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The purpose of this paper is to assess the determinants of the early termination of infrastructure projects implemented under public–private partnerships (PPP), concessions or privately managed divested assets.

Cross-section and duration model estimations were applied to a sample of 2,655 infrastructure projects implemented in Latin America and the Caribbean for the period 1993–2017. Estimation techniques consist of a logistic model and cox proportional hazards model (CPHM) applied to alternative specifications, including diverse causal factors.

Evidence is found that early termination of infrastructure projects is determined by intrinsic and extrinsic factors. Among the intrinsic factors, the main characteristics of projects that increase the likelihood of failure are the size or scale of the project, the sector in which the project is developed (transport and water and sanitation) and being investments in divested assets. Extrinsic factors that showed a negative impact on the risk of early termination are good regulatory quality and domestic macroeconomic stability. Likewise, external real and financial shocks also contribute importantly to explain the likelihood of early termination of infrastructure projects.

The results reveal that particular care must be put in design and supervision of large-scale projects, either in transport or water and sanitation. As well, risks associated with external shocks must be explicitly acknowledged in project design, with appropriate remedies and safeguards. The prevalence of relatively high rates of early termination in projects in divested assets in contrast with PPP suggests the importance of introducing simpler way out mechanisms for concessionaires. Finally, the results show the key importance of institutional factors like regulatory quality in determining project failure on economic performance of infrastructure projects.

In contrast to the previous literature, the analysis shows the decisive role played by financial external factors and institutional factors of Latin American and Caribbean countries in early termination of private participation in infrastructure projects. As well, the finding of a higher likelihood of failure in projects that involve investments in divested assets versus concession or PPP suggests the need of investigate further the tradeoffs regarding the balance that must exist among guarantees offered to investors in infrastructure projects and the need to keep contractual decisions in line with market signals.

A decision to terminate a project can demoralize project managers and team members, and increase concerns about job security. For these reasons, managers tend to delay project termination decisions. However, such delays can put a damper on the normal operation of a company. Therefore, corporations have been seeking to develop a number of methods and techniques to assist with decision making in project evaluation. Benchmarking has gained increasing acceptance as a technique that enhances business processes. This paper is concerned with the development of a model using the analytic hierarchy process (AHP) for the evaluation of project termination or continuation, which is based on the benchmarking method. The benchmarking of project evaluation, the operation of AHP, is presented along with a case study. A R&D case study in Taiwan is used to illustrate the approach, the framework of which was entered on an Excel spreadsheet. This approach has provided the decision maker with an alternative for evaluating the status of a project and making the right call.

This paper is an event time study of the valuation effects of a sample of eighty‐two permanent plant closings. The traditional approach to project termination decisions suggests that common stock prices should increase around the date on which firms publicly announce the termination of a project. However, the empirical results of this study indicate that, on average, no significant changes in share holder wealth are associated with the closing down of capital assets.

A common finding of many surveys of corporate financial management practice is that the actual usage of normative financial models is infrequent. This is mainly due to the complexity of the decision environment, the use of information processing heuristics by decision makers, and the presence of psychological factors that influence the decision maker's behaviour. This paper reviews certain psychological concepts and their effects on the validity of traditional fundamental analysis in finance. Second, it discusses how cognitive limitations of human information processing may interfere with the implementation of certain decision rules in financial management, especially when decision makers experience information overload. Third, it provides a review of the advances that have been suggested to overcome the cognitive limitations of human information processing and to evaluate whether such advances can circumvent the psychological biases inherent in human decision makers.

Managers' attention is a scarce resource in complex innovation settings. Prior research on the factors to which managers pay attention is mostly based on surveys. The present study aims to address the need for knowledge about the behavior of decision makers based on observations from portfolio meetings. The study seeks to investigate how managers allocate their attention and the role of different factors for their attention. Observations also make it possible to compare prior research and expectations with the actual observed behavior of decision makers.

The present analysis draws on insights from previous research into decision making in product and portfolio management and studies on organizational decision making. The authors frame why the attention of decision makers is so critical in complex situations. Data for this study were collected through direct observation, from a portfolio management system, and from an information quality measurement system in an internationally operating petrochemical company. Observations were transcribed, coded and analyzed with regression analysis using the Proc Lifereg procedure in SAS.

Six potential factors that might explain decision makers' attention are identified. The analysis shows that the quality of information was not significant for explaining variations of decision makers' attention; but, even more surprisingly, differences in project status did not explain variations in attention. Delayed projects did not get significantly more attention than those delivered on time. By controlling for other project characteristics, the newness of projects to the corporate portfolio was found to be the most important parameter.

First, the analysis is based on observations from actual meetings rather than from surveys. Second, several observations contradict prior research on product development, e.g. it has been argued that decision makers should pay special attention to certain phases and projects having trouble meeting expectations towards planned deadlines. It is also new that findings on the different treatment of new projects and ongoing projects have been brought forward in research on product and portfolio management.

The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

As a high school senior, there was no doubt I wanted to attend college, it was just a matter of where. I applied to only two universities – Oakland University (OU) and MSU. I was not too familiar with MSU, but it had a good reputation; I was much more familiar with Oakland. Although I had obtained an application for the University of Michigan (UM), I decided that the UM application was just too long to complete. And what the heck is a wolverine anyway? I lived in Michigan for most of my life, and I had never spotted this mythical rodent. As a tendency, I always found Michigan students and alumni to be either too arrogant or eccentric for my taste. Also, at that time of my life, I found the atmosphere in Ann Arbor not right in some way, so I applied to only two universities.¹

Over the past twenty years, the management of F. Hoffman‐La Roche, a Swiss multinational pharmaceutical and chemical producer, has developed a comprehensive process for the analysis of important investment decisions. This process has evolved gradually and naturally, according to management needs and readiness. Today it embodies a full range of decision and risk analysis procedures, which allow rapid but thorough quantitative evaluations of important investment, business development and strategy decisions. The results of this analytical process are routinely presented to top management. In addition, the quantitative evaluation is actively sought out by line managers and functional experts throughout the company.

This study aims to examine how embeddedness influences consultants' information seeking when making decisions within a social network of relationships, and how these social networks evolve throughout the project delivery stages. The study is grounded in social network theory and examines embeddedness from three perspectives: structural (network cohesion), relational (tie strength in terms of friendship and knowledge awareness) and actor prominence.

A social network analysis (SNA) questionnaire was administered to a team of consultants working on a management consultancy project in Shanghai, China. The SNA measures of density, degree centrality and betweenness centrality were used to analyse relationship patterns among project team members, permitting comparison between the networks. Networks were also compared across the three project delivery stages of collect, consider and create.

Structural embeddedness was observed in the active information seeking behaviour among consultancy team members. The moderate network density of the self-organising information seeking networks across the project delivery stages ensures that the team remains connected but avoids information redundancy and overload. Relational embeddedness was evident through the multiplexity of ties among team members with overlapping friendship and information seeking relationships. The knowledge awareness network's sparseness indicates a team of autonomous knowledge workers with distributed expertise. Project managers were the most prominent actors across the three project delivery stages, underlining these actors' relational leadership role.

The study provides a deeper understanding of collaborative decision-making behaviours in dynamic-project environments. Limited attempts have been made to visualise and analyse the relationships involved in small consulting teams. The novelty of the network approach adopted stems from its ability to offer a structural view of the relationship among consultants, thus offering a distinctive and arguably more complete picture of consultancy team dynamics.

The study validates the social network theory of embeddedness in a real-world collaborative decision-making setting and provides a deeper understanding of information seeking behaviours for decision-making in dynamic-project environments. From a project management process viewpoint, the evolving nature of the information seeking network as it changes across the project stages with associated actors' roles was also visualised graphically, offering a distinctive and arguably more complete picture of consultancy team dynamics.

The electric utility industry, unlike most other technology‐intensive industries, does not spend much money or effort on research and development. Many utilities do not possess an in‐house R&D facility, nor is there an R&D line item in their budgets. Over the last several decades the rate of change in the electric utility industry has been very slow and in‐house R&D efforts have not been required. As the rate of change in the industry is beginning to change, the need to pursue R&D is increasing. The electric utility industry is responding to this increasing requirement by increasing R&D budgets, and in some cases re‐initiating the R&D process within individual utilities. The purpose of this paper is to focus on R&D portfolio management efforts of various actors from different industrial sectors, to find out the best practices by using benchmarking method.

The paper used case study approach and on‐site interviews as research methods.

The authors found that R&D management is in its infancy in the electric utility sector, while the methods established in the manufacturing sector are applicable there.

This study is exploring R&D management in the electric utility sector and contributes to the service innovation research stream.