Jack Brimberg and W. J. Hurley
In this paper, we argue that a better information system is unlikely to solve the problem of lapsed funding that characterizes many government departments. This result is shown to…
Abstract
In this paper, we argue that a better information system is unlikely to solve the problem of lapsed funding that characterizes many government departments. This result is shown to depend critically on the nature of government costs.
Thaddeus Sim and Ronald H. Wright
Historical stock prices have long been used to evaluate a stock’s future returns as well as the risks associated with those returns. Similarly, historical dividends have been used…
Abstract
Historical stock prices have long been used to evaluate a stock’s future returns as well as the risks associated with those returns. Similarly, historical dividends have been used to evaluate the intrinsic value of a stock using, among other methods, a dividend discount model. In this chapter, we propose an alternate use of the dividend discount model to enable an investor to assess the risks associated with a particular stock based on its dividend history. In traditional applications of the dividend discount model for stock valuation, the value of a stock is the net present value of its future cash dividends. We propose an alternative approach in which we calculate the internal rate of return for a stream of future cash dividends assuming the current stock price. We use a bootstrapping approach to generate a stream of future cash dividends, and use a Monte Carlo simulation approach to run multiple trials of the model. The probability distribution of the internal rates of return obtained from the simulation model provides an investor with an expected percentage return and the standard deviation of the return for the stock. This allows an investor to not only compare the expected internal rates of return for a group of stocks but to also evaluate the associated risks. We illustrate this internal rate of return approach using stocks that make up the Dow Jones Industrial Average.
Details
Keywords
Clifford P. McCue, Eric Prier and Ryan J. Lofaro
The purpose of this study is to analyze year-end spending practices in the European Economic Area (EEA) to baseline the pervasiveness of year-end spending spikes across countries…
Abstract
Purpose
The purpose of this study is to analyze year-end spending practices in the European Economic Area (EEA) to baseline the pervasiveness of year-end spending spikes across countries in Europe.
Design/methodology/approach
The Tenders Electronic Daily dataset is used to descriptively analyze above-threshold procurement contracts by country, year and contract type from 2009 to 2018. Proportional distributions are employed to compare percentages of spend across quarters. Analyses are run within each country on the number of years displaying a fourth quarter spike, as well as within each country and contract type.
Findings
The results show that while spending spikes for above-threshold contracts in the final fiscal quarter are not consistent across all countries, patterns emerge when the data are disaggregated by country. The most populous nations in the EEA are more likely to have years with the highest proportion of fiscal spend occurring in the fourth quarter. Further, the type of contract makes a difference – services and supplies contracts are more likely to display fourth quarter spikes than works contracts.
Originality/value
This article provides the first analysis of the year-end spending spike across countries in Europe using procurement data, as well as the first to disaggregate by year and contract type. Findings support the literature on the presence of year-end spikes; such spikes exist even for above-threshold public procurement contracts.
Details
Keywords
Giuseppe Timperio, Gajanan Bhanudas Panchal, Avinash Samvedi, Mark Goh and Robert De Souza
The purpose of this paper is to provide a decision support framework for locations identification to address network design in the domain of disaster relief supply chains. The…
Abstract
Purpose
The purpose of this paper is to provide a decision support framework for locations identification to address network design in the domain of disaster relief supply chains. The solution approach is then applied to a real-life case about Indonesia.
Design/methodology/approach
An approach integrating geographic information system technology and fuzzy analytical hierarchy process has been used.
Findings
For the Indonesian case, distribution centers should be located in Pekanbaru, Surabaya, Banjarmasin, Ambon, Timika, and Manado.
Research limitations/implications
The main limitation of this work is that facilities being sited are incapacitated. Inclusion of constraints over capacity would elevate the framework to a further level of sophistication, enabling virtual pool of inventory that can be used to adsorb fluctuation in the demand due to disasters.
Practical implications
The use case provided in this paper shows a practical example of applicability for the proposed framework. This study is able to support worldwide decision makers facing challenges related with disaster relief chains resilience. In order to achieve efficiency and effectiveness in relief operations, strategic logistics planning in preparedness is key. Hence, initiatives in disaster preparedness should be enhanced.
Originality/value
It adds value to the previous literature on humanitarian logistics by providing a real-life case study as use case for the proposed methodology. It can guide decision makers in designing resilient humanitarian response, worldwide. Moreover, a combination of recommendations from humanitarian logistics practitioners with established models in facility location sciences provides an interdisciplinary solution to this complex exercise.
Details
Keywords
Arpan Kumar Kar and Ashis Kumar Pani
The application of theories on group decision support is yet to be explored extensively in supplier selection literature, although the literature in both domains is extremely…
Abstract
Purpose
The application of theories on group decision support is yet to be explored extensively in supplier selection literature, although the literature in both domains is extremely rich, in isolation. The purpose of this paper is to explore the application of group decision support theories for supplier selection.
Design/methodology/approach
The row geometric mean method (RGMM) of the analytic hierarchy process (AHP) has been used in this study for the prioritization of group preferences under consensus. A case study was conducted to test the theories of consensual group decision making and compare it with other approaches based on AHP.
Findings
The study establishes that the application of decision support theories for group decision making can improve the supplier selection process. Findings further imply that RGMM is more effective than eigen value method, for group decision making under consensus.
Research limitations/implications
Methodologically, the study highlights the greater regularity in outcome of group decision making, vis-à-vis individual decision making, for the same decision-making context. Also, it highlights how RGMM is more effective since it preserves reciprocal properties and diversity in preferences better.
Practical implications
The study establishes that firms can improve supplier selection processes by leveraging on the collective expertise of a group rather than depending on individual decision-making expertise.
Originality/value
This study explores the application of different theories based on AHP for consensual group decision making. It compares different approaches based on AHP and establishes that RGMM is a superior approach for supplier selection.
Details
Keywords
Richard A. Lewin, Marc J. Sardy and Stephen E. Satchell
Investors often have much of their portfolios invested in equities that are exposed to interest rate risk. Hedging underlying exposures are not easy; whereas fixed income…
Abstract
Investors often have much of their portfolios invested in equities that are exposed to interest rate risk. Hedging underlying exposures are not easy; whereas fixed income investors have duration to immunize bond portfolios from small fluctuations in interest rates. US equity duration estimates from dividend discount models result in long durations – often in excess of 50 years. Based on the UK data, we develop an alternative approach to generate equity duration as a by-product of asset pricing. Our analysis suggests that the equity premium puzzle may comprise an important element in reconciling this approach to equity duration, with traditional DDM alternatives.
Hamed Maleki and Mohammad Taghi Taghavi Fard
The time required for a certain task to be performed normally reduces on its frequent completion, as more units are produced over time, it is expected to have an increase in the…
Abstract
Purpose
The time required for a certain task to be performed normally reduces on its frequent completion, as more units are produced over time, it is expected to have an increase in the total worker’s output performance. Learning curve (LC) is a mathematical representation to estimate the time of tasks which occurs repeatedly. The parameter prediction is considered a major disadvantage from which LC suffers. The purpose of this paper is to investigate grey systems theory as a method for the standard time.
Design/methodology/approach
The proposed method starts with data which are obtained by traditional time study and then, models LC for an assembling activity of Electrogen Company. The paper studies the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint triangular whitenization functions and center-point triangular whitenization functions. The grey system results are compared with those of the LC.
Findings
The results show that the standard time given by grey systems theory is closer than the standard time given by LC to standard time with 100 per cent performance level.
Originality/value
Scheduling problems are complex and uncertain, and it is very rare for such systems to be exactly determined in all their complexity. According to grey systems theory, the job processing time can be considered as the object that extension is definite but intension is uncertain. Consequently, grey systems theory with its focus on the uncertainty problems of small samples and incomplete information is proposed in the paper.
Details
Keywords
Heap‐Yih Chong and Rosli Mohamad Zin
The purpose of this research is to discover the behavior of dispute resolution in the Malaysian construction industry by analyzing factors that affect the selection of dispute…
Abstract
Purpose
The purpose of this research is to discover the behavior of dispute resolution in the Malaysian construction industry by analyzing factors that affect the selection of dispute resolution methods using factor analysis approach.
Design/methodology/approach
Preliminary interviews and a questionnaire survey were conducted. Dispute resolution methods were grouped and discussed together, based on the similarity of their characteristics, and used for the questionnaire survey. This research approach is different from the earlier studies that mostly focused on a single dispute resolution method. The data were further analyzed with factor analysis. This improved the data interpretation.
Findings
Seven latent factors were extracted and revealed that the contractors and developers preferred alternative dispute resolution (ADR). However, the appreciation of the outcomes of ADR was perceived to be very low. Arbitration and litigation were in part accepted and agreed upon by the respondents.
Originality/value
The combined results from the literature review on the stages of dispute resolution and the latent factors affecting the selection of dispute resolution methods could assist in decision making. The selection of ADR or non‐ADR itself is not a major issue; rather, there is a concern for increased efficiency and an appreciation of the methods in the construction industry are more demanding.
Details
Keywords
Mark P. Pritchard and Daniel C. Funk
Current research has largely overlooked importance as a meta‐attitude consumers develop from related judgments. Drawing from observations by consumer theorists and attitude…
Abstract
Purpose
Current research has largely overlooked importance as a meta‐attitude consumers develop from related judgments. Drawing from observations by consumer theorists and attitude strength researchers, the present study seeks to investigate the formation and effect of attitude importance in an experiential setting, spectator sport.
Design/methodology/approach
The study adapts a stimulus‐response framework to conduct a structural examination of attitude importance. The investigation includes a multi‐stage sampling procedure that distributed surveys to spectators attending five professional sport matches (n=370).
Findings
Path analysis of a multiple indicator‐multiple cause (MIMIC) model revealed that perceptions of technical and functional aspects of the service experience fuel a meta‐attitude of importance. When evident in dual judgments of product interest and brand importance, the construct is able to play a significant role in patron responses.
Research limitations/implications
These findings offer insight on the nature of importance and its role in moderating spectator behavior. Support for the structural sequence also holds implications for researchers interested in delineating other strong attitudes. However, study findings are limited to hedonic service consumers and await replication in other product settings.
Practical implications
Practical implications consider different mixes of dual judgments and strategies organizations might use to leverage a meta‐attitude of importance in their patrons. Examples of scenario‐based challenges to managing this disposition in the sport industry and in other consumer contexts are discussed.
Originality/value
Despite early attention by marketing practitioners on the importance of individual product features, explanations of how a larger meta‐attitude forms and affects customers are rare. The study developed a MIMIC model and used path analysis to address the matter.