, its user-friendliness, timeliness and cost advantages facilitate the introduction of FMEA in the early phase of NPD execution.

FMEA is a well-known method used in manufacturing companies to identify and correct failures in products, processes and systems. This article explores the lack of practice-oriented evidence on the use of FMEA in the early phase of NPD execution and provides support to its applicability and effectiveness.

The uncertainty as to whether investments in riskier and less efficient markets allow managers to ‘beat the market’ remains a question to which answers are required. Accordingly, the purpose of this chapter is to offer new insights on portfolios of the US, European and Emerging Market (‘EM’) domiciled equity mutual funds whose objectives are the investment in emerging economies, and specifically analyses two main issues: alpha generation and the influence of the funds’ characteristics on their risk-adjusted performance.

The dataset is made up a survivorship-bias controlled sample of 137 equity funds over the period January 2004 to December 2014, which are then grouped into equally weighted portfolios according to the scheme’s origin. The Jensen’s (1968) Single-Factor model along with the Fama and French’s (1993) and Carhart’s (1997) multifactor models are employed to authenticate results and answer both research questions.

Research analysis reveals that EM exposed fund managers fail to collectively outperform the market. It thereby offers ground to believe that the emerging world is very close to being efficient, proving that the Efficient Market Hypothesis (‘EMH’) ideal exists in this scenario where market inefficiency might only be a perception of market participants as any apparent opportunity to achieve above-average returns is speedily snapped up by very active managers. Overall these managers take a conservative approach to portfolio construction, whereby they are more unperturbed investing in large cap equity funds so as to lessen somewhat the exposure towards risks associated with liquidity, stability and volatility.

Furthermore, the findings show that large-sized equity portfolios have the lead over the medium and small-sized competitors, whilst the high cost and mature collective investment vehicles enjoy an alpha which although is negative is superior to their peers. The riskiest funds generated the lowest alpha, and thereby produced doubts as to whether investors should accept a higher risk for the hope of earning higher returns, at least when aiming to gain an exposure into the emerging world.

Mutual fund performance is not an innovative topic so to speak. Nonetheless, researchers and academia have centred their efforts on appraising the behaviour of fund managers domiciled primarily in developed and more efficient economics, leaving the emerging region highly uncovered in this respect. This study, therefore aims at crafting meaningful contributions to the literature as well as to the practical perspective.

The purpose of this paper is to investigate the current level of reconfigurability implementation and its impact on manufacturing systems’ operational performance empirically.

This study is based on a questionnaire survey. Statistical analysis procedures were adopted to accomplish its objectives, namely, clustering methods based on cluster centroids. An ANOVA analysis was used to test for cluster differences among the variables.

The results show that the manufacturing companies surveyed can be divided into three clusters, with different levels of reconfigurability implemented. The implementation of the core characteristics of reconfigurability depends on the product’s complexity and demand variability, in terms of volume and product mix, as these have an impact on the operational performance, in terms of quality, delivery and flexibility.

The data for this survey were collected from manufacturing companies based in Portugal. Therefore, the replication of this questionnaire in other countries is recommended for future research to confirm its findings.

The questionnaire developed could be used by managers to assess the level of reconfigurability of their production systems and for internal/external benchmarking. The findings may help managers to decide which core characteristics should be implemented in their manufacturing systems.

The majority of the research addressing performance issues in reconfigurable manufacturing systems has been applied to case studies. This research reports an empirical investigation using a questionnaire-based methodology to provide generalisable empirical evidence.

This paper investigates the effect of the fit between supply and demand uncertainty (SDU) and supply chain responsiveness (SCR) (SC fit) on business and innovation performance in Brazilian companies.

The study presented an analysis carried out on an empirical study based on a sample of 150 manufacturing companies. Business and innovation performance of companies with different types of SC fit ( high–high and low–low fits) and misfit (positive and negative) are compared and discussed.

The results indicated that SC fit had a positive effect on both business and innovation performance. Further analyses suggested that companies with SC fit present similar business performance, independent of the level of SDU that characterizes the environment where they compete, while companies in environments with higher levels of uncertainty tend to present superior innovation performance. Companies with positive and negative misfit present similar performance.

An analysis of the literature showed that there is no consensus when it comes to the definitions and measurements of SC fit. The paper investigates the effects of SC fit on business and innovation performance, while previous empirical studies have mainly addressed its impact on financial performance. Moreover, this study compares the effects of two types of fit and two types of misfit and assesses SC fit in Brazilian manufacturing companies, analyzing the context of an under-researched reality.

The livestock sector contributes significantly to the Brazilian economy, but also creates many environmental and social issues. To mitigate these problems and help counteract the effects of the growing production demand, it is essential to address the prevention of food loss and waste (FLW). Therefore, the aim of the present study is to identify the causes of FLW, model their interrelationships and determine their root causes for the Brazilian beef supply chain (SC).

16 causes are analysed using an integrated interpretive structural modelling (ISM) and matrix impact of cross-multiplication applied to classification (MICMAC) methodology. ISM identified interrelationships among the causes and MICMAC determined the root causes of FLW.

The ISM highlights the “Lack of transportation infrastructures”, “Inadequate handling”, “Poor operational performance”, “Variety of products available in supermarkets” and “Unhealthy animals and outbreaks of disease” as the most influential causes and the MICMAC classifies them as the root causes of FLW in the Brazilian beef SC.

The results provide fundamental insights for researchers, practitioners and policymakers, by exploring which causes are more influential and which are the root causes, thereby assisting the SC members in the definition of suitable strategies to mitigate FLW.

This is the first empirical analysis of the interdependencies between the causes of FLW in the beef SC.

The objective of this study is to propose a sequence of implementation of the core characteristics of reconfigurability: modularity, integrability, diagnosability, adaptability and customization. For this purpose, the relationships among the core characteristics and Industry 4.0 technologies are analyzed as well as the impacts of one core characteristic on another.

This study presented tests and validated two hypothesized models based on the literature. This paper was based on a questionnaire survey. Portuguese manufacturing companies were the sampling frame. In total, 600 questionnaires were distributed and a total of 112 responses were eligible for statistical processing, representing a response rate of 18.7%. Structural equation modeling (SEM) was used to hypothesize the sequence of implementation of the core characteristics of reconfigurability.

The findings presented a roadmap to implement reconfigurability, which implies significant managerial contributions on how to make the transition from conventional to reconfigurable manufacturing systems (RMSs). This highlights the importance of the sequence of implementation of the core characteristics in order to make the most of each to achieve reconfigurability.

Implementing reconfigurability is crucial to manufacturing companies to respond to changes in production requirements and market fluctuations quickly. However, there is a gap between theory and practice in regard to achieve reconfigurability in existing manufacturing systems. This gap includes (1) understanding the type of relationships among the core characteristics of reconfigurability, (2) understanding the influence that one core characteristic has on another and (3) establishing a sequence of implementation for the core characteristics. This study makes a contribution to fill this gap in the research area.