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Article
Publication date: 3 May 2013

Richard Hauser

The purpose of this paper is to investigate whether corporate dividend policy changed during the financial crisis.

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Abstract

Purpose

The purpose of this paper is to investigate whether corporate dividend policy changed during the financial crisis.

Design/methodology/approach

For this study, a life‐cycle model is used to predict the probability that a firm pays a dividend. The data sample for this research follows that of Fama and French and of DeAngelo et al., for the time period of 2006‐2009. The panel logistic regression analysis considers the firm cluster effects and the autoregressive correlation of the firm clusters.

Findings

This study shows evidence that the probability that a firm paid a dividend declined in 2008 and 2009, even after taking the firm's financial condition into account. Furthermore, the analysis also shows that dividend policy did shift during the financial crisis.

Originality/value

The results of this study show that dividend policy did shift during the financial crisis. The research provides evidence that firms placed additional emphasis on financial viability after the financial crisis.

Details

Managerial Finance, vol. 39 no. 6
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 10 June 2021

Naman S. Bajaj, Sujit S. Pardeshi, Abhishek D. Patange, Hrushikesh S. Khade and Kavidas Mate

Several national- and state-level studies have been predicting the course of the COVID-19 pandemic using supervised machine learning algorithms. However, the comparison of…

Abstract

Purpose

Several national- and state-level studies have been predicting the course of the COVID-19 pandemic using supervised machine learning algorithms. However, the comparison of such models has not been discussed before. This is the first-ever research wherein the two leading models, susceptible-infected-recovered (SIR) and logistic are compared. The purpose of this study is to observe their utility, at both the National and Municipal Corporation level in India.

Design/methodology/approach

The modified SIR and the logistic were deployed for analysis of the COVID-19 patients’ database of India and three Municipal Corporations, namely, Akola, Kalyan-Dombivli and Mira-Bhayander. The data for the study was collected from the official notifications for COVID-19 released by respective government websites.

Findings

This study provides evidence to show the superiority of the modified SIR over the logistic model. The models give accurate predictions for a period up to 14 days. The prediction accuracy of the models is limited due to change in government policies. This can be observed by the drastic increase in the COVID-19 cases after Unlock 1.0 in India. The models have proven that they can effectively predict for both National and Municipal Corporation level database.

Practical implications

The modified SIR model can be used to signify the practicality and effectiveness of the decisions taken by the authorities to contain the spread of coronavirus.

Originality/value

This study modifies the SIR model and also identifies and fulfills the need to find a more accurate prediction algorithm to help curb the pandemic.

Details

Information Discovery and Delivery, vol. 49 no. 3
Type: Research Article
ISSN: 2398-6247

Keywords

Article
Publication date: 5 November 2019

R. Dale Wilson and Harriette Bettis-Outland

Artificial neural network (ANN) models, part of the discipline of machine learning and artificial intelligence, are becoming more popular in the marketing literature and…

Abstract

Purpose

Artificial neural network (ANN) models, part of the discipline of machine learning and artificial intelligence, are becoming more popular in the marketing literature and in marketing practice. This paper aims to provide a series of tests between ANN models and competing predictive models.

Design/methodology/approach

A total of 46 pairs of models were evaluated in an objective model-building environment. Either logistic regression or multiple regression models were developed and then were compared to ANN models using the same set of input variables. Three sets of B2B data were used to test the models. Emphasis also was placed on evaluating small samples.

Findings

ANN models tend to generate model predictions that are more accurate or the same as logistic regression models. However, when ANN models are compared to multiple regression models, the results are mixed. For small sample sizes, the modeling results are the same as for larger samples.

Research limitations/implications

Like all marketing research, this application is limited by the methods and the data used to conduct the research. The findings strongly suggest that, because of their predictive accuracy, ANN models will have an important role in the future of B2B marketing research and model-building applications.

Practical implications

ANN models should be carefully considered for potential use in marketing research and model-building applications by B2B academics and practitioners alike.

Originality/value

The research contributes to the B2B marketing literature by providing a more rigorous test on ANN models using B2B data than has been conducted before.

Details

Journal of Business & Industrial Marketing, vol. 35 no. 3
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 21 June 2013

Taegu Kim, Jungsik Hong and Hoonyoung Koo

The purpose of this study is to propose a systematic method for the diffusion of forecasting technology in the pre‐launch stage.

Abstract

Purpose

The purpose of this study is to propose a systematic method for the diffusion of forecasting technology in the pre‐launch stage.

Design/methodology/approach

The authors designed survey question items that are familiar to interviewees as well as algebraically transformable into the parameters of a logistic diffusion model. In addition, they developed a procedure that reduces inconsistency in interviewee responses, removes outliers, and verifies conformability, in order to reduce the error and yield robust estimation results.

Findings

The results show that the authors' method performed better in the empirical cases of digital media broadcasting and internet protocol television in terms of sum of squared error compared with an existing survey‐based method, a regression method, and the guessing‐by‐analogy method. Specifically, the authors' method can reduce the error by using the conformability and outlier tests, while the consistency factor contributes to determining the final estimate with personal estimates.

Research limitations/implications

The procedure proposed in this study is confined to the presented logistic model. Future research should aim to extend its application to other representative diffusion models such as the Bass model and the Gompertz model.

Practical implications

The authors' method provides a better quality of forecasting for innovative new products and services compared with the guessing‐by‐analogy method, and it contributes to managerial decisions such as those in production planning.

Originality/value

The authors introduce the concepts of conformability and consistency in order to reduce the error from personal biases and mistakes. Based on these concepts, they develop a procedure to yield robust estimation results with less error.

Details

Industrial Management & Data Systems, vol. 113 no. 6
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 5 April 2022

Mauro Vivaldini

This study discusses the influence of logistical immediacy on logistics service providers' (LSPs’) business. Specifically, its role in the face of the emerging business…

Abstract

Purpose

This study discusses the influence of logistical immediacy on logistics service providers' (LSPs’) business. Specifically, its role in the face of the emerging business scenario (e-commerce, disruptive technologies, and new models of logistical services) is examined.

Design/methodology/approach

As logistical immediacy is a nascent topic, this study utilizes a systematic literature review focusing on academic articles from the last five years related to logistical outsourcing to understand the changes imposed by logistical immediacy on LSPs.

Findings

The impact of transformations arising from an increasingly digital virtual world (DVW) on LSPs is contextualized. A theoretical view of the factors affecting LSPs' shift towards more immediate operations is presented, and how logistical immediacy impacts LSPs is discussed. Finally, a research agenda is presented as the study's main contribution.

Research limitations/implications

Due to the timeframe chosen, the restriction to a single database (Scopus), the specific search terms used related to LSPs, and limiting the search parameters to operations management, some relevant work may have been overlooked.

Practical implications

The article help LSPs' and contracting companies' managers to understand the influence of the immediacy expected in logistics operations. Possible logistics services trends and how they may impact companies are discussed.

Originality/value

This is one of the first articles in the area of operations and supply chains that addresses the issue of logistical immediacy and its impact on LSPs.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 24 April 2007

Yongyut Meepetchdee and Nilay Shah

This paper aims to propose a logistical network design framework with robustness and complexity considerations.

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Abstract

Purpose

This paper aims to propose a logistical network design framework with robustness and complexity considerations.

Design/methodology/approach

The paper defines robustness, complexity, and normalised efficiency of a logistical network. A mathematical model is then constructed based on the conceptual framework and applied to a hypothetical case study with varying robustness requirements. The mathematical model is formulated as an Mixed‐Integer Linear Programming problem. Furthermore, the paper introduces a graph‐theoretic view of the logistical network and presents its topological properties such as average path length, clustering coefficient, and degree distribution.

Findings

The results show that logistical network configurations can be obtained with desirable robustness levels whilst minimising cost. The relationships of robustness versus normalised efficiency and complexity are also presented. The results show that relationships between logistical network topological properties and robustness exist, as in other real world natural and man‐made complex networks.

Practical implications

Logistical network design is one of the earliest strategic decisions in supply chain management that supply chain managers have to make. Practitioners and researchers typically focus on optimising efficiency and/or responsiveness of logistical networks. It is argued that logistical network designers should also consider robustness and complexity as they are important characteristics of logistical network functionality. The logistical network design frame work successfully incorporates robustness and complexity into design considerations.

Originality/value

This paper newly introduces other important performance measures, robustness and complexity, into the logistical network design objective. The design framework is highly relevant and adds value to logistical network designers and managers.

Details

International Journal of Physical Distribution & Logistics Management, vol. 37 no. 3
Type: Research Article
ISSN: 0960-0035

Keywords

Article
Publication date: 1 April 2006

Peter Nyhuis and Markus Vogel

To provide a model for precise logistic controlling of one‐piece flow processes and for the description of the interactions between logistic performance measures. The…

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Abstract

Purpose

To provide a model for precise logistic controlling of one‐piece flow processes and for the description of the interactions between logistic performance measures. The developed method can help manufacturing enterprises to control their production processes and therewith to exploit existing rationalization potentials in their production.

Design/methodology/approach

The Institute of Production System and Logistics adapted the logistic operating curve for schedule reliability and the logistic operating curve for mean throughput time to describe the behaviour of one‐piece flow processes. This model‐based method depicts the correlation between the delivery reliability and mean WIP level of single manufacturing systems and enables a goal‐oriented modelling as well as a controlling of single manufacturing processes.

Findings

The derivation, calculation, and fields of application of the logistic operating curves for one‐piece flow processes, that give a functional relationship between mean WIP, mean throughput time and schedule reliability, are presented in this paper. Moreover, the paper presents how the logistic performance measures can be adjusted to target values.

Originality/value

This paper offers practical help to manufacturing enterprises confronted with the task of evaluation and optimization of manufacturing processes within the framework of production controlling. Moreover, the developed method enables manufacturing enterprises to identify bottleneck work systems where action can be taken to optimize their schedule situation and thereby improve the delivery reliability of an entire manufacturing department.

Details

International Journal of Productivity and Performance Management, vol. 55 no. 3/4
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 5 June 2007

Serkan Akinci, Erdener Kaynak, Eda Atilgan and Şafak Aksoy

The objective of this article is to determine the usage and application of logistic regression analysis in the marketing literature by comparing the market positioning of…

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Abstract

Purpose

The objective of this article is to determine the usage and application of logistic regression analysis in the marketing literature by comparing the market positioning of prominent marketing journals.

Design/methodology/approach

In order to identify the logistic regression applications, those journals having “marketing” term in their titles and indexed by the social citation index (SSCI) were included. As a result, the target population consisted of 12 journals fulfilling the criteria set. However, only eight of these that were accessible by the researchers were included in the study.

Findings

The classification of marketing articles from the chosen prominent marketing journals were made by journal title, article topic, target population, data collection method, and study location has mapped the position of logistic regression in the marketing literature.

Research limitations/implications

The sample journal coverage was limited with 12 marketing journals indexed in SSCI. In some of the journals utilized, the accessibility was limited by the electronic database year coverage. Due to this limitation, the researchers could not reach the exact number of articles using logistic regression.

Originality/value

The results of this study could highlight what is researched with logistic regression about marketing problems and may shed light on solving different problems on marketing topics for the future.

Details

European Journal of Marketing, vol. 41 no. 5/6
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 16 March 2010

Cataldo Zuccaro

The purpose of this paper is to discuss and assess the structural characteristics (conceptual utility) of the most popular classification and predictive techniques…

1965

Abstract

Purpose

The purpose of this paper is to discuss and assess the structural characteristics (conceptual utility) of the most popular classification and predictive techniques employed in customer relationship management and customer scoring and to evaluate their classification and predictive precision.

Design/methodology/approach

A sample of customers' credit rating and socio‐demographic profiles are employed to evaluate the analytic and classification properties of discriminant analysis, binary logistic regression, artificial neural networks, C5 algorithm, and regression trees employing Chi‐squared Automatic Interaction Detector (CHAID).

Findings

With regards to interpretability and the conceptual utility of the parameters generated by the five techniques, logistic regression provides easily interpretable parameters through its logit. The logits can be interpreted in the same way as regression slopes. In addition, the logits can be converted to odds providing a common sense evaluation of the relative importance of each independent variable. Finally, the technique provides robust statistical tests to evaluate the model parameters. Finally, both CHAID and the C5 algorithm provide visual tools (regression tree) and semantic rules (rule set for classification) to facilitate the interpretation of the model parameters. These can be highly desirable properties when the researcher attempts to explain the conceptual and operational foundations of the model.

Originality/value

Most treatments of complex classification procedures have been undertaken idiosyncratically, that is, evaluating only one technique. This paper evaluates and compares the conceptual utility and predictive precision of five different classification techniques on a moderate sample size and provides clear guidelines in technique selection when undertaking customer scoring and classification.

Details

Journal of Modelling in Management, vol. 5 no. 1
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 3 November 2021

Mohammad Mahdi Ershadi and Mohamad Sajad Ershadi

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective…

Abstract

Purpose

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.

Design/methodology/approach

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.

Findings

The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

Practical implications

The proposed methodology can be applied to find the best logistic plan in real situations.

Originality/value

In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 16 no. 1
Type: Research Article
ISSN: 1750-6123

Keywords

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